USSR: MEASURES OF ECONOMIC GROWTH AND DEVELOPMENT, 1950-80

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05210421
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December 8, 1982
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Approved for Release: 2019/07/19 C05210421 C 97th Congress 1 24 Session f JOINT COMMITTEE PRINT USSR: MEASURES OF ECONOMIC GROWTH AND DEVELOPMENT, 1950-80 STUDIES PREPARED FOR THE trsz OF THE JOINT ECONOMIC COMMITTEE CONGRESS OF THE UNITED STATES DECEMBER 8, 1982 Printed for the use of the Joint Ee0110Mie Committee Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 97th Congress 2d Session f JOINT COMMITTEE PRINT USSR: MEASURES OF ECONOMIC GROWTH AND DEVELOPMENT, 1950-80 STUDIES PREPARED FOR THE USE OF THE JOINT ECONOMIC COMMITTEE CONGRESS OF THE UNITED STATES DECEMBER 8, 1982 Printed for the use of the Joint Economic Committee U.S. GOVERNMENT PRINTING OFFICE 93-8920 WASHINGTON: 1982 For sale by the Superintendent of Documents. U.S. Government Printing Office Washington, D.C. 20402 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 JOINT ECONOMIC COMMITTEE (Created pursuant to sec. 5(a) HOUSE OF REPRESENTATIVES HENRY S. REUSS, Wisconsin, Chairman RICHARD BOLLING, Missouri LEE H. HAMILTON, Indiana GILLIS W. LONG, Louisiana PARREN J. MITCHELL, Maryland AUGUSTUS F. HAWKINS, California CLARENCE J. BROWN. Ohio MARGARET M. HECKLER, Massachusetts JOHN II. ROUSSELOT, California CHALMERS P. WYLIE, Ohio of Public Law 304, 79th Cong.) SENATE ROGER W. JEPSEN, Iowa, Vice Chairman WILLIAM V. ROTH, JR., Delaware JAMES ABDNOR, South Dakota STEVEN D. SYMMS, Idaho PAULA HAWKINS, Florida MACK MATTINGLY, Georgia LLOYD BENTSEN, Texas WILLIAM PROXMIRE, Wisconsin EDWARD M. KENNEDY, Massachusetts PA UL S. SARBANES, Maryland JAMES K. GALBRAITH. Executive Director BRUCE R. BARTLETT, Deputy Di/ ector (II) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 LETTERS OF TRANSMITTAL OcTonlin 28, 1982. To the Members of the Joint Economic Committee: I am transmitting for the use of the Members of the Joint Economic Com- mittee, other Members of Congress, and the public a volume of studies entitled "USSR: Measures of Economic Growth and Development, 1950-80." The volume was prepared by the Central Intelligence Agency at the reque,st of the Joint Economic Committee. The volume contains a series of tables estimating the Soviet gross national product and its components. Separate sections cover industrial production, agri- culture, and consumption. Part 1 contains estimates of Soviet GNP by sector of origin and end use. Part II is an index of Soviet industrial production. Part III is an index of agricultural production. Part IV is an index of consumption. The studies also describe the methodology and data used. The Joint Economic Committee is pleased to publish this study in the hopes that it will help improve our understanding of the Soviet economy. These studies fill a long-term gap in the West created by Soviet secrecy and deficiencies in the publication of official economic data as well as differences in the economic accounting system used in that country. The project was super- vised for the Joint Economic Committee by Richard F. Kaufman. Sincerely, HENRY S. REUSS, Chairman, Joint Economic Committee. OCTOBER 26, 1982. Hon. HENRY S. REUSS, Chairman, Joint Economic Committee, Congress of the United States, Washington, D.C. DEAR MR. CIIAIRMAN : The attached is a volume of studies entitled "USSR: Measures of Economic Growth and Development, 1950-80." The studies were prepared by specialists at the Central Intelligence Agency at the request of the Committee. Taken together, they represent an up-to-date, comprehensive, quan- tified assessment of the Soviet economy. Sincerely, RICHARD F. KAUFMAN. Assistant Director, Joint Economic Committee. (III) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 FOREWORD By Chairman Henry S. Reuss The Soviet Union does not publish measures of economic growth and devel- opment comparable with those of Western countries. Rather, it publishes measures of growth that are geared to its own definitions of economic phenom- ena and its own political requirements. In addition, it follows a policy of secrecy with regard to much of its economic activities and has been inconsistent in the comparability and coverage of the economic statistics that are published. The result is a large gap in the information available in the West concerning the performance of the Soviet economy. To help fill this gap, the Central Intel- ligence Agency (CIA) has been called upon to provide quantified estimates of the value of Soviet gross national product (GNP), its rate of growth, its size relative to U.S. GNP, and its allocation among the various end uses--consump- tion, investment, and government expenditures, including defense. The studies contained in this volume are the culmination of a large re- search effort over many years carried out by CIA's Directorate for Intelligence. The estimates of GNP and its components, which are included, are virtually the only independent Western estimates of these important measures of economic performance in the Soviet Union. Earlier results of this work have appeared in various Joint Economic Committee studies of the Soviet economy and CIA's annual Handbook of Economic Statistics. This publication is the first time that the concepts, methodologies, and data have been fully explained and docu- mented in a comprehensive and up-to-date form. The studies include separate sections devoted to agriculture and industry� the major components of the originating sectors in the GNP, and to consump- tion�the principal end-use sector. Part I discusses the overall estimates of Soviet GNP by sector of origin and end use. Each of the remaining three studies analyzes in detail a major component of GNI'. Part II contains an index of in- dustrial production. Part III is an index of agricultural production. And the final part is an index of consumption. Indices for all other sectors are included in Part I. Each study includes detailed compilations of the data used, their sources, and the methodologies used to combine the data into the aggregate measures. The goals of this publication are to achieve a wider understanding of how the synthetic measures of Soviet economic performance are derived, to encourage their broader use in analyses of Soviet economic performance, and to stimulate discussion of ways to improve these measures and our general understanding of the Soviet economy. NECESSITY To CALCULATE INDEPENDENT MEASURES There are several reasons for the calculation of independent measures of Soviet economic performance. The deficiencies of official Soviet measures of economic activity are well documented. Official Soviet measures are often con- ceptually different from the measures used in the West, are not published in sufficient detail, are sometimes published in noncomparable series, and tend to inflate real growth rates. The official Soviet measure of economic growth, referred to as net material product, includes only the value added in the production of goods, and a few services. The value added in the rest of the service sector and all depreciation (V) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 N-I income is excluded. Thus, Soviet net material product omits about one-fourth of the resources used to produce goods and servk.es in the USSR. In addition, there is an upward bias in official measures of activity. The result is that Soviet statistics on net material product provide an incomplete and distorted view of the size and growth of the Soviet economy. The need for independent measures of economic performance is heightened by the sparseness of official data and their inconsistencies. The official data tend to be published in insufficient detail, the price base of sonic series are periodically changed, and the product coverage may be altered without notice. For example, because the official measure of consumption referred to as "real incomes of the population," is not described adequately, its validity or usefulness cannot be fully assessed. The official series shows a higher growth rate than does the synthetically construdted index of consumption, in part because of the failure of the official series to take inflation into account. The Soviet indices of industrial and agricultural production are based on gross output rather than value added. As a consequence, double counting of materials used in production is incorporated in the indices. There is con- siderable evidence that the official index for industrial production has serious short-comings due to the treatment of price and quality changes. There is much evidence that prices assigned to new industrial products are too high relative, to prices for older products in view of the changes in technology and quality taking place. In the consumer sector, there is considerable evidence that new, high-priced but only slightly altered products are deliberately stibstituted for equivalent, low-priced products to syphon-off consumer purchasing power. The official data treat such changes as if there were no real price increases, thus incorporating hidden inflation. THE GENERAL APPROACH The value of GNP can be calculated in two ways. One way is to derive GNP as the sum of the various end uses of the goods and services�consumption, investment, and government (both military and civilian). GNP can also be computed as the sum of value added in the several production sectors�industry, agriculture, and the like. The intent of these studies is to replicate as far as possible, on both the sector of origin and end use sides of the accounts, the methodologies developed by the U.S. Department of Commerce and the OECD for the construction of Western economic accounts. Precise conformity is not possible, primarily be- cause the organization of the Soviet economy and the limited amount of data published by the Soviet Union require modifications and simplifications of the Western accounting framework. Defense expenditures are the most conspicuous example. Total defense is not identified separately in the Soviet GNP accounts contained in this volume because other GNP components, primarily investment and research and development expenditures, are thought to include substantial amounts of defense expenditures. As a separate exercise, the CIA estimates total defense expenditures directly from a detailed description of their defense programs and activities. The defense estimates have been explained and dis- cussed in the Joint Economic Committee's annual hearings on the "Allocation of Resources in the Soviet Union and China." Despite the limitations, it is believed that the measures developed�both the configuration of trends and absolute size�are reasonably accurate representa- tions of Soviet economic performance, can be compared with confidence with similar measures for Western economies, and are far more acceptable indicators of economic performance than the corresponding measures published by the USSR. Gross national product is defined as the market value. of the final goods and services produced by a given country. As applied to the Soviet economy, this Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 definition raises theoretical problems. The most important is that the Soviet Union does not have market determined prices. Instead, it uses, for the most part, centrally fixed prices which may be quite far removed from the values that would obtain in a market-oriented economy. Market prices reflecting real resource costs of each product are needed to derive theoretically correct infer- ences about the real growth and distribution of GNP. An important segment of Part I is devoted to computing a set of alternative, factor-cost prices used to replace Soviet prices. The latter are seriously distorted by taxes and sub- sidies and by their failure to incorporate accurately the costs of land and re- producible fixed assets. The factor-cost prices are intended to represent more accurately the actual cost of resources used to produce each category of goods and services. The indices of the growth of GNP and its three major components are computed as weighted averages of subcomponent indices. The weights are 1970 expenditures or value added as derived in the 1970 GNP accounts (Part I, Appendix D). The subcomponent indices are developed from physical produc- tion or consumption data. The index of industrial production is computed from production data on over 300 products. These are grouped first into 10 branches of industry and then into an aggregate index. The index of agricul- tural production, computed by combining production data for 42 types of crops or livestock products, represents the value of all output less that used by agriculture itself�primarily feed and seed. The index of consumption is divided into three major categories of goods and eight categories of services. Each category is further divided into individual products or services. The index of GNP by sector of origin is formed by combining the indices of indus- t rial and agricultural production with similar indices for the remaining pro- duction sectors�transportation, communications, domestic trade, and services. Similarly, GNP by end use is computed by adding indices of investment and other government expenditures, including most of defense outlays. OR PROBLEMS ENCOUNTERED The construction of the independent measures encountered numerous prob- lems. Some are universal to all aggregate measures of economic performance and some are peculiar to the Soviet case. The treatment of quality change, for example, is a universal problem. Most elements of the industrial index are expressed in physical units such as tons or number of items. This procedure may understate quality improvements over time, especially in machinery products. On the other hand, official data, expressed in rubles or as index numbers, are used where physical production data are not available. As indi- cated above, these data clearly overstate growth. Because the biases in official and physical data are offsetting, however, their use in combination should pro- vide a truer measure of real growth. Similarly, the index of housing services in the consumption index is based on the number of square meters of housing without a quality adjustment. In this case, all evidence points to remarkably little improvement in the quality of Soviet housing and there is likely not a serious bias in the housing index. Compiling consistent data for the period 1950-80 presented a challenge. Many of the official data series are incomplete or published in differing formats, requiring many interpolations and strong assumptions about relative prices. Other data are not published at all or not on a regular basis. instead, they have to be culled from the specialized monograph and journal literature. For example, data on the amount of waste included in the gross output data of agricultural products are not published regularly or in a consistent. framework. USES OF '1'11E STUDIES Just as aggregate measures of Western economic performance are used in many different applications, so the results of these studies can be employed Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 VIII in many ways. Foremost is their use in making assessments of the Soviet econ- omy by analyzing the interplay of the disposition of resources for consump- tion, defense, and future growth. Insights into the regime's policies and priori- ties can be obtained by assessing the "burden" of defense and the pattern of allocating the "growth dividend." In addition to being a measure of the size and growth of the economy, GNP also provides a standard against which other economic variables can be measured, such as the amount of energy used per unit of GNP. The G-NP data base forms the foundation for forecasting, either by using large econometric models or other means. Such forecasts not only concern the future growth rate of total GNP, but also can be employed to assess other im- portant variables, such as the domestic demand for oil. The GNP estimates can be used to compare the size of the Soviet economy with the United States or other countries, and the relative priorities each country assigns to the uses of its national product. Such international com- parisons depend, of course, on the domestic value of GNP or one of its com- ponents. For example, an earlier publication in this series estimated the value of Soviet consumption relative to other countries.1 Despite the limitations of the estimates, the work expended on the CIA independent measures represents a valuable contribution to economic analysis of the USSR. The results shown in this volume present a picture of Soviet economic growth different from that given by the official measures. Each of the four studies presents comparative results in detail. By way of swnmary, the following tabulation compares average annual growth rates for the four aggregate indices and their closest Soviet official counterparts for 1951-80: Average annual rate of growth in the years 1951-80 [Percent] CIA Soviet measure measure GNP 1 4.7 7 . 4 Industrial production 6.8 8. 7 Agriculture production 2 2. 8 3. 1 Per capita consumption 3. 5 5.0 The CIA measure for the same coverage as the Soviet measure (see text) is 5.3 percent per year a The measure shown represents "net output," or gross output less products used by agriculture (seed and feed). This is the concept of output closest in coverage to the official Soviet measure of farm output. As a contributing sector to GNP the appropriate measure for agriculture output is value added (net output less material purchases from other sectors) which over this period grew at 2.0 percent per year. It is clear that, except for agriculture, the growth rate differences are large and, over a 30-year period, indicate a significantly different picture of economic growth than that provided by official Soviet statistics. ' "Consumption in the USSR : An International Comparison," U.S. Congress, Joint Economic Committee, August 1981. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 THE CONTRIBUTIONS OF RUSH V. GREENSLADE The research in this volume owes an immense debt to the work of the late Rush V. Greenslade. Dr. Greenslade was employed at the Central Intelligence Agency from the early 1950's until his retirement in 1973. For many years he directed CIA's research on the Soviet economy. After his retirement, he con- firmed as a consultant and advisor to the CIA until his death in 1978. Dr. Greenslade's primary contributions were in the area of quantifying and analyzing Soviet economic development. He developed an index of Soviet in- dustrial production in the 1950's and wrote frequently on industrial trends. He was also closely involved in shaping the analytical framework and in organizing the collection of data for estimates of Soviet GNP. In the early 1970's, he led an effort to convert the GNP estimate to 1970 prices and to reexamine and im- prove all of the methodologies and data supporting these estimates. This work led to the publication by the CIA of a set of GNP accounts for 1970 and an article in the Joint Economic Committee's 1976 compendium on the Soviet economy, "The Real Gross National Product of the U.S.S.R., 1950-1975." This volume extends Dr. Greenslade's work by updating and documenting the 1970 base-year accounts and the many time series used in calculating each sector-of-origin and end-use GNP index. Dr. Greenslade was also deeply involved in the analysis of the size and structure of the Soviet economy in relation to that of the United States and other countries. An earlier volume in this series on Soviet GNP compared Soviet consumption with consumption in the United States and other countries. This project was designed and directed in its early stages by Dr. Greenslade. Dr. Greenslade also played a leading role in forming estimates of the dollar value of Soviet investment based on new ruble-dollar ratios for machinery and construction. The results of this ruble-dollar ratio research were published by the CIA. Dr. Greenslade's research on international economic comparisons culminated in a new comparison of Soviet and United States GNP since 1955 published by Edwards, Hughes, and Noren in the Joint Economic Committee's 1979 compendium on the Soviet economy. (Ix) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 CONTENTS Page Letters of Transmittal III Foreword by Chairman Henry S. Reuss The Contributions of Rush V. Greenslade ix I. Gross National Product of the USSR, 1950-80_ 3 II. An Index of Industrial Production in the USSR 169 III. An Index of Agricultural Production in the USSR 245 IV. An Index of Consumption in the USSR 317 (XI) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 USSR: MEASURES OF ECONOMIC GROWTH AND DEVELOPMENT, 1950-80 Central Intelligence Agency Directorate of Intelligence 1 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part I. GROSS NATIONAL PRODUCT OF THE USSR, 1950-80 By John Pitzer 3 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Contents Page List of Standard Citations 10 Introduction 11 Our Estimates in Perspective 11 Soviet National Income Data 12 The Plan of the Paper 13 Part I. Results and Analysis 15 Soviet Economic Growth in Perspective 15 Changes in Soviet Growth Since 1950 15 The Evolving Structure of the Soviet Economy Changing Patterns of Output Use Soviet Growth in International Perspective 16 18 19 How Reliable Are the Synthetic Measures of Soviet Growth? 23 Sensitivity to the Base Year Used 23 Patterns in the GNP Residual 24 Comparisons With Official Soviet Data Comparisons With Other Western Estimates Part II. Methodology The Accounting Framework The Accounting Units The Main Financial Flows Definitions and Conventions 25 26 27 27 27 29 30 Summary of Differences in the Soviet and US GNP Accounts Valuation Soviet Established Prices Finding a Basis for Valuing Soviet GNP 33 33 34 34 Distortions Caused by Turnover Taxes and Subsidies 35 Variations in Profit Rates 36 Differential Prices and New-Product Pricing 37 The Adjusted Factor-Cost Standard 37 Soviet GNP in 1970 in Established Prices and at Factor Cost 38 The Revised 1970 Soviet GNP Accounts 38 Construction of the 1970 Input-Output Table and Conversion of the 1970 Accounts to Factor Cost 38 A Comparison of Established and Factor-Cost Prices 40 5 93-892 0 - 82 - 2 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Problems in Estimating Volume Indexes of Economic Activity in the USSR 42 Effect of the Base Year on the Growth Rate 42 Aggregation of Quantity Indexes Instead of Deflated Value Indexes 42 Specific Index Number Problems 43 Problems of Measuring the Real Growth of Value Added 44 Soviet GNP Indexes 46 End-Use Indexes 46 Sector-of-Origin Indexes 48 Appendixes A. Soviet Gross National Product, 1950-80 51 B. Sector-of-Origin Indexes 83 C. End-Use Indexes 117 D. Revised 1970 GNP Accounts in Established Prices 125 E. Conversion of 1970 GNP From Established Prices to 163 Factor-Cost Prices Tables 1. Average Annual Rate of Growth of National Product for Selected 20 OECD Countries (GDP) and for the USSR (GNP) 2. Percentage Distribution of National Product by End Use in Selected 21 OECD Countries (GDP) and in the USSR (GNP) 3. Average Annual Rate of Growth of Per Capita Consumption in 22 Selected OECD Countries and the USSR 4. Percentage Distribution of 1960 and 1976 Soviet GNP by Sector of 23 Origin in Current and 1970 Established Prices 5. Turnover Taxes as a Share of Gross Output in Industry, 1972 35 6. Subsidies on Agricultural Products Sold to the Light and Food 36 Industries 7. Profits as a Percent of Productive Fixed and Working Capital in 36 1972 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Gross National Product of the Soviet Union in Established Prices, by Type of Income, 1970 39 Gross National Product of the Soviet Union in Established Prices, by End Use, 1970 39 10. 1970 Soviet Gross National Product by End Use 41 11. 1970 Soviet Gross National Product by Sector of Origin 41 Figures 1. Growth of Soviet GNP 15 2. Annual Soviet GNP Growth Rates 16 16 3. Growth Rates of Soviet GNP and Agriculture 4. Growth Rates of Soviet GNP and Industry 17 5. Distribution of Soviet GNP by Sector of Origin 17 6. Distribution of Soviet GNP by End Use 18 7. The Outlays n.e.c. Residual and a Synthetic Measure 25 8. Annual Growth Rates of Soviet Adjusted GNP and Net Material Product 25 9. Soviet End-Use and Sector-of-Origin GNP Categories 30 Appendix Tables A-1. GNP by Sector of Origin 52 A-2. Average Annual Rates of Growth of GNP by Sector of Origin 55 56 A-3. Annual Growth Rates of GNP by Sector of Origin A-4. Percentage Shares of GNP by Sector of Origin 59 A-5. Indexes of GNP by Sector of Origin 62 A-6. GNP by End Use 65 A-7. Average Annual Rates of Growth of GNP by End Use 68 69 A-8. Annual Growth Rates of GNP by End Use A-9. Per Capita GNP by End Use 72 A-10. Average Annual Rates of Growth of Per Capita GNP by End Use 75 A-11. Percentage Shares of GNP by End Use 76 A-12. Indexes of GNP by End Use 79 B- 1. 1972 Construction Input Weights 85 7 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 B-2. Derivation of the Index of Purchases of Construction Materials by the Construction Sector 86 B-3. Derivation of the Implicit Construction Price Index 87 B-4. Derivation of an Implicit Price Index for Investment in New Construction and Other Capital Outlays 87 B-5. Selected Purchases by Agriculture of Material Inputs From Nonagricultural Sectors in 1972 88 B-6. Derivation of the Index of Purchases of Nonagricultural Material Inputs by Agriculture 89 B-7. Derivation of the Index of Value Added in Agriculture 90 B-8. Gross Output, Total Material Purchases, and Value Added in Agriculture 91 B-9. Data Relating to the Activity of Various Modes of Freight Transportation 94 B-10. Derivation of the Index of Value Added in Transportation 95 B-11. Valuation of Farm Household Consumption in Kind in 1970 Prices 98 B-12. Valuation of Collective Farm Ex-Village Market and Commission Sales in 1970 Prices 100 B-13. Derivation of the Retail Trade Index 102 B-14. Derivation of the Wholesale Trade Index 104 B-15. Computation of the Weights for the Agricultural Procurement Index 105 B-16. Derivation of the Agricultural Procurement Index 106 B-17. Derivation of the Index of Value Added in Trade 108 B-18. Derivation of the Index of Material Purchases by Science 110 B-19. Derivation of the Index of Value Added in Science 111 B-20. Derivation of the Index of Value Added in Credit and Insurance 112 B-21. Man-Hour Employment in Government Administrative Services 114 C-1. Derivation of the Index of Investment in Machinery and Equipment 118 C-2. Derivation of Investment in New Construction and Other Capital Outlays 120 C-3. Derivation of the Index of Capital Repair Expenditures 122 C-4. Estimated Soviet Defense Expenditures, 1951-80 123 D-1. Soviet Household Incomes, 1970 128 D-2. Soviet Household Outlays, 1970 130 D-3. Soviet Public-Sector Incomes, 1970 134 8 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 D-4. Soviet Public-Sector Outlays, 1970 137 141 142 D-5. Soviet Gross National Product in Established Prices by End Use, 1970 D-6. Soviet Gross National Product in Established Prices by Type of Income, 1970 D-7. Soviet Gross National Product in Established Prices by Sector of Origin, 1970 143 D-8. Distribution of the State Wage Bill by Sector of Origin, 1970 145 D-9. State Wages and Salaries, 1970 147 D-10. Distribution of Other and Imputed Income by Sector of Origin, 1970 149 D-11. Distribution of Social Insurance Deductions by Sector of Origin, 1970 151 153 D-I2. Social Insurance Deductions, 1970 D-13. Depreciation by Sector of Origin, 1970 154 D-14. Distribution of Amortization Deductions by Branch of Industry, 1970 157 D-15. Distribution of Profits by Sector of Origin, 1970 158 D-16. Distribution of Turnover and Other Indirect Taxes by Sector of Origin, 1970 160 9 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 List of Standard Citations Full Citation Abbreviated Citation USSR Central Statistical Administration, Statistical Handbooks � Narodnoye khozyaystvo SSSR v 19� godu (National Economy of the USSR in 19�) Sel'skoye khozyaystvo SSSR, 1960 (Agriculture USSR) Sel'skoye khozyaystvo SSSR, 1971 (Agriculture USSR) Narkhoz 19� Selkhoz 1960 Selkhoz 1971 Sovetskaya torgovlya, 1964 (Soviet Trade) Soy torg 1964 Gosudarstvennyy byudzhet SSSR i byudzhety soyuznykh respublik (State Budget of the USSR and Budgets of the Union Republics) 1961-65 1966-70 1971-75 Gosbyudzhet, 1966 Gosbyudzhet, 1972 Gosbyudzhet, 1976 Soviet Periodicals Voprosy ekonomiki (Problems of Economics) Vop ek Vestnik statistiki (Herald of Statistics) Vest stat Ekonomika I organizatsiya promyshlennogo proizvodstva (Economics and Organization of EKO Industrial Production) Ekonomicheskaya gazeta (Economic Gazette) US Government Publications Ekon gaz CIA, USSR: Gross National Product Accounts, 1970, A (ER) 75-76, November 1975 CIA, The Soviet Grain Balance, 1960-73, A (ER) 75-68, September 1975 CIA, A Comparison of Consumption in the USSR and the US, January 1964 CIA, GNP 1970 A (ER) 75-68 CIA, A Comparison�, 1964 Joint Economic Committee, Congress of the United States, An Index of Industrial Production in the USSR, 1982 An Index of Agricultural Production in the USSR, 1982 An Index of Consumption in the USSR, 1982 Consumption in the USSR: An International Comparison, 1981 Gross National Product of the USSR: An International Comparison, 1982 Soviet Economic Prospects for the Seventies, June 1973 Soviet Economy in a New Perspective, October 1976 Soviet Economy in a Time of Change, October 1979 JEC, Industry JEC, Agriculture JEC, Consumption JEC, Consumption Comparison JEC, GNP Comparison JEC, 1973 JEC, 1976 JEC, 1979 Other Publications Irving B. Kravis, Zoltan Kenessey, Alan Heston, and Robert Summers, A System of International Comparisons of Gross Product and Purchasing Power, United Nations International Comparisons Project, Phase I (Baltimore, The Johns Hopkins University Press, 1975) ICP, Phase I Irving B. Kravis, Alan Heston, and Robert Summers, International Comparisons of Real Product and Purchasing Power, United Nations International Comparisons Project, Phase H (Baltimore, The Johns Hopkins University Press, 1978) Abraham S. Becker, Soviet National Income, 1958-1964 (Berkeley, University of California Press, 1969) ICP, Phase II Becker, 1969 Abram Bergson, The Real National Income of Soviet Russia Since 1928 (Cambridge, Mass., Harvard University Press, 1961) Bergson, 1961 Abram Bergson, Productivity and the Social System: The USSR and the West (Cambridge, Mass., Harvard University Press, 1978) Bergson, 1978 Vladimir G. Treml and John P. Hardt, eds., Soviet Economic Statistics (Durham, N.C., Duke University Press, 1972) Treml and Hardt 10 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Gross National Product of the USSR, 1950-80 Introduction This paper presents estimates of the real growth of Soviet gross national product (GNP) since 1950 devel- oped by the Central Intelligence Agency and de- scribes the methodology used to construct those esti- mates. An earlier publication presented our estimates of Soviet GNP for a single base year, 1970, in both established and factor-cost prices.' This paper revises the 1970 GNP estimates based on information collect- ed since their publication and develops constant-price activity indexes to move each component of 1970 GNP over time.' The result is an estimate of the growth of Soviet GNP in 1970 prices since 1950. Our Estimates in Perspective The Soviet GNP data presented here supplement an already large body of research. The accounting struc- ture closely follows the one pioneered by Professor Abram Bergson and further developed by scholars at the Rand Corporation.' The result of their efforts is a set of Soviet GNP accounts for 1928, 1937, 1940, 1944, and 1948-66 in current rubles. Bergson also 'CIA, GNP 1970. 'Preliminary versions of the time-series data presented here were published in Herbert Block, "Soviet Economic Performance in a Global Context," JEC, 1979, vol. 1, pp. 135-140; and Rush V. Greenslade, "The Real Gross National Product of the U.S.S.R., 1950-1975," JEC, 1976, pp. 269-300. ' The principal publications, in order of the years for which the GNP accounts were constructed are: Oleg Hoeffding, Soviet National Income and Product in 1928, Columbia University Press, New York, 1954; Abram Bergson, Soviet National Income and Product in 1937, Columbia University Press, New York, 1953; Abram Bergson and Hans Heymann, Jr., Soviet National Income and Product, 1940-48, Columbia University Press, New York, 1954; Abram Bergson, Hans Heymann, Jr., and Oleg Hoeffding, Soviet National Income and Product, 1928-1948: Revised Data, Research Memorandum 2544, The Rand Corporation, Santa Moni- ca, Calif., 1960; Bergson, 1961; Oleg Hoeffding and Nancy Nimitz, Soviet National Income and Product, 1949-1955, Research Memo- randum 2101, The Rand Corporation, Santa Monica, Calif., 1959; Nancy Nimitz, Soviet National Income and Product, 1956-1958, Research Memorandum 3112-PR, The Rand Corporation, Santa Monica, Calif., 1962; Becker, 1969; and Sally Anderson, Soviet National Income, 1964-1966, in Established Prices, Research Memorandum 5705-PR, The Rand Corporation, Santa Monica, Calif., 1968. 11 devised the adjusted factor-cost standard (AFCS) in order to correct some of the distortions caused by the Soviet pricing system. He recalculated GNP using factor-cost prices, which are determined by imputing a uniform capital charge in place of profits, and eliminating the highly discriminatory turnover tax. In order to compute the real growth of Soviet GNP, Bergson developed price indexes to deflate the cur- rent-price values of each end-use component of GNP. Becker similarly computed the real growth of Soviet GNP from 1958 to 1964 in both 1958 and 1964 factor-cost prices.4 A number of other scholars have published estimates of Soviet GNP. TwO estimates for early years are by Baran and Seton.' The United Nations, Bornstein, and Cohn constructed GNP accounts for single years in the 1950s.6 More closely related to this study are calculations of the real growth of Soviet GNP for extended time periods by Moorsteen and Powell, Kaplan, and Cohn.' The latter three studies combine a ' Bergson, 1961, pt. 3; and Becker, 1969, ch. 6. 'Paul A. Baran, "National Income and Product of the USSR in 1940," Review of Economic Statistics 29, November 1947, pp. 226- 234; and Francis Seton, "The Social Accounts of the Soviet Union in 1934," Review of Economics and Statistics 36, August 1954, pp. 290-308. 6"An Estimate of the National Accounts of the Soviet Union for 1955," Economic Bulletin for Europe 9, United Nations, Economic Commission for Europe, May 1957, pp. 89-107; Morris Bornstein et al,, "Soviet National Accounts for 1955," Center for Russian Studies, The University of Michigan, 1961 (mimeographed); and Stanly Cohn, Derivation of 1959 Value-Added Weights for Origi- nating Sectors of Soviet Gross National Product, Technical Paper RAC-TP-210, The Research Analysis Corporation, McLean, Va., 1966. ' Richard Moorsteen and Raymond P. Powell, The Soviet Capital Stock, 1928-1962, app. P, Richard D. Irwin, Homewood, III., 1966; Norman Kaplan, The Record of Soviet Economic Growth, Re- search Memorandum 6169, The Rand Corporation, Santa Monica, Calif., 1969; and Stanly Cohn, "General Growth Performance of the Soviet Economy," Economic Performance and the Military Burden in the Soviet Union, US Congress, Joint Economic Com- mittee, Government Printing Office, Washington, D.C., 1970, pp. 9-17. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 distribution of Soviet GNP by sector of origin for a base year with constant-price activity indexes for each sector to estimate the real growth of Soviet GNP in the prices of the base year. The most recent study is by Lee, who constructed end-use accounts for 1955- 75.8 This paper combines the sector-of-origin and end-use approaches to estimating the real growth of Soviet GNP. First, the GNP accounts are constructed for 1970 in established prices following the Bergson model. Second, the income side of the GNP account is rearranged by sector of origin. Third, GNP by sector of origin is converted to factor-cost prices, and the factor-cost correction is carried over to GNP by end use via an estimated 1970 input-output table. Fourth, indexes in 1970 prices are constructed for each sector- of-origin and end-use component. Finally, the compo- nent indexes are combined using the 1970 weights in factor-cost prices to estimate the real growth of Soviet GNP both by sector of origin and end use. The results are intended to measure changes in both production potential and actual resource allocation over time. Soviet National Income Data The Central Statistical Administration of the Soviet Union compiles its own measure of aggregate econom- ic activity, usually labeled net material product (NMP) in the West.' The annual Soviet statistical handbook, Narkhoz 19�, provides data on total Soviet NMP, including five sector-of-origin and two end-use components. There are three principal reasons for compiling an independent index of Soviet econom- ic activity rather than accepting the Soviet measure: (1) there are important differences in coverage be- tween NMP and GNP, (2) we do not have sufficient knowledge of the methodological base of the NMP data, and (3) the Soviet data in purported constant prices are subject to major price distortions. 'W. T. Lee, "USSR Gross National Product in Established Prices, 1955-1975," Jahrbuch der Wirtschaft Osteuropas, vol. 8, 1979, pp. 399-429. e The actual Soviet term (natsionarniy dokhod) translates as "national income." Since the same term is used in Western GNP accounting for a different concept, the Soviet term is referred to as net material product; it measures the net value added in the production of material goods. The main difference between NMP and GNP is that NMP does not include the value added in the produc- tion of most services, or a capital consumption allow- ance.' To build an estimate of GNP from Soviet data, these two quantities, which represented about 25 percent of GNP in 1970, must be estimated in the desired detail. Historically, production of the exclud- ed services has grown more slowly than the other components of GNP and, therefore, this difference in coverage has imparted an upward bias to the growth of NMP. The omission of depreciation from NMP affects the growth rate if total depreciation grows more rapidly than the other elements of value added, or if the base- year distribution of depreciation among the sectors of origin differs markedly from the distribution of the remaining components of value added. The available data are not sufficient to infer the direction of the bias in the growth rate of NMP due to the omission of depreciation. The exclusion of depreciation does, of course, affect the absolute size of NMP. The Soviet Government regularly publishes annual data on total NMP produced in both current and constant prices, but the five sector-of-origin compo- nents are given only in current prices. Annual data are also published in current prices for "NMP used," disaggregated into two end uses�"consumption" and "accumulation and other outlays"; similar data in constant prices have been published only for recent five-year periods. Even if suitable deflators could be devised, the published sectoral disaggregations are far too few to support systematic analysis of structural changes in the economy or to provide adequate data for economic modeling. The problems in using the NMP data are complicated by gaps in our knowledge about the methodology used to compile the data. The Soviets have never published "See USSR: Toward a Reconciliation of Marxist and Western Measures of National Income, US Central Intelligence Agency, Washington, D.C., 1978, for a more detailed discussion of the differences between the GNP and NMP concepts. 12 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 a manual setting out their procedures in detail. The nearest thing to such a manual was prepared by the CEMA secretariat for publication by the United Nations." This document sets out only the general procedures and states that individual nations of CEMA frequently diverge from them. Various Soviet authors, including some known to hold important positions in the Central Statistical Administration, have published books on NMP. It is never clear, however, whether these books represent official state- ments or personal opinions. The lack of knowledge of Soviet NMP practices makes it difficult to know how to adjust NMP in order to reach GNP. The dividing line between NMP and GNP is not always clear, and the user of the NMP data is left to guess the correct interpretation.'2 The third principal reason for making independent GNP estimates is that Soviet data on the real growth of NMP and sectoral output involve considerable overstatement. Soviet NMP increased 57 percent in constant prices and 51 percent in current prices from 1970 to 1979, which implies deflation in the Soviet Union since 1970.'3 In contrast, most studies by Western scholars indicate that there is persistent inflation in the Soviet Union, both overt and re- pressed. For example, Cohn allocated the difference in the growth rates of Western estimates of Soviet GNP and Soviet NMP to differences in (1) coverage, (2) the weights assigned to each sector, and (3) sectoral growth rates. He found the latter to be the most important." The chief cause of the difference in sectoral growth rates in the postwar period is believed to be the Soviet method of accounting for the production of new industrial products. In constructing an output series in constant prices, a price must be imputed to products introduced after the base year. In theory, the Soviets " Basic Principles of the System of Balances of the National Economy, United Nations, New York, 1971. 12 See Abraham S. Becker, "National Income Accounting in the USSR," in Treml and Hardt, pp. 115-119, for a discussion of this problem. Narkhoz 1979, p. 405. Stanly H. Cohn, "National Income Growth Statistics," in Treml and Hardt, pp. 136-137. For a recent look at inflation in general see Alec Nove, Political Economy and Soviet Socialism, ch. 11, George Allen & Unwin, London, 1979. 13 assign each new product a price high enough to recover research, development, and introductory pro- duction costs. After these initial costs are recovered, the price of the new product is supposed to be lowered and a permanent price established. In practice, how- ever, pricing procedures are used by Soviet managers to inflate the growth of output in two ways. Often old products are altered slightly and declared to be new products with unjustifiably higher prices, and genu- inely new products are allowed to retain their intro- ductory price as a permanent price. In both cases, the unjustifiably high price is used by the Soviets as the base-year price needed for the constant-price output calculation. The impact of the new-product pricing problem will be greatest in those sectors with a high rate of innovation, primarily the machinery and chemicals branches of industry in the Soviet Union." The Plan of the Paper This paper is divided into two main parts. Part I presents and analyzes the results; detailed description of the construction of individual sector indexes is reserved for the appendixes. The first sections exam- ine the estimated growth rates for both total GNP and its principal components, the percentage distribution of GNP over time, major shifts in resource allocation, the growth of per capita consumption, and interna- tional comparisons of the growth and structure of the Soviet economy. The final sections of part I assess the accuracy and reliability of the results. Part II sets out the methodology used to construct base-year weights in factor-cost prices and the indexes of real economic activity. The methodology itself is presented in four sections: the accounting framework, the valuation problem, conversion of the 1970 GNP accounts from established prices to factor-cost prices, and the construction of constant-price activity index- es. The final section briefly describes the nature of the various end-use and sector-of-origin indexes. See Comparing Planned and Actual Growth of Industrial Output in Centrally Planned Economies, Central Intelligence Agency, Washington, D.C., 1980, p. 6; and Rush V. Greenslade, "Industrial Production Statistics in the USSR," in Treml and Hardt, pp. 181- 186, for discussions of the new-product price issue. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix A contains the detailed statistical results of this study. Appendixes B and C document the meth- odologies used to construct those individual sector-of- origin and end-use indexes not described elsewhere. Appendix D describes the revisions in the 1970 estab- lished-price accounts, and appendix E describes the methodology used to convert the 1970 established- price values to a factor-cost basis. 14 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part 1 Results and Analysis 16 Soviet Economic Growth in Perspective National economic accounts constructed for the Sovi- et Union along conventional Western lines confirm that the Soviet economy has experienced rapid growth since 1950. The output of the Soviet Union in 1980 was about four times the level in 1950 (figure 1), the result of an average annual growth rate of 4.7 percent. Changes in Soviet Growth Since 1950 The pace of advance over this 30-year period, howev- er, has not been steady. In fact, annual rates of growth have been characterized by both wide year-to- year swings and a pronounced downward trend (figure 2). Despite this volatility, an absolute fall in GNP from one year to the next�that is, a negative growth rate�has been extremely rare.'' The downward trend shows up clearly in average annual rates of GNP growth for each of the five-year plan periods between 1950 and 1980: Five-Year Period Average Annual Percentage Growth 1951-55 5.5 1956-60 5.9 1961-65 5.0 1966-70 5.2 1971-75 3.7 1976-80 2.7 These data suggest that the Soviet economy has been in a strong growth slide since the late 1960s, and that "All of the results presented here are in terms of 1970 factor-cost prices unless otherwise stated. Part II discusses the rationale for using these synthetic prices. The single occurrence is 1963 when an enormous reduction in the inventory of livestock following a disastrous harvest drove the growth rate down to �1.1 percent. This decline is probably exaggerated because the livestock index uses an average value per head and most of the animals which were slaughtered in 1963 were relatively low-valued young livestock. 15 Figure 1 Growth of Soviet GNP Index: 1970=100 140 120 100 80 60 40 20 lIIIIlIIIIIIIIItI11I_LIJIIjIILI 0 1950 55 60 65 f10 75 80 the average growth rate in the late 1970s was barely half the rate of 10 years earlier. 18 The wide year-to-year fluctuations in Soviet growth are due primarily to swings in agricultural production. Agriculture still represents a large part of the Soviet Conventional average annual rate-of-growth calculations are sub- ject to potential distortion if either of the end years is abnormal. Alternative calculations based on procedures developed by Boris Pesek, "Economic Growth and its Measurement," Economic Devel- opment and Cultural Change 9, April 1961, pp. 295-315 to reduce this source of distortion yield results which show only small differences in the rates of growth calculated above. The Pesek average annual growth rates for the five-year periods listed in the tabulation above are: 1951-55, 5.5; 1956-60, 5.8; 1961-65, 4.8; 1966-70, 5.1; 1971-75, 4.0; and 1976-80, 2.6 percent per year. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 2 Annual Soviet GNP Growth Rates. Percent 12 10 8 4 2 Annual growth rate Three-year moving average Figure 3 Growth Rates of Soviet GNP and Agriculture Percent 40 �20 I I 1 I I 1 1 I I I 1 I I .,I 1 1 I I I I 11J 1 1 ii I I I I I I I I I I I I I 1 I 1 I 1 I I 1 I I I I I I I I �2 1951 55 60 65 70 75 80 �30 1951 t4 60 65 70 75 80 economy-14 percent of GNP produced in 1980 (measured in 1970 prices). As a result of geoclimatic limitations and cropping practices, Soviet agricultural output is subject to large variations.� It is not at all unusual for agricultural output to fall from one year to the next, but such declines usually have been followed by a return to more normal weather and therefore a more normal level of output from agricul- ture in the following years. The recovery shows up as a very high growth rate of GNP in the year after a shortfall in agriculture, producing a distinct saw-tooth pattern to annual growth rates in GNP (figure 3). While agriculture is the major source of sharp annual swings in GNP growth, industry, with its large weight in total GNP (37 percent in 1980 in 1970 prices), appears to be the major source of the secular decline '9 Year-to-year variation in Soviet agricultural output is three times greater than in the United States. See Douglas B. Diamond and W. Lee Davis, "Comparative Growth in Output and Productivity in U.S. and U.S.S.R. Agriculture," JEC, 1979, vol. 2, p. 20. in growth. Industrial growth, although generally ex- ceeding that of GNP, has slowed from the 8- to 12- percent-per-year range in the 1950s to the 3- to 4- percent-per-year range in the late 1970s (figure 4). The Evolving Structure of the Soviet Economy The structure of the Soviet economy has changed dramatically since 1950 (figure 5).20 By far the most important change has been the decline in the share of GNP produced in agriculture and the steady increase in the share produced in industry. Other notable trends are the growing importance of transportation and�surprisingly�the declining relative importance of the service sector. " The percentage shares of GNP are calculated in 1970 factor-cost prices. A more accurate portrayal of changes in the structure of GNP would be obtained by computing the shares in current factor- cost prices. Unfortunately, those data are not currently available. 16 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 4 Growth Rates of Soviet GNP and Industry Percent 12 10 6 Ii! 1 1 1 1 I �2 1951 55 I 1 1 1 1 11,1 1 I 1 J I 1 1 I 1 1 1 1 I Figure 5 Distribution of Soviet GNP by Sector of Origin Percent 60 66 65 70 75 80 1950 As a result of the Soviet Union's long-term policy of emphasizing industrial development, the share of GNP created in industry has increased steadily from 20 percent in 1950 to 37 percent in 1980. The rate of growth of industry's share of GNP has been slowing, however, and has changed little in the late 1970s. Among the branches of industry, the machinery and chemicals branches have had the highest growth rates. The machinery share of GNP has risen from 6 percent in 1950 to 14 percent in 1980, while the chemicals share has risen from 1 to 3 percent of GNP.' Agriculture's share of GNP has dropped from 31 percent in 1950 to 14 percent in 1980. As discussed above, fluctuation in the index of agricultural produc- tion is the dominant cause of fluctuation in the growth rate of GNP. Since the relative importance of agricul- ture in the Soviet economy probably will continue to 2 See JEC, Industry, for an analysis of the development of Soviet industry. 17 55 60 65 70 75 80 decrease, the repercussions of its future fluctuations on GNP growth should diminish. The demand for transportation, communications, and trade services is derived for the most part from the growth of industry and construction. Consequently, the share of these three sectors in GNP has grown significantly: Percentage Share of GNP 1950 1960 1970 1980 Transportation 3.9 6.8 8.7 10.3 Communications 0.6 0.7 0.9 1.2 Trade 5.0 6.8 , 7.3 7.7 In particular, the increase in the share of GNP produced in the transportation sector can be attribut- ed to the increasing size of the industrial sector, which relies on transportation to move raw materials and Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 products; the increasing specialization within indus- try, which leads to more transportation of semiproc- essed materials; and the shifting of industrial produc- tion toward Siberia, which leads to longer shipping distances to reach the European population centers. Within the transport sector itself, the share of rail transport has been steadily falling: rail freight trans- port accounted for 86 percent of total freight revenue in 1950 in the sample used in this study to estimate the contribution of this sector to GNP and only 47 percent in 1980, as air and truck freight transport expanded rapidly from minuscule levels. The share of GNP produced in the service sector has declined from 29 percent in 1950 to 20 percent in 1970." This decline has been shared by almost all of the individual services; only science has shown any appreciable growth as a share of GNP, rising from 1.1 percent of GNP in 1950 to 2.3 percent in 1980. The decreasing share of GNP produced in the service sector is contrary to the experience of most developing nations. Normally an increase in the income level of a nation leads to above-average growth in the demand for services. The below-average growth of services in the USSR suggests a deliberate policy to restrain the development of services. Changing Patterns of Output Use Accompanying the shifts in the producing structure of the Soviet economy has been a changing pattern of output use since 1950. The dominant trend is the increasing share of GNP which is allocated to invest- ment at the expense of most other use categories. Measured in 1970 prices, expenditures on investment have climbed from 14 percent of GNP in 1950 to 33 percent in 1980 (figure 6). The growth of investment reflects partially the traditional Soviet emphasis on growth through rapid increases in capital stock. Moreover, there has been a pronounced change in the structure of investment. The share of expenditures for the sum of producer durables and new construction allocated to producer durables alone has risen from 22 percent in 1950 to 39 percent in 1980." This shift " The service sector includes housing, utilities, repair and personal care, recreation, education, health, science, credit and insurance, and government administrative services. " Table A-6. This change in the structure of Soviet investment is analyzed by Boris Rumor, The Dynamics of the Capital Coefficient of USSR Industrial Output: Investment Process in Soviet Industry, National Council for Soviet and East European Research, 1981. Figure 6 Distribution of Soviet GNP by End Use Percent 100 80 60 40 20 0 1950 Other goy amen expe4lturei I I 1 I 1 ?.1 I 1 1 I 1 I I 55 60 65 70 75 80 reflects the increasing emphasis toward reequipping and modernizing existing production sites rather than creating entirely new facilities. The growth rate for investment has slowed sharply, however, from 11.5 percent per year for the 1950s to an average of 5.8 percent per year since 1960. The direct consequence of slower investment growth is a smaller contribution to GNP growth through a larger capital stock. Defense is a major claimant on Soviet resources. Although no data are presented here on total defense expenditures, it is believed that total defense expendi- tures amounted to 11 to 13 percent of GNP in 1970 and have increased at an average annual rate of 4 to 5 percent per year since 1965." Since this rate is somewhat above the growth in GNP during that period, the share of GNP allocated to defense has "` Allocation of Resources in the Soviet Union-1980, US Con- gress, Joint Economic Committee, Government Printing Office, Washington, D.C., 1981, p. 124. 18 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 increased slightly since 1965. Total defense expendi- tures are not presented as a separate end-use category because we believe that some defense expenditures are contained in several other components of GNP. In- vestment probably includes the procurement of com- mon use durables, such as trucks and transport air- craft, and the construction of military facilities. Science probably is very heavily weighted toward defense expenditures. Other defense expenditures could well be contained in administration, education, and health expenditures. Because of many uncertain- ties, no estimate is made here of the values of defense expenditures included in the other end-use categories. Estimates of total defense expenditures have been made by the CIA independent of the GNP accounts. These data are presented for reference in appendix C. Consumption has declined as a share of GNP from 60 percent in 1950 to 54 percent in 1980. Consumption consists of two principal components, goods and serv- ices, which have shown similar growth rates. The consumption of goods has grown at an annual rate of 4.3 percent per year since 1950, and services at 4.2 percent compared with 4.7 percent for GNP. As a result, the consumer goods share of GNP has declined from 38 percent in 1950 to 34 percent in 1980, while the consumer services share has declined from 22 to 20 percent. Within consumption, there have been sizable structural changes. The consumption of food has declined sharply as a share of GNP, from 32 percent in 1950 to 23 percent in 1980, while the consumption of soft goods and durables has risen as a share of GNP from 6 percent in 1950 to 11 percent in 1980. Trends in per capita consumption are more useful indicators of the impact on living standards of re- sources allocated to consumption than are trends in total consumption. Measured at factor cost, Soviet per capita consumption has grown at an average annual rate of 2.9 percent since 1950, but only 2.2 percent since 1970�reflecting both the overall slowdown in GNP growth and the falling share of consumption in GNP. Soviet Growth in International Perspective Without doubt the Soviet economy has achieved rapid growth since 1950. This performance, however, can best be interpreted and understood when compared 19 with growth trends in other countries during the same period. These trends can be measured in terms of GNP growth, priorities in output use, and growth in per capita consumption. Comparisons of GNP Growth. Table 1 compares the average annual rates of growth of GNP for the Soviet Union and of gross domestic product (GDP) for selected OECD countries." For the entire 1951-79 period, the figure for the Soviet Union is roughly in the middle of the OECD range. Japan, West Germa- ny, Spain, and Turkey clearly achieved faster growth than the Soviet Union, and several other nations achieved rates close to the Soviet figure. In compari- son with the United States, the Soviet Union consis- tently enjoyed a higher growth rate until the late 1970s. The average annual growth rate of Soviet GNP is a full percentage point higher than that of the United States for the entire 1951-79 period. Since 1970, however, the growth rate of Soviet GNP has declined steadily, while the US growth rate has continued at roughly an unchanged tempo. As a result, the US and Soviet economies grew by almost the same average rates in the 1970s. Priorities in Output Use. Another way of comparing the performance of the Soviet and OECD economies is to examine the patterns of output use. Table 2 shows the percentage distribution of the GDP of several OECD countries and of the GNP of the Soviet Union among consumption, investment, and all other expenditures. The data for the Soviet Union are not strictly comparable with those for the OECD coun- tries because Soviet Government expenditures for health, education, and physical culture are included in consumption. These expenditures were equal to 5.5 percent of Soviet GNP in 1970 and serve to inflate Soviet consumption data relative to the OECD data." The share of Soviet GNP allocated to investment, measured in 1970 prices, has steadily increased� from 14 percent in 1950 to 32 percent in 1979�while " The difference between GNP and GDP for the Soviet Union is negligible and can be ignored for these comparisons. JEC, Consumption Comparison, makes careful adjustments for these definitional differences and obtains similar changes in the consumption shares to those shown in table 2. The absolute levels of the adjusted consumption shares, as expected, are higher. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 1 Percent Average Annual Rate of Growth of National Product for Selected OECD Countries (GDP) and for the USSR (GNP) 1951-55 a 1956-60 1961-65 1966-70 1971-75 1976-79 195179a Total OECD NA NA 5.2 4.8 3.1 4.0 NA Of which Canada 5.2 4.0 5.7 4.8 5.0 3.7 4.8 United States 4.2 2.3 4.6 3.1 2.3 4.4 3.4 Japan 7.2 8.6 10.0 12.2 5.0 5.9 8.3 Australia 3.8 4.0 4.8 6.0 3.5 2.4 4.2 New Zealand 3.8 4.0 4.9 2.7 4.0 0.3 3.3 Finland 5.0 4.1 4.8 4.8 3.9 2.5 4.2 France 3.7 5.0 5.8 5.4 4.0 3.7 4.6 West Germany 9.2 6.5 5.0 4.4 2.1 4.0 5.1 Italy 5.6 5.5 5.2 6.2 2.4 3.8 4.8 Netherlands 5.9 4.0 4.8 5.5 3.2 3.1 4.4 Norway 3.8 3.3 4.8 3.7 4.6 4.2 4.1 Spain 5.2 3.2 8.5 6.2 5.5 2.5 5.3 Sweden 3.4 3.4 5.2 3.9 2.7 1.1 3.4 Switzerland 4.9 4.3 5.2 4.2 0.8 0.9 3.5 Turkey 8.1 4.6 4.8 6.6 7.5 4.1 6.0 United Kingdom 3.9 2.6 3.1 2.5 2.0 2.4 2.7 USSR 5.5 5.9 5.0 5.2 3.7 3.0 4.8 Data in column I for Japan and the United Kingdom are for 1953- 55; for Finland, France, West Germany, Italy, and the Nether- lands-1952-55; and for New Zealand and Spain-1955 only. The corresponding data in column 7 are for 1953-79, 1952-79, and 1955- 79, respectively. NA = not available. Sources: OECD data are from National Accounts &OECD Countries, OECD, Paris, 1981, except for the value for total OECD for 1961-65. The latter value is from the 1980 edition of the same publication. USSR data are from table A-5. 20 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 2 Percentage Distribution of National Product by End Use in Selected OECD Countries (GDP) and in the USSR (GNP) Expenditures Consumption Investment All Other 1950 1960 1970 1979 1950 1960 1970 1979 1950 1960 1970 1979 Total OECD NA 60.1 59.3 61.0 NA 20.2 22.8 21.2 NA 19.7 17.9 17.8 Of which Canada 55.2 57.5 53.3 57.0 21.1 22.5 21.7 22.2 23.7 20.0 25.0 20.8 United States 62.1 60.9 62.2 64.6 19.5 18.2 18.4 17.4 18.4 20.9 19.4 18.0 Japan 63.2 a 63.2 54.4 55.4 15.1 a 23.1 34.9 33.2 21.7 . 13.7 10.7 11.4 Australia 67.5 61.5 57.7 59.3 24.4 24.6 26.5 21.2 8.1 13.9 15.8 19.5 New Zealand NA 68.2 59.9 62.4 NA NA NA NA NA NA NA NA Finland 52.8 b 54.4 55.1 54.1 25.5 b 30.1 28.6 23.2 21.7 b 15.5 16.3 22.7 France 60.0 b 60.3 59.1 62.6 17.3 b 19.3 23.8 21.5 22.7 b 20.4 17.1 15.9 West Germany 52.5 b 52.0 53.3 54.7 20.1 b 24.0 24.1 22.2 27.4 b 24.0 22.6 23.1 Italy 66.1 b 59.4 63.6 62.4 15.6 b 26.0 24.4 18.9 18.3 b 14.6 12.0 18.7 Netherlands 56.9 b 51.8 57.4 59.8 18.6 b 21.6 25.3 20.8 24.5 b 26.6 17.3 19.4 Norway 61.1 57.9 54.1 48.6 27.3 26.3 28.2 26.3 11.6 15.8 17.7 25.1 Spain 72.9 c 69.9 67.4 68.8 15.6 c 16.7 23.1 20.0 11.5 c 13.4 9.5 11.2 Sweden 62.3 56.8 52.3 52.5 16.7 20.6 21.6 19.0 21.0 22.6 26.1 28.5 Switzerland 67.4 58.7 58.4 63.9 16.2 23.7 25.5 23.6 16.4 17.6 16.1 12.5 Turkey 77.3 79.7 73.9 72.9 16.8 15.5 19.4 16.6 5.9 4.8 6.7 10.5 United Kingdom 62.6 a 63.7 61.0 61.4 12.7 a 16.7 20.7 17.9 24.7 a 18.6 18.3 20.7 USSR 59.9 57.7 54.2 53.2 14.2 24.2 28.2 32.5 25.8 18.1 17.6 14.3 a The data are for 1952. b The data are for 1951. c The data are for 1954. NA = not available. Sources: OECD data are from National Acounts of OECD Countries, OECD, Paris, 1981, except for the value for total OECD for 1960. The latter value is from the 1980 edition of the same publication. The USSR data are from table A-11. All percentages, except for total OECD, are calculated using data expressed in domestic currencies in constant prices. The total OECD data are calculated using data expressed in 1975 US dollars. 21 93-892 0 - 82 - 3 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 3 Percent Average Annual Rate of Growth of Per Capita Consumption in Selected OECD Countries and the USSR 195155a 1956-60 1961-65 1966-70 1971-75 1976-79 1951-79 a Total OECD NA NA 3.7 3.7 2.8 3.1 NA Of which Canada 2.5 2.1 2.6 2.7 5.2 2.4 2.9 United States 1.5 1.0 2.8 2.7 2.0 3.4 2.2 Japan 7.0 6.8 7.9 8.6 4.8 3.9 6.6 Australia 0.4 0.9 2.5 2.9 2.5 1.1 1.7 New Zealand NA NA 1.5 0 1.2 0.1 0.7 Finland 3.7 2.0 5.0 4.1 3.6 1.5 3.4 France 3.7 3.2 4.5 4.0 . 4.1 3.6 3.9 West Germany 8.1 5.5 4.1 4.0 2.6 3.7 4.6 Italy 3.9 4.1 5.3 6.1 1.8 2.6 4.0 Netherlands 3.4 2.3 4.9 4.9 2.3 3.3 3.5 Norway 1.8 2.2 2.6 2.9 3.2 1.9 2.5 Spain 4.6 1.5 7.3 4.8 4.8 1.6 4.1 Sweden 1.8 1.8 3.6 2.3 2.3 0.9 2.2 Switzerland 1.4 2.3 3.1 3.0 1.4 2.1 2.2 Turkey 5.4 1.9 1.8 3.0 4.5 1.7 3.1 United Kingdom 3.9 2.2 2.0 1.6 2.0 2.4 2.2 USSR 3.1 3.8 2.1 4.3 2.6 1.7 3.0 a Data in column 1 for Japan and the United Kingdom are for 1953- 55; for Finland, France, West Germany, Italy, and the Nether- lands-1952-55; and for Spain-1955 only. The corresponding data in column 7 are for 1953-79, 1952-79, and 1955-79, respectively. The value in column 7 for New Zealand is for 1961-79. NA = not available. Sources: See sources to table 1 for the OECD consumption data. The USSR consumption data are from table A-9. The population data for all countries are from World Population 1979, US Bureau of the Census, Government Printing Office, Washington, D.C., 1980, and Demographic Estimates for Countries With a Population of 10 Million or More: 1981, US Bureau of the Census, Government Printing Office, Washington, D.C., 1981, and World Population 1977, US Bureau of the Census, Government Printing Office, Washington, D.C., 1978. 22 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 the share allocated to consumption has decreased by 7 percentage points. The only other country to have a similar change in output-use patterns is Japan, where investment has risen from 15 to 33 percent of GDP, while private consumption has fallen from 63 to 55 percent. Most of the other OECD countries show either stable patterns of distribution or shifts from private consumption to other (mostly government) expenditures. Growth in Per Capita Consumption. Table 3 com- pares the average annual growth rates of per capita consumption for selected OECD countries and the USSR. There is considerable variance among coun- tries and time periods. The USSR compares quite favorably with most OECD countries but lags well behind Japan and West Germany. Declining Soviet growth shows up clearly in the Soviet data, with the growth rate of per capita consumption falling to 1.7 percent per year in 1976-79. How Reliable Are the Synthetic Measures of Soviet Growth? The data used above to describe and interpret Soviet economic growth since 1950 are based on convention- al Western national income concepts. While they rely on published official Soviet data, they reflect numer- ous judgments about both the meaning of Soviet data and the best procedures for constructing the Western- style accounts. The reliability and sensitivity of the synthetic GNP data can be examined in terms of the: (1) sensitivity of the growth rate of GNP to the base year used, (2) patterns in the residual component of the accounts, (3) comparison with official Soviet NMP data, and (4) comparison with other Western esti- mates of Soviet GNP. Sensitivity to the Base Year Used When the prices of one year are used to measure growth over a 30-year span, growth rates in years far from the base year can be distorted because of changes in intersectoral price relationships." As a check on the severity of this problem, current-price " Bergson concludes that the long-term decline of the Soviet GNP growth rate is understated on this account. See Abram Bergson, "Conclusions," The USSR in the 1980s, NATO-Directorate of Economic Affairs, NATO, Brussels, 1978, pp. 231-242. 23 Table 4 Percentage Distribution of 1960 and 1976 Soviet GNP by Sector of Origin in Current and 1970 Established Prices 1960 1976 Sector 1960 Prices 1970 Prices 1970 Prices 1976 Prices Industry 47.2 42.1 47.9 48.9 Construction 7.1 7.3 8.0 7.9 Agriculture 17.5 25.1 16.8 16.1 Transportation 7.2 5.8 7.9 8.4 Communications 0.6 0.5 0.8 0.8 Trade 4.6 4.5 5.0 4.9 Services 13.0 12.0 11.5 11.1 Other 2.8 2.6 1.9 1.9 Sources: The data in 1970 prices are derived by using the indexes in table A-5 and the established-price weights in table D-7. The methodology is described in appendix A. See footnote 28 for the data in 1960 and 1976 prices. GNP accounts for the USSR were constructed for 1960 and 1976." The distribution of GNP by sector of origin in 1960 and 1976 in current and 1970 estab- lished prices is compared in table 4." In 1960 the primary difference is that agriculture has a lower weight in 1960 prices than in 1970 prices, a result which reflects the fact that price increases for agricul- tural output between 1960 and 1970 were greater than those for other sectors. The rates of growth of GNP obtained by using 1960, 1970, and 1976 as a base year are compared in the following tabulation: Average Annual Percent Growth of GNP Period 1960 Prices 1970 Prices 1976 Prices 1951-60 6.6 6.2 6.1 1961-70 5.5 5.3 5.2 1971-80 3.4 3.2 3.1 " These accounts are not included in this report, but were constructed using the same methodology as described in this report for 1970. Because of the problems inherent in using Soviet-established prices for measuring the growth of GNP (discussed in part II) a more informative comparison would be in factor-cost prices. At this time, however, data for 1960 and 1976 in current factor-cost prices are not available. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The data clearly show that Soviet GNP grows more rapidly when measured in 1960 prices than in 1970 prices, but that the differences are not large. The use of 1976 prices appears to make little difference in the growth rate of GNP compared to 1970 prices." Patterns in the GNP Residual In the 1970 GNP accounts for the Soviet Union, certain expenditures cannot be identified explicitly. These outlays not elsewhere classified (n.e.c.) com- prise a residual component within the base-year ac- counts. Conceptually, this category includes defense expenditures n.e.c., changes in strategic reserves, oth- er unidentified expenditures, and a statistical discrep- ancy. In addition, we have not been able to calculate constant-price indexes of inventory change or net exports; therefore, both of these quantities are also conceptually part of the outlays n.e.c. component in the time-series data. Outlays n.e.c. is calculated as a residual. Total GNP is derived from the sector-of- origin data. Then the sum of identified end-use components is subtracted from total GNP. The result- ing value is outlays n.e.c. Since total GNP should be the same regardless of whether it is calculated as the sum of the sector-of- origin or of the end-use components, the reliability of our GNP estimates can be assessed by examining the level and the trend in the residual component. The level of outlays n.e.c. should be well above zero. Although inventory change and net exports can be negative, the other elements of outlays n.e.c. (mainly some defense expenditures) should be sufficiently large to ensure that total outlays n.e.c. is positive. The reasonableness of the trend in the residual can be checked by using some additional data and making some strong assumptions about defense expenditures. Data are available on a large share of inventory change in current prices, but a suitable deflator is not. The fluctuations in this component of outlays n.e.c., however, generally should be in the same direction in both constant and current prices. " This comparison may understate somewhat the sensitivity to the base year used because the same activity indexes were used with all three sets of weights. If the indexes were recalculated using 1960 or 1976 prices to combine their various subindexes, then the difference in the average GNP growth rate probably would be increased slightly. The Soviet foreign trade statistical handbook, Vnesh- nyaya torgovlya SSSR v 19�godu, now publishes volume indexes of exports and imports. For the pur- pose of this exercise, we can assume that these indexes are accurate reflections of exports and imports in 1970 prices. Although total defense expenditures are estimated to have grown at 4 to 5 percent per year since 1965,3' the portion included in outlays n.e.c. may have increased at a quite different rate. Nevertheless, for the purpose of this exercise, it is assumed that all of the unidenti- fied expenditures in the base-year accounts are de- fense expenditures and that they have increased at a rate of 4.5 percent per year since 1965. The sum of inventory change in current prices and net exports and partial defense expenditures in constant prices provides a synthetic measure of outlays n.e.c. which should indicate whether the actual trend in outlays n.e.c. is plausible. The ruble values of the synthetic measure and the actual outlays n.e.c. com- ponent of end-use GNP are compared in figure 7. The year-to-year changes in the synthetic measure usually are in the same direction as changes in outlays n.e.c. until 1978; therefore, outlays n.e.c. appears to be a reasonable reflection of those expenditures that can- not be explicitly identified. The synthetic measure shows an upward trend while outlays n.e.c. shows little change prior to 1978. The difference in the trends can be interpreted as an indication of the existence of inflation. The imprecision in all of the data underlying this comparison, however, precludes any inference about the actual rate of inflation. After 1978, outlays n.e.c. decrease rapidly and be- come implausibly low to represent a large portion of defense expenditures plus inventory change and net exports. The cause of this decline is not known. Arithmetically, it could result from an underestimate of the growth of GNP or an overestimate of the growth of the other end-use components. See footnote 24. 24 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 7 The Outlays n.e.c. Residual and a Synthetic Measure Billion Rubles Figure 8 Annual Growth Rates of Soviet Adjusted GNP and Net Material Product Percent 60 Synthetic measure 50 40 30 20 10 0 1965 70 75 Outlays n.e.c. 14 12 10 2 Net matetial product Adjusted GNP 80 �4 .1951 55 60 65 70 75 79 Comparisons With Official Soviet Data Another assessment of the reliability of our GNP accounts can be made by comparing the official Soviet NMP data in constant prices with a synthetic measure of NMP derived from the GNP accounts. NMP measures the value added (less depreciation) in industry, construction, agriculture, freight transporta- tion, business communications, trade, and "other branches" of material production. The synthetic measure of NMP constructed here consists of the entire value added in industry, construction, agricul- ture, trade, general agricultural programs, and forest- ry, and part of the value added of transportation and communications. Figure 8 compares the annual growth rates of NMP in constant prices and the synthetic measure derived from our GNP data. Average annual growth rates by 25 five-year periods are shown in the following tabulation: Five-Year Period Average Annual Percent Growth Adjusted GNP Net Material Product 1951-55 7.6 11.1 1956-60 7.1 9.1 1961-65 5.1 6.5 1966-70 5.6 7.7 1971-75 3.7 5.7 1976-80 2.6 4.2 The results show that the synthetic measure grows more slowly than NMP but that the pattern of annual fluctuations is quite close to that of the Soviet meas- ure in constant prices. This result suggests that the' Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 fluctuations in Soviet GNP are captured fairly accu- rately in our data. The continued close relationship of both measures after 1978 suggests that our estimates of the growth rate of total GNP are accurate, and that the apparent underestimate of outlays n.e.c. after 1978 noted above results from an overestimate of other end-use components. Comparisons With Other Western Estimates A number of other estimates of Soviet GNP have been compiled by Western scholars, although none is as comprehensive or recent as those presented here. Most of these estimates concern the 1950s or early 1960s. The tabulation below compares the average annual rate of growth of total GNP derived in these other Western studies with the corresponding value derived in this study: " Period Other Western Studies of Soviet GNP Average Annual Rate of Growth Derived in This Author Average Annual Study (Percent) Rate of Growth (Percent) 1951-55 Bergson 7.6 5.5 1951-61 Moorsteen and Powell 7.4 5.7 1951-65 Kaplan 6.3 5.5 1951-69 Cohn 5.5 5.3 1956-75 Lee 7.7 5.0 1959-64 Becker 5.8 4.8 It is readily apparent that in each case the growth rate derived in this study is lower, and in some cases the difference is considerable. The studies by Bergson, Becker, and Lee estimate the growth of GNP as the sum of end-use expenditures. About 60 percent of the " Bergson, 1961, p. 149; Moorsteen and Powell, Soviet Capital Stock, pp. 623-624; Kaplan, Soviet Economic Growth, p. 14; Cohn, "Growth of the Soviet Economy," p. 17; W. T. Lee, "USSR Gross National Product," p. 413; and Becker, 1969, p. 128. difference between the growth rates computed by Becker and in this study arises from the lower growth rate of consumption derived here (4.7 versus 3.5 percent per year). This difference in turn results largely from Becker's use of Soviet price indexes to deflate the retail sales data as opposed to the use of physical quantity consumption and production data in this study. Similarly, most of the difference between Bergson's estimate and the one obtained here is the much lower growth rate of consumption derived in this study. Again, Bergson uses Soviet price indexes to deflate the retail sales component of consumption. Lee's data are essentially in current prices and this undoubtedly accounts for most of the difference be- tween his results and those obtained here. The studies by Moorsteen and Powell, Kaplan, and Cohn all use a set of base-year, sector-of-origin weights and a set of corresponding production indexes in order to estimate the growth rate of GNP. The growth rate obtained here is lower than that of Moorsteen and Powell primarily because of different weights. The 1950 implicit weights for industry (a high-growth sector) in this study are lower and the weights for agriculture and housing (low-growth sec- tors) are higher. The Kaplan growth rate is higher mainly because industry is assigned a higher weight and the average growth rate of industry is a full percentage point higher. The Cohn growth rate is nearly the same as the one obtained here. 26 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part II Methodology The estimation of Soviet GNP and its change over time presents several thorny methodological problems. This part first summarizes the major issues in formu- lating an accounting structure and devising a set of synthetic prices that will be in accord with the Western theoretical model of national income valua- tion and growth measurement. A discussion of the construction of our 1970 base-year accounts using Soviet official prices and their conversion to our synthetic prices follows. Having described the base-year accounts, the discus- sion then shifts to the methodological problems in- volved in measuring the growth of Soviet GNP over time. The central problem is how to measure the real growth of a diverse collection of goods and services when the relative prices and quantities are shifting. Index number theory tells us that there is no single answer to this question. A summary of the problem is provided here with additional discussion. of a few specific problems that are particularly serious in the Soviet case. Finally, all of the indexes used to measure the growth of the various components of GNP by sector of origin and end use and their underlying methodologies are described. The Accounting Framework The accounts used to compute GNP are partially determined by the institutional structure of the coun- try involved. This section first describes the account- ing units that comprise the Soviet economy and then describes the main financial flows involving these units. Next a number of definitional problems are considered and the resulting differences between the US GNP accounts and those constructed here for the Soviet Union are discussed. The Accounting Units There are four important types of accounting units in the USSR. The first two are khozraschet enterprises and so-called budget institutions, both of which are 27 state organizations. The other two are the collective farm (kolkhoz), which is part state and part coopera- tive, and the private household. Khozraschet Enterprises. A khozraschet enterprise is a state organization that operates on a profit-and loss- basis. It sells its output, uses the proceeds to purchase its inputs, and thereby obtains a profit or loss. The enterprise, however, must regulate production in con- formity with the highly detailed state economic plan and is in other ways directly administered by the government. Although it differs operationally from a private corporation in the United States, a khozras- chet enterprise, when viewed from a GNP accounting standpoint, is similar to and treated much like a private corporation. It is similar in that the financial relations between a khozraschet enterprise and the state are conducted on a net rather than a gross basis. The enterprise is expected to be managed sufficiently well to obtain enough profits to finance certain activi- ties, and the amount of government revenues obtained from the enterprise depends on its performance." An enterprise's profit is disposed of according to administrative rules. Most profits go to the state budget, much like an income tax in the United States. In 1970, for example, 59 percent of the profits of khozraschet enterprises were turned over to the bud- get. The government takes such a large share of the profits because it is directly involved in the capital transactions of khozraschet enterprises, contrary to the situation in a private US corporation. Most capital investment is paid for by allocations from the state budget. Retained profits of enterprises are used not only for capital investment, but also for a variety of " It should not be forgotten that a khozraschet enterprise is a state organization. All of its capital stock is state owned and can be taken away without compensation, just as the profits derived from the operation of the state-owned assets also can be taken away. The director of an enterprise is appointed by the state and is charged with fulfillment in the most economical manner of the production plan assigned to the enterprise. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 managerial incentives, employee welfare, and other purposes. Indeed, some of the incentive funds are considered to be labor payments in GNP accounting rather than profits. Although khozraschet enterprises normally are ex- pected to be profitable, many cannot be so under existing prices. For example, many meat and milk processing enterprises must be subsidized heavily because the government has repeatedly raised pro- curement prices for many agricultural products while holding their retail prices constantm Budget Institutions. A budget institution receives the funds necessary for its current operations from the state budget and returns any receipts accruing from its operations to the budget. Budget institutions tend to be organizations conducting government adminis- trative operations or providing services to the popula- tion at little or no direct charge. Government adminis- tration is carried out by organizations such as the State Planning Committee (Gosplan), the Central Statistical Administration, the Ministry of Defense, and municipal government organizations. Organiza- tions producing consumer services include the health and education ministries, which collect only modest fees, and the municipal service organizations, some of which are expected to collect sufficient fees to offset most of their current expenses. In general, the accounts of budget institutions are less detailed than those of khozraschet enterprises. In particular, depreciation allowances are not charged as a current expense. The Narkhoz, therefore, does not include depreciation of the capital stock of budget institutions in its depreciation data. Budget institutions play a large role in the Soviet economy. According to Soviet capital stock data, budget institutions possessed capital valued at 102.4 billion rubles on 1 January 1973, 10 percent of the total. It is likely that 20 to 25 percent of the labor force is employed in budget institutions, although exact data are not available. The borderline between " See Vladimir G. Treml, Agricultural Subsidies in the Soviet Union, US Department of Commerce, Bureau of the Census, Foreign Economic Report No. 15, Washington, D.C., 1978, for estimates of the size, growth, and distribution of this subsidy. budget and khozraschet enterprises has been a shift- ing one, but there has been a long-run tendency to increase the sphere of khozraschet enterprises in order to achieve greater control and efficiency. Collective Farms. In the USSR the collective farm, or kolkhoz, is part state and part cooperative. The land is state owned but given rent free to the kolkhoz. Members of the collective supposedly elect the direc- tor, and the net proceeds from farm activities are distributed to the members. In fact, the kolkhoz is now very similar to a state farm, or sovkhoz. The director is for all practical purposes appointed by the state, the state assigns a production and procurement plan, and the kolkhoz member is now guaranteed payment for his labor under a wage system like that of state farms. For accounting purposes, however, kolkhozy present several problems. Financial data in the Narkhoz and other sources tend to report only on state organiza- tions, omitting kolkhoz statistics. Kolkhoz accounts, therefore, have to be compiled from scattered sources. For example, earnings are retained and used for investment but are not included in Soviet data on profits. In addition, kolkhozy perform a considerable amount of industrial and construction work that is difficult to quantify. As a result, our estimate of agricultural value added is probably overstated somewhat. Private Households. The final accounting unit in the reconstructed GNP accounts for the Soviet Union is the private household. Private citizens carry out pro- duction, consumption, and investment activities. Their production is centered in agriculture, housing, and other services. In agriculture, production from private plots is sold and consumed in kind. Households con- tribute to the construction component of GNP by sector of origin through private housing construction, and they provide numerous services, including repair and personal care, education, health, recreation, and housing repair services. The operation of owner- occupied housing is included in the housing sector. 28 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The Main Financial Flows The nature of the accounting units determines the main financial flows used in the GNP accounts. For each type of unit incomes and outlays can be listed. The output of a khozraschet enterprise is sold to other enterprises for use in current production or is allocat- ed to one of the end uses: private consumption, investment, government consumption, or exports. A khozraschet enterprise buys goods and services for its own production needs and spends some of the funds at its disposal on wages, social insurance contributions, depreciation, and taxes. Sales less expenses equal profits and other net income. These financial flows are listed below: Khozraschet Enterprise Income and Outlay Account Outlays Incomes 1.1 Goods and services 1.2 Wages 1.3 Social insurance 1.4 Depreciation 1.5 Indirect taxes 1.6 Retained profits 1.7 Profits paid to the state budget 1.8 Special charges for education, research and development, and other 1.9 Miscellaneous charges 1.10 Subsidies received (negative value) 1.11 Sales to other enterprises on current account 1.12 Sales to private consumption 1.13 Sales to investment 1.14 Sales to government consumption 1.15 Sales to export A budget institution normally does not sell its output; instead it receives its funds through the state budget. In the US GNP accounts, the output of a government organization is valued as the sum of its current operational expenditures. A Soviet budget institution is treated in the same manner here. The deficiency in this approach, as is the case in the US accounts, is its failure to take account of the contributions of fixed and working capital. The income and outlay accounts of a budget institution are as follows: Budget Institution Income and Outlay Account Outlays Incomes 2.1 Goods and services 2.2 Wages 2.3 Military pay 2.4 Military subsistence 2.5 Social insurance 2.6 Sales receipts (transfer to budget) 2.7 Budget allocation for operating expenditures 2.8 Sales for intermediate consump- tion to enterprises 2.9 Sales to consumers 29 There is some double counting here for institutions that sell some goods or services, because the list of incomes includes both sales receipts and the entire budget allocation. The sales receipts are also listed as an outlay (item 2.6) when they are transferred to the state budget. An example is a theater or museum that operates on budgetary allocations but collects admis- sion fees. The admission fees would be listed both as an income under item 2.9 and as an outlay under item 2.6. Constructing accounts for the kolkhozy is more diffi- cult because of the scarcity of relevant data. Kolkhoz output is either sold to state procurement agencies, sold directly to state enterprises, sold in kolkhoz village markets, or distributed to members of the collective. In addition, the kolkhoz is expected to pay depreciation and to make sufficient profits to cover investment needs and pay taxes. These flows are outlined below: Kolkhoz Income and Outlay Account Outlays Incomes 3.1 Goods and services 3.2 Money wages of kolkhoz members 3.3 Money wages of hired workers 3.4 Social insurance 3.5 Depreciation 3.6 Taxes 3.7 In kind distributions to kolkhoz members 3.8 Retained income 3.9 Sales to procurement organiza- tions for resale 3.10 Sales for consumption 3.11 In kind distributions to kolkhoz members 3.12 Sales to kolkhoz markets The private household account is concerned with the production of goods and services, as well as with consumption and investment. As producers, house- holds sell agricultural production from their private plots, rent their owner-occupied housing to them- selves, sell various services, and sell newly constructed housing. Some of the values in the account are imputed rather than monetary flows. An example is imputed rent of owner-occupied housing, which is based on the rental rate for state-owned housing and Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 estimated expenditures for maintenance. Household Figure 9 financial flows are categorized as follows: Household Income and Outlay Account Outlays Incomes 4.1 Goods and services 4.2 Net earnings from sales of goods and services 4.3 Imputed wages 4.4 Imputed net rent 4.5 Consumption in kind of private plot output 4.6 Investment in kind of live- stock 4.7 Imputed earnings from pri- vate housing construction 4.8 Rent of owner-occupied housing 4.9 Sales of services 4.10 Sales of new housing 4.11 Sales of agricultural products to the state and private consumption 4.12 Imputed sales of in kind con- sumption of private plot output 4.13 Imputed sales of in kind invest- ment in livestock Definitions and Conventions Sector Classifications. Three measures of GNP are calculated, based alternatively on end use, income flows, and sector of origin. The end uses are, as in Western accounts, consumption, investment, govern- ment, and net exports. The detailed end-use catego- ries are listed in figure 9. Consumption is divided into goods and services. Goods comprise four types of food (animal products, basic foods, processed foods, and beverages), soft goods, and durables. Services com- prise housing rents (cash and imputed), utilities, trans- portation, communications, repair and personal care, recreation, education, and health. Some services are purchased by consumers, and some are partly paid for by the government." Other services either are not available to Soviet consumers, or there are no data with which to estimate them. For example, financial and real estate services furnished to households are negligible, and privately supplied services of lawyers, doctors, dentists, and teachers cannot be estimated adequately, especially over time. Our 1970 weights, however, do include some estimates of private health and educational services. Soviet investment differs from the end-use category in the US GNP accounts by the inclusion of investment in kind in livestock and expenditures on capital repair. Contrary to Western practice, the Soviets make de- preciation deductions for capital repair and account " See JEC, Consumption, for a discussion of the rationale for including government-paid services with consumption. Soviet End-Use and Sector-of-Origin GNP Categories End-Use Categories Sector-of-Origin Categories Consumption Consumer goods Food Animal products Processed foods Basic foods Beverages Soft goods Durables Consumer services Housing Utilities Transportation Communications Repair and personal care Recreation Education Health Investment New fixed investment Machinery and equipment Construction and other capital outlays Net additions to livestock Capital repair Other government expenditures Government administrative services General agricultural pro- grams Forestry State administration and the administrative or- gans of social organiza- tions Culture Municipal services Civilian police Research and development Outlays n.e.c. Industry Ferrous metals Nonferrous metals Fuel Electric power Machinery Chemicals Wood, pulp, and paper Construction materials Light industry Food industry Other industry Construction Agriculture Transportation Communications Trade Services Housing Utilities Repair and personal care Recreation Education Health Science Credit and insurance Government administrative services General agricultural programs Forestry State administration and the administrative organs of social organizations Culture Municipal services Civilian police Military personnel Other branches for these expenditures separately from current repair. In the United States, some repairs of this sort are considered current expense and not included in GNP; others are capitalized and included with new fixed investment. The Soviet investment expenditures re- ported in the Narkhoz include investment by state 30 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 enterprises, the government, and kolkhozy for ma- chinery and equipment, construction-installation work, design work, and other capital outlays, and also investment by private households for housing. New fixed investment, as defined in the reconstructed GNP accounts for the USSR, also includes net additions to livestock, which are part of inventory investment in the US accounts. In contrast to the United States, the Soviets include the cost of installing machinery in construction expenditures. These expenses would be part of investment in machinery in the United States. Because of the different scope of government activity in the Soviet Union, government expenditures are treated somewhat differently than in US GNP. The Soviet Government provides a wide range of consumer services without charge. Government current expendi- tures for health, education, and recreational services are classified here as consumption rather than as government expenditures. The government, through the state budget, also purchases a large share of the investment goods and distributes them to various organizations. These expenditures are treated as in- vestment rather than as government expenditures. Investment in the US accounts includes only private investment; government investment is included in government expenditures. Included in government expenditures for the USSR are current outlays for government administrative services, research and de- velopment, and a part of defense expenditures. Gov- ernment administrative services in turn consist of outlays on cultural activities, municipal services, civil- ian police, general agricultural programs, forestry, and state administration and the administrative or- gans of social organizations. The second basis of classifying GNP is by type of income. This approach is not used in computing the growth of real GNP, but is used to construct the base- year GNP weights. The principal types of household incomes are state wages and salaries, kolkhoz money wage payments, net income from sales of farm prod- ucts, consumption in kind of private agricultural production, earnings from private services, net rent from owner-occupied housing, and net income from construction of private housing. The principal types of income in the public sector are retained earnings, 31 charges for special funds, taxes, depreciation, subsi- dies (as negative income), deductions from profits, and other payments to the budget. The third basis of calculating GNP is by sector of origin, aggregating the income earned in each sector of production activity. The classification of the pro- duction of goods and services conforms to Soviet definitions: industry, construction, agriculture, trans- portation, communications, trade, and services. Indus- try is further broken down into 11 subsectors and services into nine. Military personnel and a small "other branches" sector complete the sectors of origin. The full list of sectors is shown in figure 9. Each type of income earned in 1970 is allocated among the sectors of origin. The values assigned to each sector are then summed to form the 1970 weights for each sector. Each sector weight is then multiplied by a matching volume index to derive the estimated growth of real GNP. Production Boundaries. The definition of a final good or service is not always clear in national income accounting. The main source of uncertainty is wheth- er government expenditures should be considered final or intermediate output. The decision in Western practice has been to declare all government purchases of goods and services to be final output. The more extensive scope of government activity in the USSR makes definition of final output still more difficult. One major problem concerns science expenditures. In the United States, research and development is large- ly financed by private corporations, and their expendi- tures are considered intermediate purchases. The research and development funded by governments is considered final output, being treated as purchases from the various industries that perform research and development on government contract or as direct purchases of materials and wages of government employees. Accordingly, in the US accounts there is not a separate comprehensive account for research and development expenditures. In the Soviet Union, most science expenditures are funded by the govern- ment, and science is considered a separate sector. For practical reasons, then, all Soviet science expenditures Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 are classified as final output in our GNP accounts. Expenditures funded by ministries and enterprises for the final development and implementation of produc- tion of new products are considered to be intermediate purchases." The value of services, such as health and education, that are paid for by enterprises presents a similar problem. In the United States, businesses normally pay for health and educational services directly con- nected with employment. Most Soviet health and education expenses are paid for by the government, but enterprises also are thought to pay significant amounts. Soviet data, however, do not identify which expenditures are for private consumption and which are incidental to the production of goods and services. In these accounts, we estimate the volume of enter- prise payments in 1970 for education and then classify all educational services as final output, contrary to US practice. Valuation of government services poses a question of comparability. In the United States, government serv- ices are valued at cost, as the sum of all current expenditures for materials, services, and wages. This procedure undervalues these services relative to pri- vately provided services because there is no allowance for profits or depreciation. In estimating Soviet GNP, we have followed the same practice, but the more extensive nature of government services in the USSR leads to greater distortion on this account. The Second Economy. The second,, or unofficial, economy in the Soviet Union has grown rapidly, and both its size and significance are now discussed widely. Grossman asserts that the second economy constitutes a large share of the Soviet economy and that its incomplete accounting in GNP distorts meas- ures of the size and distribution of Soviet output. Schroeder and Greenslade argue that the most impor- tant aspects of the second economy are already ac- counted for in the GNP accounts as presented here." " The exact coverage of the Soviet official data on science expenditures is uncertain. In particular, some prototype production may not be included. " Gregory Grossman, "The 'Second Economy' of the USSR," Problems of Communism 26, September-October 1977, pp. 25-40; and Gertrude E. Schroeder and Rush V. Greenslade, "On the Measurement of the Second Economy in the USSR," ACES Bulletin 21, spring 1979, pp. 3-21. The term "second economy" normally is defined to encompass the entire range of private productive activity in the Soviet Union. Most of this activity is legal, including private agricultural production, pri- vate housing construction, and the sale of privately produced services such as health, education, and recreation. Although the present accounts attempt to cover this activity, in all likelihood they do not capture it completely. In addition to the legal activities, a wide variety of illegal activities are carried on, including the theft and sale of state property and the illegal production of certain products, the most prominent of which is liquor." The practice in the US accounts is to exclude illegal activities, and that rule is followed here." Imputations. Several imputations are necessary to account for production that takes place outside of normal buyer-seller relationships and, hence, does not have any monetary value assigned to it. In the Soviet Union, the prime categories of such activity are agricultural production consumed in kind, the value of food and clothing given to members of the armed forces, and the rental value of owner-occupied hous- ing. The goal is to attach a value to these activities using the same prices for which equivalent goods are sold. Thus, the retail prices of food and clothing are used to value military subsistence, the average rent per square meter of state housing is used for estimat- ing the rental value of owner-occupied housing, and the average realized selling price of each type of agricultural product is used to value agricultural output consumed in kind. Valuation of owner-occu- pied housing presents a special problem in that state- owned housing is heavily subsidized, and the proce- dure adopted here implicitly provides a similar subsidy for private housing. The quality of state housing may be superior to that of private housing, but the evidence is insufficient to make an adjustment. " An estimate of private production of liquor in the Soviet Union is in Vladimir G. Treml, "Production and Consumption of Alcoholic Beverages in the USSR: A Statistical Study," Journal of Studies on Alcohol 36, March 1975, pp. 285-320. " The effects of illegal activities on GNP are discussed in Edward F. Denison, "Effects of Selected Changes in the Institutional and Human Environment Upon Output Per Unit of Input," Survey of Current Business 58, January 1978, pp. 37-42. 32 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Summary of Differences in the Soviet and US GNP Accounts As discussed above, the structural characteristics of the Soviet economy have made it necessary to con- struct a set of GNP accounts that differ somewhat from the US accounts. In addition, the lack of data forces some simplification and consolidation of the Soviet accounts as compared with the US accounts. This section summarizes the structure of our Soviet GNP accounts and the differences between the Soviet and US accounts. Three interrelated accounts comprise our Soviet GNP accounting system. The first is the household account. It enumerates the various incomes and outlays, in- cluding imputed, of private households. The house- hold sector is defined to include all activity by households. That is, investment and current produc- tion activity are included as well as consumption and transfer payments. The second account shows the incomes and outlays of the public sector. Because of lack of data, we are unable to differentiate between government final ex- penditures and production activities. As a result, public-sector outlays include government administra- tive expenditures as well as investment bS, khozras- chet enterprises. Similarly, public-sector incomes in- clude tax payments to the budget as well as retained earnings of khozraschet enterprises and kolkhozy. The third account is the consolidated GNP account. It includes the incomes and expenditures resulting from current production activity. The various transfer pay- ments between the household and public sectors are excluded since they do not represent expenditures for goods and services. All of the incomes and outlays are derived from the relevant portions of the household and public-sector accounts. The household and public-sector income and outlay accounts for 1970 are presented in appendix D. The GNP account is discussed in more detail below. The US GNP accounts consist of five accounts. The first account shows personal incomes and outlays. It resembles the Soviet household income and outlay 33 account presented above. The main differences be- tween the accounts are the explicit inclusion of agri- cultural income in kind and private investment in the Soviet account. Agricultural income in kind is includ- ed in the US account, but its importance is small and it does not appear as a separate item. Private invest- ment in the Soviet Union consists of private housing construction and the net addition of livestock to private herds. In the US accounts, these investment activities are considered part of the business sector and are included in gross private business investment. The second US account shows government incomes and outlays. Because of the wide scope of Soviet Government activity and the lack of data to make adjustments, the Soviet GNP accounts merge the equivalent of the business sector with the government sector into an aggregate public sector. In particular, it is not possible to quantify separately government- financed investment and enterprise-financed investment. The third US account is foreign trade. Foreign trade in the Soviet Union is a state monopoly and cannot be separated from the public sector for accounting pur- poses. Foreign trade in the Soviet accounts is, there- fore, shown as a net item in public-sector outlays. The fourth US account shows savings and investment. This account does not exist in the Soviet accounts because of the problem of separating enterprise in- vestment from government investment. The fifth US account shows consolidated GNP as the sum of the relevant parts of the other four accounts. Valuation As is widely recognized, Soviet prices differ markedly in concept from Western scarcity prices. Accurate measurement of the growth of production potential requires the use of prices that come as close as possible to the theoretical standard�that is, the prices of any two products should be proportional to the marginal rate of transformation between the two Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 products. The purpose of Bergson's adjusted factor- cost standard (AFCS) is to adjust Soviet prices so that they more closely approximate the theoretical stand- ard. This section first examines the basic nature of Soviet prices and then describes Bergson's AFCS, its justification, and its limitations. Soviet Established Prices In most countries, GNP is computed only in terms of market prices. The related prices in the Soviet Union are the so-called established prices.' Most prices in the Soviet Union are established by administrative decision rather than by market forces. They are intended to cover material costs, wages, depreciation allowances, social security allowances, other direct costs, and a profit surcharge�in other words, average cost plus a profit markup. While the profit surcharges are intended to average about 15 percent of the stock of fixed and working capital, in practice they are computed as a percentage of input costs. The costs computed are those that would be incurred by an average enterprise producing according to required standards and following normal procedures, rather than the actual production costs of any one enterprise. Thus some enterprises should make above-average profits because of better-than-average production con- ditions, while other enterprises will make less-than- average profits or even losses. This method of price formation, however, does not apply to all prices. Agricultural prices include a bewildering array of procurement, above-plan procurement, direct deliv- ery, zonal, and collective-farm-market prices. The construction industry does not have a standard prod- uct; hence, its prices are formed on a cost plus basis for each construction project. The profits included in Soviet prices are intended to cover the normal uses to which an enterprise is allowed to put its profits while leaving enough for the needs of the state budget. Since the economic reforms in the late 1960s, the enterprises have been allowed to form increased material incentive and other funds from profits and have had to pay a charge to the state for the use of enterprise capital stock. The allowance for profits has, therefore, been increased. The term "prevailing prices" is also used in Western literature. See Bergson, 1961. Established prices in the USSR have several aspects that make them unsuitable as weights in computing the real growth of the Soviet economy. These aspects include large turnover taxes (levied primarily on consumer goods), rapidly growing subsidies on hous- ing and industrial purchases of agricultural goods, widely varying profit rates when computed as a return to capital, differential prices for the same good, and inflated prices of new products. Each of these prob- lems will be discussed briefly. Finding a Basis for Valuing Soviet GNP The important uses of national income statistics in- clude the analysis of resource allocation and the measurement of the growth of economic production capability. A considerable amount of Western litera- ture centers on measurement of national income for these purposes and on what can or cannot be implied from the results.' In practice, Western countries construct GNP accounts using existing market prices as if they met the theoretical requirements for use in measuring resource allocation or economic growth. Although the requirements are never perfectly met, market prices of most Western industrialized coun- tries fit the theoretical model reasonably well, so that the distortions probably are small. The Soviet Union's centrally established and fre- quently arbitrary prices diverge greatly from the theoretical model. The principal requirements of this model are that the relative prices of two goods should be equal to their relative marginal costs and that the rate of return to each factor of production should be equal in all of its uses. Soviet procedures for price formation violate these requirements. A price based on the average direct cost of all enterprises producing a product does not allow for the differential cost of the capital resources being used, for the different utility Among the classic articles are: J. R. Hicks, "The Valuation of ' Social Income,- Economica 7, May 1940, pp. 105-124; Simon Kuznets, "On the Valuation of Social Income," Economica 15, February-May 1948, pp. 1-16, 116-131; J. R. Hicks, "On the Valuation of Social Income," Economica 15, August 1948, pp. 163- 172; P. A. Samuelson, "Evaluation of Real National Income," Oxford Economic Papers 2, January 1950, pp. 1-29; and Richard H. Moorsteen, "On Measuring Productive Potential and Relative Efficiency," Quarterly Journal of Economics 75, February 1961, pp. 451-467. 34 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 that two products of equal cost may have, or for the relative scarcity of the inputs used to produce the product. Since demand has little or no effect on prices, some goods will be in abundant supply while others are rationed. Distortions Caused by Turnover Taxes and Subsidies The turnover tax is one of the major sources of government income in the Soviet Union. It is effec- tively an excise tax levied selectively on various products, but mostly on consumer goods. It can be characterized as a tax on consumers' income, intended to soak up excess purchasing power and to restrain consumer demand. The often high incidence of the tax and its selective application are important reasons why Soviet prices do not fit the Western model which requires that price equal marginal cost. Table 5 shows selected data from the 1972 Soviet input-output table on the level and variability of the turnover tax. Most of the taxes are levied on consumer goods, as indicated by the large amounts collected in the light and food industry sectors. The fuel taxes are an exception: most are collected on interindustrial sales and in some cases are extremely high. In the case of agriculture, the farms pay heavy taxes on fuel pur- chases while receiving a subsidy on electricity purchases. The aggregate data in table 5 not only indicate a high variance in tax incidence, but also hide other differ- ences. For example, the entire turnover tax revenue shown for machinery products arises from taxations of consumer goods, mainly automobiles (the tax accounts for 53 percent of consumption outlays for automobiles in purchasers' prices) and radioelectronics (15 per- cent). Within the food industry, no taxes are paid on the output of the fish, meat, dairy products, flour, and fruit and vegetable sectors. On the other hand, the tax amounts to 30 percent of the gross output of the sugar industry and 56 percent of the gross output of the "other foods" branch, which manufactures alcoholic beverages. Clearly, wide variations in indirect tax rates weaken the usefulness of prices as a measure of production potential. The suggestion has been made that Soviet turnover taxes represent a surrogate factor charge to compensate for the other problems in Soviet prices. 35 Table 5 Turnover Taxes as a Share of Gross Output in Industry, 1972 Turnover Taxes as a Share of Gross Output (percent) Sector Turnover Taxes (billion rubles) Gross Output (billion rubles) Metals 0.1 44.2 0.2 Fuel 5.9 39.2 15.1 Electric power 0.6 14.0 4.1 Machinery 4.3 117.1 3.7 Chemicals 1.1 29.6 3.7 Wood, pulp, and paper 0.2 25.5 0.9 Construction materials 0.4 25.0 1.4 Light industry 15.7 87.5 18.0 Food industry 26.2 126.2 20.8 Other industry 1.0 13.4 7.6 Source: Dimitri M. Gallik, Barry L. Kostinsky, and Vladimir G. Treml, Input-Output Structure of the Soviet Economy: 1972, Foreign Economic Report 18, US Department of Commerce, Bureau of the Census, Foreign Demographic Analysis Division, Washington, D.C.; forthcoming. This issue has been discussed in detail by Becker and Bergson, both of whom rejected the argument." Subsidies also force a divergence between prices and marginal costs. In the 1967 price reform, the prices of natural resources such as coal, oil, gas, and ferrous and nonferrous ores were raised sharply in order to eliminate subsidies or to improve profit levels. Rising extraction costs since then have made once profitable branches unprofitable and led to renewed subsidies and the need to raise prices once again. In the coal industry, for example, profits have declined from 844 million rubles in 1970 to a loss of 626 million rubles in 1978." The most expensive subsidies are now paid on agricul- tural products. The Soviet Government has several times raised procurement prices for various agricul- tural products, notably meat and dairy products, in 42 Becker, 1969, pp. 47-49; and Bergson, 1961, pp. 105-108. " Narkhoz 1978, p. 517. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 6 Billion Rubles Table 7 Subsidies on Agricultural Products Sold to the Light and Food Industries Year Light Industry Food Industry 1966 0.3 3:3 1967 0.3 5.0 1968 0.3 7.3 1969 0.3 8.2 1970 1.7 13.0 1971 1.8 14.1 1972 2.0 15.2 1973 0.6 15.8 1974 0.2 17.3 1975 0.5 19.0 Source: Vladimir G. Treml, Agricultural Subsidies in the Soviet Union, US Department of Commerce, Washington, D.C., 1978, p. 9. order to stimulate production and improve the quality of the Soviet diet. At the same time, the government has held retail prices constant. Therefore, it has had to subsidize the light and food industries increasingly to cover their higher costs. The agricultural subsidy has grown rapidly and now amounts to more than 20 billion rubles per year. Selected data relating to the light and food industries make it clear that the food industry receives most of the subsidy (table 6). The price distortions resulting from the combined effects of turnover taxes and subsidies are most striking at a disaggregated level. Turnover taxes were 30 and 56 percent of the gross outputs of the sugar and other food branches in 1972, while subsidies represented a negative 48 and 22 percent of the gross outputs of the meat and dairy sectors. Thus the subsidies tend to reinforce rather than offset price distortions caused by turnover taxes. Variations in Profit Rates Profits of a khozraschet enterprise-as noted earli- er-are not intended to serve the same purpose as profits in a Western business. Instead, they are a mechanism to obtain sufficient funds for centralized public expenditures, to provide material incentives to Profits as a Percent of Productive Fixed and Working Capital in 1972 Industry 19.3 Electric power 10.2 Oil extraction 26.0 Oil refining 21.8 Gas 46.0 Goal 6.3 Ferrous metals 16.0 Chemicals 19.8 Machinery 20.2 Wood, pulp, and paper 17.7 Construction materials 11.8 Light industry 27.0 Food industry 24.5 Sugar 5.5 Meat 59.3 Transportation 12.7 River transport 12.2 Automobile transport 31.5 Communications 13.9 Source: Narkhoz 1975, pp. 728-29. enterprise management, to measure performance of enterprise management, and to exercise fiscal and administrative control. After the management reforms of 1965, the role of profits increased significantly. Reflecting this, total profits increased rapidly, from 37 billion rubles in 1965 to 87 billion rubles in 1970. Profits, however, are distributed quite unevenly among sectors, and the profit rate on fixed and working capital varies enor- mously (table 7). For this reason, profits do not appear to be a reliable indicator of the contribution of capital to production, a precondition for the use of established prices as a measure of production potential. Moreover, much of the service sector does not earn profits because the enterprises are financed from the state budget. The lack of any charge for the use of capital stock in the service sphere undervalues the resources used to produce those services. 36 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Differential Prices and New-Product Pricing Not only do relative prices of Soviet goods and services not correspond to relative costs of resources used in their production, but the price of a product often varies according to purchaser. The price dis- crimination is sometimes accomplished by selective application of taxes and subsidies, and sometimes by charging different prices. The full extent of this price discrimination is not known, but it is especially preva- lent in the fuel sector. The indirect consequence is a divergence in the relative prices of output from the value of resources used. Once a product is in serial production in the USSR, its price rarely changes. This is due partly to bureau- cratic inertia and partly to the convenience of price stability for planning and administration. To increase profits, many enterprises and ministries introduce new products that are new in name only. Creating a new product permits establishment of a new, higher price for essentially the same good and results in relative prices that do not reflect relative resource use and hence do not measure accurately the production po- tential of alternative economic activities. As with differential prices, we have insufficient information to account for this price distortion. Whenever possible, therefore, we use physical output data to measure changes in the level of output rather than deflated value data. While avoiding the new-product price problem, this method tends to understate quality change." The Adjusted Factor-Cost Standard Because of the deficiencies of Soviet prices, Bergson concluded that established prices did not conform sufficiently well with the requirements of the theory of optimal resource allocation to permit their use in measuring the change in Soviet production potential over time or to study the resource allocation pattern adopted by the Soviet Union. As an alternative, he proposed his adjusted factor-cost standard. For GNP to measure production potential, some strong assumptions are required: chiefly perfect com- petition, the absence of price distortions in factor " This issue is discussed in more detail in Comparing Planned and Actual Growth of Industrial Ouput in Centrally Planned Econo- mies, Central Intelligence Agency, National Foreign Assessment Center, Washington, D. C., 1980. 37 markets, and the full use of all productive factors. If these conditions are met, then the economy will operate on its production-possibility frontier, where the production of any product cannot be increased unless the production of some other product is de- creased and where the relative prices of the two products indicates the trade-off. Bergson hypothesized that the Soviet economy does not operate on its production-possibility frontier, but rather on a feasibility locus which is well short of the frontier. This shortfall of production may result from bureaucratic inefficiency or from the misallocation of resources. Bergson further conjectured that the feasi- bility locus is broadly parallel to the production- possibility frontier. Working from this hypothesis, Bergson derived a set of price rules that would be sufficient to measure the growth of production potential as represented by the feasibility locus. These rules form his AFCS. Accord- ing to Bergson, if the feasibility locus were to ap- proach the production-possibility frontier, then the AFCS would also approach the efficiency standard for valuing national income. Broadly speaking, the AFCS ensures that prices are equal to average cost and that factor prices are equal between markets and proportional to factor productivities. In particular, the AFCS requires that the following statements be true: � All product prices must resolve into charges for primary inputs; that is, for land, labor, and capital. � The differences in wages among sectors represent differences in labor productivity and workers' disutility. � Rent is charged for the use of superior land and other natural resources. � The charge for capital consists of a depreciation allowance and an interest payment based on a rate of interest corresponding to the average level of capital productivity." � Commodity prices are uniform within a given mar- ket area. " There is a difference of opinion over whether capital stock should be valued gross or net of depreciation. The capital stock data used in this study are gross of depreciation. 93-892 - 8? _ Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 It should be clear that the AFCS is an imperfect measure of production potential and that our empiri- cal application of it is even more imperfect. The prices that we implicitly construct using the AFCS are not the equilibrium prices of Western national income theory, and the data do not exist to implement the AFCS with great precision. Nevertheless, the AFCS is to be preferred to Soviet established prices because it removes major price distortions and provides a better measure of changes in production potential and resource allocation than do Soviet prices. Our application of the AFCS builds on the work by Bergson and Becker. Starting with established prices, they deleted turnover taxes and added subsidies to arrive at GNP by sector of origin at factor cost. The effect of these price changes was then estimated on the various components of GNP by end use. The same adjustments also are done here. The availability of reconstructed Soviet input-output tables, however, permits some improvement in the allocation of the adjustments among end-use sectors. In addition, we replace profits with a capital charge which is calculat- ed as a percentage of each sector's stock of fixed and working capital, and extend our earlier use of the input-output tables by integrating the service sectors into the adjustment process. Soviet GNP in 1970 in Established Prices and at Factor Cost This section presents GNP accounts for the Soviet Union in 1970 in established prices and then converts the accounts to factor-cost prices, step by step: � The 1970 accounts in established 'prices are elabo- rated into an input-output framework. � A 1970 input-output table in producers' prices is estimated. � A factor-cost repricing algorithm is developed and applied to the 1970 input-output table. The Revised 1970 Soviet GNP Accounts CIA's original estimates of the 1970 GNP accounts were published in 1975." The revisions in those accounts to take account of new information are described in appendix D, and the revised accounts are " CIA, GNP 1970. summarized in tables 8 and 9. These accounts are based on an elaboration and recombination of the income and outlay flows described above. The income account (table 8) combines portions of the left-hand column in each of the individual accounts. Thus, state wages and salaries are the sum of items 1.2 and 2.2. Similarly, the expenditure account (table 9) shows data from the right-hand side of each set of accounts. In order to estimate the relationship between estab- lished prices and factor-cost prices, it is necessary to identify the effect of a price change in one sector on the price level of all sectors. This is necessary because a change in value added, such as replacing profits by a capital charge, represents a price change. The device used for this purpose is an input-output (I-0) table. It shows the structure of each sector's purchases from and sales to each sector, which allows the direct and indirect effects of a price change to be traced. In order to use an I-0 table, the data in tables 8 and 9 need to be disaggregated according to I-0 definitions. The value-added quadrant of an I-0 table identifies the types of income shown in table 8 with the sector in which it is produced (columns of the I-0 table). Similarly GNP by end use (table 9) represents the final expenditures on final goods and services. The final-demand quadrant of the I-0 table identifies these expenditures with the sectors from which they are purchased (rows of the I-0 table). Both of these disaggregations are shown in appendix E. Construction of the 1970 Input-Output Table and Conversion of the 1970 Accounts to Factor Cost The construction of the 1970 input-output table pro- ceeds in two steps. First, the established-price data are converted to producers' prices. Then the converted data are used with an I-0 updating algorithm to estimate a 1970 I-0 table in producers' prices based on the structure of the Soviet 1972 I-0 table in producers' prices. Producers' prices are equal to estab- lished prices less turnover taxes, plus subsidies, less trade and transportation expenses on delivered prod- ucts.' Producers' prices are used to estimate the 1970 47 For a detailed discussion of producers' prices, see Vladimir G. Treml et at., Conversion of Soviet Input-Output Tables to Produc- ers' Prices: The 1966 Reconstructed Table, US Department of Commerce, Bureau of Economic Analysis, Foreign Economic Re- port No. I, Washington, D.C., 1973. 38 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 8 Billion Rubles Gross National Product of the Soviet Union in Established Prices, by Type of Income, 1970 Table 9 Gross National Product of the Soviet Union in Established Prices, by End Use, 1970 Billion Rubles Wage bill 135.412 Consumption 211.083 State wages and salaries 132.032 Goods 166.478 Military pay and allowances 3.380 Food 107.926 Other and imputed income 62.251 Soft goods 44.294 Net income of households from agriculture 41.709 Durables 14.258 Military subsistence 3.200 Services 44.605 Other money income currently earned and 10.598 Housing 3.429 statistical discrepancy Utilities 3.478 Imputed net rent 1.080 Transportation 5.400 Imputed value of owner-supplied construction services 0.579 Communications 1.200 Repair and personal care 5.497 Charges to economic enterprises for special funds 5.085 Recreation 2.608 Education 0.400 14.380 Education Research 2.578 Health 8.613 Social-cultural measures and sports activities 0.162 Investment 109.220 Militarized guards 0.880 New fixed investment 90.220 Support for administration of higher echelons 1.065 Machinery and equipment 26.053 Social insurance 9.436 Construction and other capital outlays 59.800 Profits 89.154 Net additions to livestock 4.367 State enterprises 79.591 Capital repair 19.000 Retained profits of state enterprises 26.481 Other public-sector expenditures 62.956 Deductions from profits of state enterprises 53.110 Government administrative services 9.030 Collective farms 7.852 General agricultural programs 1.004 Retained income of collective farms 7.186 Forestry 0.636 Tax on income of collective farms 0.666 State administration and the administrative 3.821 Consumer cooperatives 1.283 organs of social organizations Retained profits of consumer cooperatives 0.821 Municipal and related services 3.569 Tax on income of consumer cooperatives 0.462 Culture 1.180 Other organizations 0.428 Municipal services 0.628 Retained profits of other organizations 0.321 Civilian police 1.761 Tax on income of other organizations 0.107 Research and development 10.343 Depreciation 31.827 Outlays n.e.c. 28.429 Turnover and other indirect taxes 77.732 Net exports 0.961 Turnover taxes 53.346 Defense n.e.c., unidentified outlays, and 27.468 Miscellaneous charges 24.386 statistical discrepancy Allowances for subsidized losses n.e.c. -22.553 Inventories 15.154 Gross national product 383.259 Gross national product 383.259 Source: Appendix D. Source: Appendix D. 39 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 1-0 table because relative producers' prices are thought to be more stable over time than relative purchasers' prices. Since Soviet I-0 tables show only the productive sectors," while the transportation and communica- tions sectors furnished both productive (freight trans- portation) and nonproductive (passenger transporta- tion) services, these GNP sectors must be disaggregated. In addition, to obtain a value-added quadrant in producers' prices, we must compute: (1) the implicit subsidies received and turnover taxes paid by each productive sector on its material purchases, (2) the nonproductive services purchased by each sector, and (3) the material purchases of the service sectors. These estimates are explained in more detail in appendix E. The 1970 I-0 table is estimated with the help of a least squares minimization algorithm. It estimates a 1970 1-0 table in producers' prices that is as much like the actual 1972 table as possible, with the constraint that each row and column must sum to a predetermined amount. The row and column sums are determined as each sector's gross output less, respec- tively, its value added or final demand. See appendix E for further discussion of the algorithm and its rationale. Many of the steps taken to compute the 1970 I-0 table in producers' prices are part of the conversion to factor-cost prices, notably the elimination of turnover taxes and subsidies on final goods and services. The remaining steps eliminate the rest of turnover taxes and subsidies and replace profits with a uniform capital charge. In our earlier publication on the 1970 GNP accounts, the uniform capital charge was set at 12 percent of the sum of fixed and working capital. The present report follows the work of Brown, Hall, " The Soviet Union divides its economy into productive and nonproductive sectors. Productive sectors are those which produce material goods (industry, construction, and agriculture) and those which are needed to deliver material goods to their final user (freight transportation, business communications, and wholesale and retail trade). and Licari in applying 1-0 repricing algorithms, developed originally for East European 1-0 tables, to determine the interest rate." The repricing procedure or algorithm relies on a basic property of an 1-0 table: that the sum of the entries in a particular column must equal the sum of the entries in the corresponding row. That is, a sector's sales must equal its total expenses, including profits. This proper- ty, plus the distribution of each sector's sales de- scribed by an I-0 table, provides the ability to relate an increase in the price of the output of one sector to increases in the costs of all sectors. Thus, equalizing the rate of return on each sector's fixed and working capital implies a given set of changes in relative prices, and the 1-0 table can be used to compute directly the required array of price changes. A Comparison of Established and Factor-Cost Prices Tables 10 and 11 compare the percentage distribution of GNP by end use and by sector of origin, in established prices and in factor-cost prices. As expect- ed, the largest difference in the end-use distribution (table 10) is the increase in the share attributed to services, especially housing, when factor-cost prices are used. Expenditures on consumer services, which were 11.6 percent of GNP in established prices, are 19.5 percent of GNP in factor-cost prices. The hous- ing share increases from 0.9 to 7.0 percent of GNP. The shares of most other services also rise. The major reductions in GNP shares are in consumer goods, especially beverages, soft goods, and durables. These changes stem mainly from the elimination of turnover taxes. As a whole, however, the share of consumption is about the same in established prices (55.1 percent) as in factor-cost prices (54.2 percent). The share of investment is virtually unchanged by the use of factor-cost prices. Total investment is 28.5 percent of GNP in established prices and 28.2 percent in factor-cost prices, with the structure almost the same. " Alan A. Brown, Owen P. Hall, and Joseph A. Licari, Price Adjustment Models for Socialist Economies: Theory and Empiri- cal Technique, International Development Research Center, Bloo- mington, Ind., 1973. 40 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 10 1970 Soviet Gross National Product by End Use Percent Table 11 Established Prices Factor-Cost Prices Consumption 55.1 54.2 Consumer goods 43.4 34.7 Food 28.2 25.5 Animal products 11.0 14.3 Processed foods 3.6 2.7 Basic foods 6.0 6.1 Beverages 7.5 2.4 Soft Goods 11.6 6.8 Durables 3.7 2.5 Consumer services 11.6 19.5 Housing 0.9 7.0 Utilities 0.9 1.0 Transportation 1.4 1.7 Communications 0.3 0.5 Repair and personal care 1.4 1.2 Recreation 0.7 1.0 Education 3.8 4.5 Health 2.2 2.6 Investment 28.5 28.2 New fixed investment 23.5 23.4 Machinery and equipment 6.8 6.7 Construction and other capital outlays 15.6 15.6 Net additions to livestock 1.1 1.2 Capital repair 5.0 4.8 Other public-sector expenditures 16.4 17.6 Government administrative services 2.4 2.8 Research and development 2.7 3.1 Outlays n.e.c. 11.4 11.6 Source: See text. As regards changes in the distribution of GNP by sector of origin (table 11), the two sectors showing the largest increases in percentage shares of GNP as a result of repricing are trade (retail, wholesale, and agricultural procurement) and housing. The light and food industry sectors experienced the greatest decline in GNP shares, primarily because most of the turn- over taxes are collected in those sectors. 41 1970 Soviet Gross National Product by Sector of Origin Percent Established Prices Factor-Cost Prices Industry 45.8 32.0 Ferrous metals 1.9 2.3 Nonferrous metals 1.2 1.3 Fuel 3.9 3.1 2.2 10.1 2.0 Electric power 1.5 Machinery 11.9 Chemicals 2.6 Wood, pulp, and paper 2.9 2.4 Construction materials 2.0 2.1 Light industry 8.7 2.5 3.0 0.9 Food industry 7.4 Other industry 1.7 Construction 7.4 7.3 Agriculture 20.5 21.1 Transportation 7.4 8.7 Communications 0.7 0.9 Trade 4.8 7.3 20.5 Services 11.4 Housing 0.9 7.2 Utilities 0.5 0.6 Repair and personal care 1.1 1.2 Recreation 0.5 0.8 Education 3.0 3.8 Health 1.6 2.0 Science 1.6 2.0 Credit and insurance 0.3 0.4 2.5 0.3 0.1 1.2 0.4 0.2 Government administrative services 1.9 0.2 General agricultural programs Forestry 0.1 State administration and the ad- ministrative organs of social organizations 0.8 0.3 Culture Municipal services 0.1 Civilian police 0.4 0.4 Military personnel 1.8 1.9 Other branches 0.3 0.3 Source: See text. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Problems in Estimating Volume Indexes of Economic Activity in the USSR The real growth of Soviet GNP is computed by multiplying each of the 1970 sector-of-origin and end- use weights by an appropriate constant-price activity index. While use of this method is not unusual in OECD countries, it is more common to deflate cur- rent-price data. The lack of detailed Soviet price indexes and our distrust of those that do exist pre- cludes that approach here. The problems of estimating constant-price indexes have generated a voluminous amount of literature." In connection with the presentation of our Soviet GNP indexes it is appropriate to summarize some of the general problems encountered in working with index numbers. Effect of the Base Year on the Growth Rate In the computation of GNP, the aggregation of physical quantities expressed in different units re- quires the use of prices as weights. Thus the growth of GNP between any two years in constant prices is the ratio of two summations of prices times quantities. If relative prices or quantities of the various goods and services produced in the two years are the same in each year, then it does not matter whether the prices of the first or second year are used for aggregation. In general, however, technological progress; changing endowments of land, labor, and capital; and other factors will cause changes in relative prices. In prac- tice, then, the measured GNP growth rate will vary, depending on whether prices of the first or second year are used. In computing a series of growth rates for a multiyear period, it is possible to use the prices of one year for " Some of the general sources are: Lawrence Grose, Real Output Measurement in the United States National Income and Product Accounts, US Department of Commerce, Washington, D.C., 1967; T. P. Hill, The Measurement of Real Product, The Organization for Economic Cooperation and Development, Paris, 1971; R. G. D. Allen, Index Numbers in Theory and Practice, Aldine Publishing Co., Chicago, 1975; United Nations, Guidelines on Principles of a System of Price and Quantity Statistics, New York, 1977; Richard Stone, Quantity and Price Indexes in National Accounts, Organi- zation for European Economic Cooperation, Paris, 1956; Franklin M. Fisher and Karl Shell, The Economic Theory of Price Indices, Academic Press, New York, 1972; and Dan Usher, The Measure- ment of Economic Growth, ch. 4, Columbia University Press, New York, 1980. all calculations or to use a moving price base. With a moving price base, the weights used to combine the constant-price volume indexes are different for each calculation. In this report, 1970 prices are used for all growth rate calculations. The primary reason for this approach is that the construction of current-year weighted (Paasche) indexes requires current-price GNP accounts for each year, information which is not currently available. In addition, Western practice is to use the base-year weighted (Laspeyres) For analysis of current trends, the base year should be reasonably close to the current year so that the base- year relative prices are not greatly different from those of the current year. For the Soviet Union, 1970 is sufficiently recent to qualify as Soviet prices have not changed much since then. The large energy price changes of 1973-74 make it more important to use a price base of 1975 or later for a Western economy." Aggregation of Quantity Indexes Instead of Deflated Value Indexes There are two basic methods of computing a constant- price activity index of the output of a collection of goods or services. Assuming that observations are available on the quantities produced and the prices of each good or service, then the current-price output can be deflated by a price index, or a weighted quantity index can be computed. With full informa- tion, the result will be the same. For the year 0, let Q(0,1), , Q(0,i), , Q(0,N) be the physical quantities of the N goods produced in year 0 and p(0,1), , p(0,i), , p(O,N) the corresponding prices. Then the growth of output from year 0 to year t, expressed in current prices, is: I Q(t,i)p(t,i) i= 1 Q(0,0p(0,i) i= 1 " Bergson, 1961, pp. 25-41, discusses the various economic interpre- tations of the two indexes. Also, see Becker, 1969, pp. 69-72, and the sources listed in footnote 50. " The benchmark of the US accounts in 1981 retained 1972 as the base year, implying that the data for using a more recent base year are not available or that the US national income accountants do not think the change in relative prices is a severe problem. Many OECD countries, however, have shifted to a 1975 base year. 42 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 If this expression is deflated by a Paasche (current- year weighted) price index, then the desired Laspeyres output index is obtained: Q(t,i)p(t,i) i= 1 ; Q(0,i)p(0,i) E Q(t,i)p(0,i) = 1 i= 1 � Q(t,i)p(t,i) i= I E Q(t,i)p(0,i) i= 1 E Q(0,i)p(0,i) i= 1 Rarely is information available on production and prices for all goods and services in both the base and the given year. If only a sample of observations is available, then the two sides of the previous equation may not be the same. For example, suppose there are N products, but price and quantity data are available only for n (less than N) products. The estimated growth of output from year 0 to year t using the deflated current-price index would be: E Q(t,i)p(0,i) E Q(t,i)p(t,i) E Q(t,i)p(0,i) i= I = i= I i= I X � Q(0,i)p(0,i) E Q(0,i)p(0,i) E Q(t,i)p(t,i) 1=1 i= 1 i= I and the estimate using the quantity index would be: � Q(t,i)p(0,i) E Q(t,i)p(0,i) i= 1 = i=1 � Q(0,i)p(0,i) 1=1 E Q(0,i)p(0,i) i= 1 If n=N, then the two equations are identical. If n is less than N, the reliability of the deflated current- price index depends on the accuracy of the price index 43 computed from the sample data, and the reliability of the quantity index depends on the representativeness of the quantity sample. Hill argues that the price index is likely to be more accurate, especially when large numbers of new products are being introduced arid old products withdrawn." Unfortunately, Soviet price data are so scarce and unreliable that the deflation method is not practical either for GNP as a whole or for most individual sector indexes. The quantity index method is relied upon almost exclusively. Specific Index Number Problems Several specific index number problems are also important in the measurement of Soviet GNP. They arise in the treatment of regional production, seasonal production, price discrimination, quality changes, and unique products. Regional Production. The resources required to pro- duce a given product may be quite different depend- ing on where a product is made. For example, a school building of exactly the same dimensions may cost much more to construct in Siberia than in the Ukraine because of greater transportation expenses, more stringent structural requirements, a larger heat- ing unit, and more difficult construction conditions. To the extent that the added cost reflects real differ- ences in the use of resources, a shift in production to a more expensive region represents an increase in pro- duction rather than a price increase. Theoretically, we should construct weighted regional production index- es, but the scarcity of data does not permit doing so. The influence of regional production on the growth of GNP is probably most important in the construction, agriculture, and fuel sectors. Seasonal Production. Changes in seasonal production patterns present a similar problem. A vegetable grown near Moscow in a hothouse during the winter requires more resources than the same vegetable grown out- doors during the summer. Theoretically, the two vegetables should be treated as different products, and a production or price index containing them " Hill, Measurement, p. 25. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 should be weighted appropriately. The Soviet Union attempts to capture this effect in the construction sector by allowing price supplements for work done during the winter. No adjustments are made in this study. Price Discrimination, Quality Changes, and Unique Products. According to one of the conditions of the AFCS, product prices must be uniform within a market area. This condition is violated frequently in the Soviet Union, especially in energy pricing. Some sectors pay preferential prices, receive higher quality products for the same price, or enjoy special delivery privileges. To the extent that differential prices are included in the input-output data, the factor-cost prices are inaccurate. Changes in the degree of dis- crimination will also affect the indexes. The problem of quality change is pervasive in index computations. The basic question is how much of the change in the price of a product actually reflects a change in the quantity of the services provided by the product. The answer is not always clear. The problem is particularly severe in the Soviet case, because we rarely can observe products over time on a scale sufficient to assess quality changes and because a common method of raising prices in the Soviet Union is to make a cosmetic change in the product and call it a new product. The quality problem mainly affects our index of industrial production, which frequently relies on physical output data covering fairly broad product categories. The lack of adjustments for quali- ty changes probably understates real quantity changes." Many investment goods are produced as unique prod- ucts or in very small batches. Most construction projects and as much as one-third of producer dura- bles constitute unique products. A variety of tech- niques have been devised to measure the real cost of unique products: summing input costs; using hedonic indexes; using a related, standard product as an analog; and computing the cost as a sum of standard components. The construction index used here, for example, is a material-input index rather than an output index. Although we suspect that our index of See Comparing Planned and Actual Growth, Central Intelligence Agency, Washington, D.C., for a discussion of this problem. investment in producer durables (based on official values in so-called constant estimate prices) overstates growth, we lack the data to use an alternative approach. Problems of Measuring the Real Growth of Value Added The discussion to this point has centered on the problems of any constant-price activity index. The construction of indexes of value added in economic sectors poses additional problems. Value added cannot be measured directly in constant prices because changes in depreciation, profits, and social insurance do not lend themselves to separation into price and quantity changes. Therefore, value added is computed as a residual�the difference between gross output and current material inputs. This procedure makes value added especially subject to measurement error. Specialists generally agree that the preferred ap- proach to measure real changes in value added is the so-called double deflation method. If Q(j,t) is the gross output of sector j in year t, q(i,j,t) is the current input of type i used by sector j in year t, n is the number of sectors, and p(j,t) is the price of the good or service produced by sector j in year t, then value added in sector j in year t is: p(j,t)Q(j,t) � p(i,t)q(i,j,t). i= I The value added in base-year prices (year 0) is then computed as the difference between the deflated values of both terms, or: V(j,t) = p(j,0)Q(j,t) � p(i3O)q(i,j,t). i = 1 The virtue of this approach is that it preserves consistency between the end-use and sector-of-origin accounts. If the sales of all sectors are properly deflated, then the sum of deliveries to end-use compo- nents of GNP in base-year prices will equal the sum of deflated value added by sectors of origin. 44 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Several problems preclude widespread use �double deflation: � It requires a great deal of data to implement. A full I-0 table is needed for a complete accounting of a sector's inputs. A surrogate method relying on a price index of a sample of a sector's inputs can be used, but even this requires much data and will not support timely estimates. � Double deflation assumes that the inputs actually used in year t by sector j would have been used even with a different set of relative prices, an unlikely occurrence. It is possible that value added calculat- ed by the double deflation method could be negative if the prices of some of the major inputs in year t in- creased greatly between year 0 and year t. � Because double deflation is the difference between two values, it is subject to large fluctuations that result from small fluctuations in the two other values." " Hill investigated the conditions under which double deflation is the best procedure for estimating value added (Measurement, ch. 2.) Let y be the ratio in constant prices of the inputs used by sector j in year t compared to year 0: y= Let z be the gross output index of sector j: z = p(j,0)Q(j,t)/p(j,0)()(j,0). Finally, let x equal the ratio of sector i's inputs to its gross output: x = Zp(i3O)q(ij,0)/p(j,0)Q(j,0). It can be shown that the index of value added in constant prices is the following weighted average of z and y: v = (wXz)+(l�wXy), where w = 1/(1�x). Since x is always less than 1, w is greater than 1 and 1�w is less than 0. If sector j uses very few inputs, then x is small, w is close to 1, and the value-added index approximates a gross output index. If sector i's use of inputs is high, then w is very large, and the weight for the inputs, 1�w, becomes a large negative value. The question now becomes should v be computed as the weighted average just described, as an index of gross output, or as an index of some other quantity, such as employment. The answer depends on the reliability of the various indexes involved. Unfortunately, if both z and y have some error, the error in v will tend to be the sum of the two errors rather than their average or difference. Therefore, the error in v increases rapidly with an increase in uncertainty in the two other indexes. This error should then be compared with the error that would be obtained by using the gross output index alone. 45 It turns out that double deflation is optimal only when knowledge of both the output and input indexes is perfect. As uncertainty about either index increases, the advantages of using the gross output index in- crease.56 Hill surveyed the practice of OECD mem- bers and found that agriculture is the only sector for which double deflation is frequently used. This prac- tice is also true of our sector-of-origin indexes. Except for agriculture, we use gross output or some other indicator of the level of production as our index of value added. If double deflation is not used, and if a gross output index is not available or not accurate enough, then some other indicator must be used. Among those that have been suggested are an input index; an employ- ment, hours worked, or deflated wages index; an employment index plus an arbitrary productivity al- lowance; or an index of some related industry. In this study we have used gross physical output in most of the nonservice sectors. We also use gross output indexes for some of the service sectors, but many are simple indexes of man-hour employment. A detailed list of our sectors and the type of index used for each follows. The construction of the indexes is described in appendixes B and C. Ibid, p. 20, and footnote 55. According to Hill, if x = 0.5 and if the standard deviations of the errors in the growth rates of the output and input indexes are both 1 percentage point, then the difference between the output and input indexes must be at least 2 percentage points in order for double deflation to be preferred to the use of the gross output index alone. It is interesting that the gross output index is always closer to the value-added index than is the input index. The expression of v as a weighted average of z and y can be rewritten as: v = wz+(l�w)y = z+wz�z�(w-1)y = z+(w�lXz�y). Therefore, if z > y (gross output grows faster than inputs) and if w-1 > 0 (the base-year share of inputs is between 0 and 1), then: v = z+(w�lXz�y) = z+b, where b > 0, and v > z > y. The reverse is also true: if z < y, then v < z < y. Therefore, if in- dexes of gross output and current inputs are both available, the gross output index is always a better indicator of value added unless the errors associated with the gross output index are much larger than those associated with the input index. Approved for Release: 2019/07/19 C05210421 Soviet GNP Indexes End-Use Indexes Consumption. The consumption index (described in detail in JEC, Consumption) consists of three consum- er goods indexes and eight consumer services indexes. The consumer goods indexes are (1) food, (2) soft goods, and (3) durables. The consumer services index- es are (1) housing, (2) utilities, (3) transportation, (4) communications, (5) repair and personal care, (6) recreation, (7) education, and (8) health. Consumer Goods. Food. The food index aggregates 18 categories of food. Three basic types of indexes are used. Ten of the 18 (fish, meat, milk, vegetable oil, sugar, eggs, potatoes, vegetables, fruit, and flour and groats) are determined from physical per capita con- sumption data (published in the Narkhoz) and the size of the population. The milk, sugar, and flour and groats figures are known to contain the milk, sugar, and flour used in making butter, confectionery prod- ucts, and macaroni products, so deductions are made in order to avoid double counting. Six of the 18 indexes are based on production data (butter, cheese, tea, margarine, confectionery products, and bever- ages), with adjustments for inventory changes and foreign trade where possible. The other two indexes (macaroni and tobacco) are based on deflated retail sales data. Deflated sales data are less satisfactory than the per capita consumption and production in- dexes because Soviet price indexes probably under- state inflation and hence overstate growth. The 18 indexes are each multiplied by a 1970 estimate of consumption expenditures and then summed for each year to obtain consumption of food in 1970 estab- lished prices. For computation of the factor-cost prices, the food index was subdivided into four parts�animal products, processed foods, basic foods, and beverages, so as to take account of the differential effects of subsidies and taxes on different types of foods. Conversion to factor-cost prices raises the weight of animal products and lowers the weight of beverages. Soft Goods. The soft goods index is a weighted sum of indexes for 15 line items. Nine line-item indexes (cotton, wool, silk, and linen fabrics; haberdashery; school supplies; publications; household soap; and Approved for Release: 2019/07/19 C05210421 toilet soap) are based on deflated retail sales. Five line-item indexes (hosiery; leather, rubber, and felt footwear; and knitwear) are based on physical produc- tion data, and one (sewn goods) is based on Soviet reported production in rubles in constant prices. As with the food index, each line-item index is multiplied by estimated consumption expenditures in 1970 and summed. No attempt is made to recompute the internal weights of the soft goods index in factor-cost prices. Durables. The consumer durables index is the least satisfactory of the consumption indexes. It consists simply of total deflated retail sales of nonfood goods less the deflated retail sales of identified nondurable goods. All retail sales are deflated, if possible, by the corresponding official retail sales price index. The resulting series undoubtedly includes some nondura- bles and is not adequately deflated. There is not enough information, however, to construct an index based on production or sales of individual consumer durables. Consumer Services. Housing. The housing index is the stock of housing measured in millions of square meters of urban and rural housing�the only aggre- gate data available. Since the index is based on purely physical measures, it does not capture changes in the average quality of Soviet housing." Utilities. The utilities index is a weighted average of household consumption of electricity, gas, and the urban housing stock. The latter is intended to repre- sent household consumption of centralized heat, hot water, water, and sewage services, for which data are not available. Information for electricity and gas consumption is incomplete and involves some interpo- lations and extrapolations. Transportation. This index is a weighted average of nine modes of passenger transportation. Rail, sea, inland- waterway, bus, and air transport are measured by passenger-kilometers; tram, trolleybus, and subway " See JEC, Consumption, for a more detailed discussion of this problem. 46 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 transport are measured by the number of rides; and taxi services are measured by the volume of paid kilometers. It was assumed that 25 percent of the 1970 expenditures on passenger transportation repre- sented business travel expenditures; this amount was deducted in arbitrary proportions from the rail, air, and taxi weights. No allowance was made for a change in the relative importance of business travel over time. Communications. Since a large share (about two-thirds) of communications activity is considered to be consump- tion rather than production related, we use our index for total communications as a sector of origin. This index is a weighted average of: (1) the volume of letters, newspapers, parcels, and money orders mailed, (2) the number of telegrams sent, (3) the stock of telephones and the volume of long distance telephone calls, and (4) the stock of radio and television receivers and the number of radio relay facilities. Repair and Personal Care. This index is the sum of expen- ditures on state-supplied services and on private serv- ices. State services include the repair of clothing, shoes, furniture, radio and television receivers; dry cleaning; film processing; and similar household serv- ices. The index is based on sales data in constant prices patched together from several Narkhoz series. Estimates of sales to state organizations were deduct- ed from the Narkhoz values. Also the value of materials used in some types of services, but not included in the Narkhoz data, were added. The purchase of private services is based on a few reports of aggregate expenditures and is not a satisfactory index. It represents, however, a declining share of the total index; hence, errors in the estimate of private services should not greatly disturb the total index. Recreation. The recreation index attempts to measure a diverse collection of expenditures. It is computed as a weighted average of the number of movie and theater admissions, the number of people attending resorts, and employment in hotels. The latter is a crude measure of personal expenditures on hotels. Education. The education index is a weighted average of indexes of employment and other current expendi- tures. The employment index is based on man-hour 47 data and is straightforward. The calculation of other current expenditures is quite complicated. It is based on budgetary data for several levels of educational activities. For each level, all labor and capital expend- itures identified in republic budget data are subtract- ed from the total, yielding a residual that is assumed to represent current expenditures other than labor costs. Each index of nonlabor current expenditures is then applied to a USSR total for that level of educational activity to obtain a series of nonlabor current expenditures expressed in current prices. The sum of those series is then deflated by our implicit price index for the consumption of goods." Health. Construction of this index parallels that of the education index, but in less detail. Investment. The index of Soviet investment is a weighted average of indexes of new fixed investment and capital repair. The index of new fixed investment, in turn, is a weighted average of investment in machinery and equipment, construction and other capital outlays, and net additions to livestock. The index of investment in machinery and equipment is taken directly from the Narkhoz, and is said to be in constant prices. Most machinery and equipment, how- ever, are produced by the machinery sector, for which the published price index is widely believed to be seriously understated." Thus, we suspect that the growth of investment in machinery and equipment may be overstated. The index of construction and other capital outlays are derived from our sector-of- origin construction index described below. The two major products of the construction sector are new construction and capital repair. The construction component of capital repair is estimated and then subtracted from the sector-of-origin index for the total construction sector. The Narkhoz series on "See M. Elizabeth Denton, "Soviet Consumer Policy: Trends and Prospects," JEC, 1979, p. 766, for the derivation of this price index. An Analysis of the Behavior of Soviet Machinery Prices, 1960- 73, US Central Intelligence Agency, Washington, D.C., 1979; and Abraham Becker, "The Price Level of Soviet Machinery in the 1960s," Soviet Studies 26, July 1974, pp. 363-379, are two of many sources that discuss the shortcomings of the official machinery price index. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 investment in construction-installation work is be- lieved to overstate the growth of new construction. While the residual calculation used here is not fully satisfactory, the resulting index does show slightly slower growth than the Narkhoz series. The series on net additions to livestock is a part of the index of agricultural output and is based on reported changes in livestock numbers. The major difficulty with this index is that large changes in livestock inventories often reflect disproportionate swings in the numbers of young livestock, whose value per head is less than average. This causes excessive fluctuations in the index. The capital repair index is a deflated current- price index. The major data available on capital repair are current-price data on amortization deduc- tions and budget allocations for capital repair. The machinery and construction components are deflated separately using price indexes constructed by compar- ing Soviet production in current prices with our reconstructions in constant prices. Other Government Expenditures. Government Admin- istrative Services. This index is a collection of small services: (1) general agricultural program, (2) forest- ry, (3) state administration and administrative organs of social organizations, (4) culture, (5) municipal services, and (6) civilian police. All of these indexes are based on man-hour employment because we have no physical indicators to measure the output of these services. As is well known, indexes based on employ- ment, by definition, do not reflect changes in labor productivity. Research and Development. This index attempts to measure what the Soviet Union defines as science expenditures. Unfortunately, Soviet data and defini- tions are not always clear and often conflict with other published data. The problem is greatly com- pounded by the belief that Soviet science is heavily oriented toward military objectives and by the fact that many different sources of finance exist. Thus, this index is subject to considerable error in its interpretation and growth rate. It is constructed as a weighted average of man-hour employment and other current expenditures. The employment component is based on Narkhoz employment data for science and estimated average annual hours of work. The other current expenditures component is based on data for 1960-72 from a Soviet monograph and the observa- tion that other current expenditures were a nearly constant share of total expenditures in that period. The resulting current-price expenditure data are de- flated by a price index made up mostly from Soviet wholesale price indexes and weighted by the structure of material expenditures in science. Outlays n.e.c. This final end-use component is the residual of total GNP, calculated from the sector-of- origin indexes, less the identified end-use components described above. This component includes a large portion of defense expenditures, net exports, inventory change, other unidentified outlays, and a statistical discrepancy. Sector-of-Origin Indexes Industry. The index of industrial production is a weighted average of 10 industrial branch indexes: (1) ferrous metals; (2) nonferrous metals; (3) fuel; (4) electric power; (5) machinery; (6) chemicals; (7) wood, pulp, and paper; (8) construction materials; (9) light industry; and (10) food industry. Each branch index is the sum of several subbranch indexes combined by value-added weights derived from the 1972 1-0 table in producers' prices. Each subbranch index measures the gross output of an I-0 sector by summing the physical production of several products, each multi- plied by a base-year price. We do not have an index for the 11th branch, "other branches of industry." We assume the index for this branch to be the same as that of total industrial production. The index of industrial production is explained in detail by Ray Converse in JEC, Industry. Construction. It would be desirable to measure con- struction activity by its gross output, but the only data available are a current-price gross output series and a constant-price series for the construction-installation component of investment (Soviet definition). The lat- ter excludes a significant part of the output of the construction sector (capital repair) and probably is not adequately deflated. For these reasons, we have con- structed an independent index. It is a weighted aver- age of material inputs. The structure of inputs is taken from the 1972 Soviet 1-0 table, and the growth 48 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 of the individual inputs is taken from the correspond- ing parts of the industrial production and other indexes. The material-input index is less desirable than a double deflation or gross output index, but apparently the best that can be had with the data available. Agriculture. The index of net agricultural production (gross production less intra-agricultural use) is de- scribed in detail by Margaret Hughes and Barbara Severin in JEC, Agriculture. It is derived as the sum of the physical production of 42 products multiplied by their average 1970 price, less the estimated quanti- ties of seed and feed used by agriculture itself. The value-added index is then derived by subtracting an index of material purchases from nonagricultural sectors. The weights for this index are based on the 1972 1-0 table. Transportation. This index is a weighted average of indexes of freight and passenger transportation. Deri- vation of the passenger transportation index is the same as the end-use transportation index, but without any deductions for business travel in the 1970 weights. The freight transportation index is a weight- ed average of rail, sea, inland-waterway, oil-pipeline, truck, air, and gas-pipeline freight transportation. The output of all of the components is measured in ton- kilometers, except that of gas pipelines which is measured in cubic meters of gas shipped. The weights are 1970 revenues per ton-kilometer or per cubic meter. Communications. The communications index is the same as the one described above as a part of consumption. Trade. The trade index is a weighted average of the three main activities of the domestic trade sector: (1) retail trade, (2) wholesale trade and material-technical supply, and (3) agricultural procurement. The retail trade index is an average of the consumption indexes for food (less income in kind), soft goods, and dura- bles. The wholesale trade index is a gross output weighted average of the indexes of all of the branches of industry except the electric power and other indus- try branches. The agricultural procurement index is a weighted average of state purchases of 16 types of 49 agricultural products. The weights are 1970 procure- ment prices. The three component indexes are com- bined with estimated 1970 value-added weights. Services. The service indexes on the sector-of-origin side of the accounts are the same as those described in the list of end-use indexes except that an index is added for the credit and insurance sector. Only this index and any differences from the end-use indexes are described here. The credit and insurance index represents employ- ment converted to hours worked. All of the reserva- tions about employment indexes apply to this index. Indeed, the credit and insurance index almost certain- ly fails to capture labor productivity growth that results from effective application of machine calcula- tors and computers. We have no evidence, however, on which we could estimate a productivity allowance. The sector-of-origin utilities index measures the value added by that part of the housing-communal economy sector that supplies water, gas, heat, and sewage services. The delivery of gas is measured by total gas production and the delivery of all other services is measured by the stock of urban housing. The education and health indexes for sector of origin use only the labor component of the end-use indexes. Military Personnel. This is an index of personnel costs in 1970 prices as estimated by the CIA. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix A Soviet Gross National Product, 1950-80 This appendix presents the main statistical results of this report. All data included here utilize the 1970 factor-cost weights. A similar set of data could be calculated using the 1970 established-price weights. The indexes for each sector (except military personnel) and their growth rates are the same in both types of prices. The ruble values, percentage shares of GNP, and the aggregate indexes are different in factor-cost prices than in established prices. Tables A-1 through A-5 contain data on Soviet GNP by sector of origin. Table A-1 shows the value added in each sector as measured in 1970 factor-cost rubles. These data are obtained by multiplying the base-year (1970) ruble values for each sector by its correspond- ing index. Total GNP and the subtotals for industry, services, and government administrative services are obtained by addition. Tables A-2 and A-3 show average annual growth rates for five-year periods and annual growth rates for each component. All of the growth rates are derived from the ruble data in table A-1. The percentage distribution of GNP by sector of origin is shown in table A-4. The percentage values are derived by dividing the ruble value for each component by the ruble value for total GNP. The sectoral indexes used to compute the ruble data are shown in table A-5. The indexes for total GNP and the subtotals are derived from the ruble data in table A-1. 51 Data on Soviet GNP by end use are shown in tables A-6 through A-12. The ruble values, average annual growth rates for five-year periods, and annual growth rates are shown in tables A-6 through A-8 and are derived in the same manner as the sector-of-origin data. The data for total GNP are taken directly from the sector-of-origin tables and the ruble values for outlays n.e.c. are obtained as the residual of total GNP less the sum of the other end-use components. The percentage distribution of GNP by end use and the sectoral indexes are shown in tables A-11 and A-12. Tables A-9 and A-10 contain data on per capita consumption, per capita GNP, and the population size. Table A-9 presents these data in rubles (the population data are in millions of people) and table A-10 has average annual growth rates for five-year periods. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 GNP by Sector of Origin Billion 1970 Rubles 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Industry 27.2 30.5 33.1 36.1 39.8 44.1 47.8 51.5 56.1 61.3 Ferrous metals 2.0 2.2 2.6 2.8 3.1 3.4 3.6 3.8 4.1 4.5 Nonferrous metals 0.9 1.0 1.2 1.3 1.4 1.7 1.8 1.9 2.0 2.1 Fuel 2.9 3.2 3.4 3.6 4.0 4.5 5.0 5.6 6.1 6.6 Electric power 1.0 1.2 1.3 1.5 1.7 1.9 2.2 2.4 2.7 3.0 Machinery 8.3 9.1 9.9 10.8 11.8 13.2 14.1 15.1 16.2 17.7 Chemicals 1.0 1.1 1.2 1.3 1.5 1.7 2.0 2.1 2.4 2.6 Wood, pulp, and paper 3.8 4.3 4.5 4.7 5.1 5.4 5.6 6.0 6.6 7.2 Construction materials 1.1 1.3 1.5 1.7 2.0 2.3 2.6 3.0 3.6 4.2 Light industry 2.7 3.2 3.4 3.7 4.2 4.4 4.7 4.9 5.3 5.7 Food industry 2.6 3.0 3.2 3.6 3.9 4.2 4.8 5.1 5.5 6.0 Other industry 0.8 0.9 1.0 1.0 1.2 1.3 1.4 1.5 1.6 1.8 Construction 5.7 6.5 7.2 7.9 8.8 10.0 10.9 12.1 13.7 15.3 Agriculture 40.8 37.6 39.5 41.9 42.7 48.4 55.5 54.7 59.3 60.5 Transportation 5.2 5.8 6.4 7.0 7.8 9.2 10.2 11.7 12.9 14.3 Communications 0.7 0.8 0.9 0.9 1.0 1.1 1.2 1.3 1.3 1.4 Trade 6.7 7.3 8.0 8.9 9.8 10.7 11.7 12.6 13.9 14.8 Services 39.4 40.3 41.3 41.9 42.6 43.3 44.2 45.3 47.4 49.4 Housing 13.3 13.7 14.1 14.4 14.9 15.3 15.9 16.6 17.5 18.5 Utilities 0.6 0.6 0.6 0.6 0.7 0.7 0.8 0.9 0.9 1.0 Repair and personal care 2.2 2.2 2.2 2.3 2.3 2.4 2.3 2.3 2.4 2.8 Recreation 1.3 1.4 1.4 1.5 1.6 1.9 1.9 2.0 2.1 2.2 Education 6.9 7.1 7.3 7.5 7.9 8.2 8.3 8.5 8.7 8.9 Health 3.4 3.5 3.6 3.8 4.0 4.3 4.4 4.6 4.8 5.1 Science 1.4 1.6 1.7 - 1.8 1.9 2.0 2.3 2.6 2.9 3.2 Credit and insurance 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.0 1.0 1.0 Government administrative services 9.3 9.3 9.3 8.9 8.3 7.4 7.2 6.9 7.0 6.8 General agricultural pro- grams 0.7 0.8 0.8 0.8 0.8 0.6 0.6 0.6 0.7 0.8 Forestry 0.7 0.7 0.7 0.6 0.6 0.6 0.6 0.5 0.5 0.5 State administration and the administrative or- gans of social organiza- tions 5.2 5.2 5.1 4.9 4.4 3.9 3.7 3.5 3.5 3.3 Culture 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.7 Municipal services 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.5 Civilian police 1.7 1.6 1.6 1.6 1.4 1.2 1.2 1.1 1.1 1.1 Military personnel 7.5 8.4 9.0 8.3 7.7 7.2 7.1 6.6 6.1 5.7 Other branches 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.6 0.6 Gross national product 133.6 137.7 145.8 153.4 160.7 174.5 189.1 196.2 211.2 223.4 52 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (Continued) GNP by Sector of Origin Billion 1970 Rubles 1966 1967 1968 1969 1960 1961 1962 1963 1964 1965 Industry 65.7 70.1 75.3 79.8 85.0 90.4 95.5 102.1 108.8 114.6 Ferrous metals 4.8 5.3 5.7 6.0 6.5 6.9 7.3 7.7 8.1 8.3 Nonferrous metals 2.3 2.5 2.7 3.0 3.1 3.4 3.7 4.0 4.3 4.6 Fuel 7.0 7.3 7.7 8.4 8.9 9.5 10.1 10.6 11.0 11.4 Electric power 3.3 3.7 4.2 4.6 5.2 5.7 6.1 6.6 7.2 7.7 Machinery 19.3 20.9 23.1 24.5 26.1 27.5 28.8 30.7 33.5 35.8 Chemicals 2.9 3.2 3.5 3.9 4.4 5.1 5.6 6.1 6.6 7.0 Wood, pulp, and paper 7.2 7.2 7.3 7.6 8.0 8.1 8.2 8.6 8.8 9.0 Construction materials 4.7 5.0 5.3 5.4 5.7 6.1 6.5 6.9 7.2 7.4 Light industry 6.1 6.3 6.5 6.6 6.8 6.9 7.4 8.0 8.7 9.2 Food industry 6.3 6.8 7.2 7.5 7.9 8.8 9.2 9.8 10.4 11.0 Other industry 1.9 2.0 2.2 2.3 2.5 2.6 2.8 3.0 3.2 3.3 Construction 16.5 17.4 18.2 18.9 19.9 21.1 22.1 23.8 25.0 26.0 Agriculture 59.3 63.4 61.5 48.7 64.4 68.1 70.8 69.7 74.0 70.8 Transportation 15.7 16.8 18.2 19.7 21.5 24.1 25.7 27.9 29.8 31.4 Communications 1.5 1.6 1.7 1.8 2.0 2.2 2.4 2.6 2.8 3.j Trade 15.8 16.5 17.4 18.1 18.8 20.0 21.6 23.1 24.9 26.2 Services 51.4 53.3 55.8 58.0 60.9 63.8 66.7 69.6 72.7 75.6 Housing 19.6 20.5 21.4 22.3 23.1 23.8 24.6 25.4 26.2 26.9 Utilities 1.1 1.2 1.3 1.4 1.6 1.7 1.8 1.9 2.0 2.1 Repair and personal care 2.7 2.4 2.4 2.5 2.7 3.0 3.3 3.6 3.9 4.2 Recreation 2.3 2.4 2.4 2.4 2.6 2.7 2.7 2.9 3.0 3.1 Education 9.1 9.5 10.2 10.7 11.4 12.1 12.7 13.2 13.7 14.1 Health 5.3 5.5 5.7 5.9 6.1 6.4 6.6 6.8 7.1 7.4 Science 3.7 4.1 4.6 4.9 5.3 5.6 6.0 6.3 6.7 7.2 Credit and insurance 1.0 1.0 1.0 1.0 1.0 1.1 1.1 1.2 1.2 1.3 Government administrative services 6.7 6.6 6.8 6.8 7.1 7.5 7.9 8.4 8.9 9.4 General agricultural pro- grams 0.9 0.8 0.8 0.8 0.8 0.9 0.9 1.0 1.1 1.1 Forestry 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 State administration and the administrative or- gans of social organiza- tions 3.1 3.1 3.2 3.1 3.3 3.5 3.7 3.9 1.0 4.1 4.3 Culture 0.7 0.7 0.8 0.8 0.9 0.9 1.0 1.2 1.3 Municipal services 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.7 0.7 0.7 Civilian police 1.0 1.0 1.0 1.0 1.0 1.1 1.2 1.3 1.3 1.4 Military personnel 5.6 5.5 5.7 5.9 6.1 6.3 6.4 6.6 6.9 7.2 Other branches 0.6 0.7 0.7 0.7 0.8 0.8 0.9 0.9 1.0 1.0 Gross national product 232.3 245.3 254.5 251.7 279.4 296.8 311.9 326.3 346.0 355.9 53 93-892 0 - 82 - 5 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (Continued) GNP by Sector of Origin Billion 1970 Rubles 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 Industry 122.6 130.0 136.6 144.5 153.9 163.4 169.8 176.5 182.6 188.0 193.4 Ferrous metals 8.8 9.1 9.4 9.8 10.2 10.7 11.0 11.0 11.3 11.3 11.3 Nonferrous metals 4.8 5.1 5.4 5.8 6.1 6.4 6.6 6.8 7.0 7.2 7.3 Fuel 12.1 12.7 13.3 13.9 14.6 15.4 16.0 16.7 17.2 17.7 18.1 Electric power 8.3 9.0 9.6 10.3 11.0 11.7 12.5 12.9 13.5 13.9 14.6 Machinery 38.5 41.7 44.5 48.3 52.4 56.4 59.5 62.9 66.4 70.1 73.2 Chemicals 7.8 8.4 8.9 9.7 10.7 11.7 12.3 12.9 13.4 13.4 14.1 Wood, pulp, and paper 9.4 9.7 9.8 10.1 10.3 10.7 10.7 10.7 10.7 10.3 10.6 Construction materials 8.0 8.5 9.0 9.5 10.0 10.4 10.8 11.0 11.2 11.3 11.4 Light industry 9.8 10.2 10.3 10.6 10.8 11.2 11.6 11.9 12.2 12.4 12.7 Food industry 11.6 11.9 12.3 12.4 13.4 14.1 13.9 14.5 14.3 14.8 14.6 Other industry 3.6 3.8 4.0 4.2 4.5 4.7 4.9 5.1 5.3 5.5 5.6 Construction 28.0 29.9 31.5 33.3 35.0 36.8 38.0 38.9 40.1 40.4 41.4 Agriculture 81.0 79.6 72.8 84.9 83.0 72.0 80.2 83.0 85.9 78.8 73.1 Transportation 33.4 35.7 37.6 40.3 43.2 45.8 47.8 48.8 51.1 52.3 54.3 Communications 3.3 3.6 3.8 4.1 4.4 4.7 5.0 5.3 5.6 5.9 6.2 Trade 28.0 29.4 30.3 31.9 33.5 35.1 36.3 37.6 38.9 39.8 40.7 Services 78.5 81.4 84.3 87.1 90.0 92.8 95.1 97.4 100.4 103.4 106.6 Housing 27.7 28.5 29.2 30.0 30.8 31.6 32.3 33.1 33.9 34.6 35.3 Utilities 2.2 2.3 2.4 2.5 2.6 2.8 3.0 3.1 3.2 3.4 3.6 Repair and personal care 4.6 4.8 5.2 5.5 5.9 6.2 6.6 6.9 7.4 7.9 8.4 Recreation 3.1 3.2 3.2 3.3 3.4 3.4 3.4 3.4 3.5 3.6 3.7 Education 14.5 15.0 15.3 15.6 15.9 16.3 16.6 16.9 17.3 17.7 18.3 Health 7.6 7.9 8.1 8.3 8.5 8.6 8.8 8.9 9.0 9.3 9.3 Science 7.8 8.3 8.9 9.5 9.9 10.4 10.6 10.9 11.2 11.7 12.2 Credit and insurance 1.4 1.5 1.6 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 Government administrative services 9.6 10.0 10.4 10.7 11.2 11.6 11.9 12.3 12.7 13.0 13.4 General agricultural programs 1.1 1.2 1.2 1.3 1.3 1.4 1.5 1.5 1.6 1.7 1.8 Forestry 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 State administration and the administrative organs of social organizations 4.4 4.6 4.7 4.9 5.1 5.3 5.4 5.5 5.6 5.8 5.9 Culture 1.4 1.5 1.5 1.6 1.7 1.7 1.8 1.9 2.0 2.0 2.1 Municipal services 0.8 0.8 0.9 0.9 0.9 1.0 1.0 1.0 1.1 1.1 1.1 Civilian police 1.4 1.5 1.5 1.6 1.6 1.7 1.7 1.8 1.8 1.8 1.9 Military personnel 7.4 7.6 7.7 7.8 7.9 8.0 8.1 8.1 8.2 8.2 8.3 Other branches 1.1 1.1 1.1 1.2 1.2 1.3 1.3 1.4 1.4 1.4 1.4 Gross national product 383.3 398.2 405.7 435.2 452.2 459.7 481.6 497.0 514.1 518.2 525.4 54 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 Percent Average Annual Rates of Growth of GNP by Sector of Origin 1971-75 1976-80 1951-55 1956-60 1961-65 1966-70 Industry 10.2 8.3 6.6 6.3 5.9 3.4 Ferrous metals 11.1 7.6 7.2 5.1 4.0 1.1 Nonferrous metals 12.8 6.9 7.6 7.4 5.9 2.6 Fuel 9.4 8.9 6.3 5.0 5.0 3.3 Electric power 13.1 11.4 11.5 7.9 7.0 4.5 Machinery 9.6 7.9 7.4 6.9 7.9 5.3 Chemicals 11.6 1().5 12.0 8.9 8.6 3.8 Wood, pulp, and paper 7.4 5.8 2.6 2.9 2.6 -0.1 Construction materials 15.7 14.7 5.4 5.7 5.4 1.8 Light industry 10.4 6.4 2.6 7.2 2.7 2.6 Food industry 10.2 8.4 6.8 5.9 3.9 0.7 Other industry 10.2 8.3 6.6 6.3 5.9 3.4 Construction 11.8 10.5 5.0 5.8 5.6 2.4 Agriculture 3.5 4.2 2.8 3.5 -2.3 0.3 Transportation 12.3 11.3 9.0 6.7 6.5 3.5 Communications 8.1 7.0 7.1 8.9 7.3 5.8 Trade 9.9 8.2 4.8 7.0 4.6 3.0 Services 1.9 3.5 4.4 4.2 3.4 2.8 Housing 2.9 5.0 4.0 3.1 2.7 2.2 Utilities 5.4 9.1 8.1 5.5 5.1 5.0 Repair and personal care 1.8 2.2 2.3 8.9 6.5 6.2 Recreation 7.5 4.0 3.5 2.8 1.9 1.4 Education 3.6 2.2 5.9 3.7 2.2 2.5 Health 5.0 4.4 3.8 3.6 2.6 1.6 Science 7.5 12.5 9.0 6.7 6.0 3.2 Credit and insurance -0.1 -:2.4 1.5 5.5 5.9 4.6 Government administrative services -4.5 -1.8 2.2 5.2 3.8 3.0 General agricultural programs -4.5 9.7 -1.3 4.8 4.8 5.4 Forestry -2.8 -4.0 1.3 1.7 0.9 0.3 State administration and the administrative organs of social organizations -6.0 -4.1 2.2 4.9 3.5 2.5 Culture 3.5 1.6 5.5 8.4 5.0 3.6 Municipal services 2.7 1.4 3.4 5.3 4.5 3.3 Civilian police -6.0 -4.1 2.2 4.9 3.5 2.5 Military personnel -0.8 -4.8 2.2 3.4 1.6 0.6 Other branches 5.5 5.9 5.0 5.2 3.7 2.7 Gross national product 5.5 5.9 5.0 5.2 3.7 2.7 55 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-3 Percent Annual Growth Rates of GNP by Sector of Origin 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 Industry 12.2 8.5 9.1 10.1 11.0 8.2 7.7 9.0 9.3 7.2 Ferrous metals 13.0 13.7 9.7 9.0 10.1 7.6 5.9 6.8 8.7 8.8 Nonferrous metals 13.3 12.5 11.5 9.4 17.4 6.0 5.6 5.6 8.1 9.0 Fuel 9.2 6.9 6.9 10.3 13.8 11.0 11.5 9.2 7.0 6.0 Electric power 13.8 14.4 12.8 11.8 12.7 12.7 9.5 12.3 12.4 10.2 Machinery 9.8 8.6 8.9 9.0 11.8 7.2 6.8 7.5 9.0 9.1 Chemicals 9.8 9.1 10.3 13.8 14.9 12.2 9.5 12.2 8.7 10.1 Wood, pulp, and paper 13.4 3.9 4.3 10.1 5.5 3.6 7.0 9.3 9.2 0.1 Construction materials 13.7 12.8 16.7 16.5 18.8 11.0 16.2 19.3 15.1 12.1 Light industry 17.5 6.4 9.5 11.8 7.1 5.9 4.6 8.0 7.6 5.7 Food industry 14.7 9.0 11.0 7.2 9.3 12.9 6.6 7.5 10.4 4.7 Other industry 12.2 8.5 9.1 10.1 11.0 8.2 7.7 9.0 9.3 7.2 Construction 14.1 10.4 10.3 11.3 13.2 8.8 10.9 13.1 12.3 7.6 Agriculture -8.0 5.1 6.0 2.0 13.3 14.7 -1.5 8.4 2.1 -2.0 Transportation 12.1 9.8 10.3 10.6 18.7 11.3 13.9 10.5 11.1 9.7 Communications 9.3 9.0 6.4 8.2 7.5 7.7 7.7 5.8 6.4 7.6 Trade 8.8 9.7 11.0 10.5 9.2 9.3 8.0 9.9 6.9 6.8 Services 2.4 2.4 1.4 1.7 1.5 2.2 2.3 4.7 4.3 4.0 Housing 2.6 2.7 2.7 2.9 3.2 3.5 4.3 5.3 5.9 5.8 Utilities 4.1 4.1 5.4 6.7 6.8 7.0 8.6 10.8 9.8 9.3 Repair and personal care 1.5 1.6 1.7 1.9 2.0 -2.2 -0.7 5.6 13.2 -3.8 Recreation 3.8 4.6 4.9 10.3 14.4 3.9 3.6 6.5 2.1 3.9 Education 3.4 3.3 2.5 4.6 4.1 1.4 1.9 2.5 2.2 2.8 Health 4.1 3.9 3.6 6.9 6.3 2.8 4.4 5.4 4.6 4.7 Science 9.9 8.2 5.0 5.8 9.0 13.2 10.8 13.3 10.9 14.4 Credit and insurance -0.7 -0.7 0.2 0.2 0.2 -2.1 -4.2 -1.1 -2.7 -1.9 Government administrative services 0 0 -3.8 -7.3 -10.9 -1.9 -4.6 1.2 -2.6 -1.2 General agricultural programs 8.4 7.5 -8.5 3.7 -27.9 9.0 -4.1 18.7 5.5 21.5 Forestry 1.7 1.7 -10.1 -3.5 -3.4 -2.2 -5.6 -3.3 -6.7 -1.9 State administration and the administrative or- gans of social organiza- tions -1.5 -1.5 -3.5 -10.7 -12.0 -3.8 -5.8 -0.7 -4.3 -5.9 Culture 3.4 3.2 2.5 4.5 4.0 1.0 1.5 2.5 1.3 1.7 Municipal services 3.9 3.7 2.1 2.0 1.9 2.6 0.9 1.2 0.7 1.8 Civilian police -1.5 -1.5 -3.5 -10.7 -12.0 -3.8 -5.8 -0.7 -4.3 -5.9 Military personnel 12.5 7.4 -8.0 -7.3 -6.8 -2.0 -5.9 -8.3 -6.9 -0.6 Other branches 3.1 5.9 5.2 4.7 8.6 8.4 3.8 7.6 5.8 4.0 Gross national product 3.1 5.9 5.2 4.7 8.6 8.4 3.8 7.6 5.8 4.0 56 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-3 (Continued) Annual Growth Rates of GNP by Sector of Origin Percent 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 Industry 6.7 7.4 6.0 6.4 6.5 5.6 6.9 6.5 5.4 7.0 Ferrous metals 8.5 7.7 6.2 7.3 6.4 6.2 5.7 4.6 3.5 5.5 Nonferrous metals 8.4 8.9 7.8 6.0 7.2 9.7 8.9 8.0 5.0 5.6 Fuel 4.9 5.8 8.4 6.5 5.9 6.4 5.2 3.5 4.4 5.5 Electric power 12.1 12.8 11.2 11.2 10.0 7.6 7.7 8.8 7.9 7.6 Machinery 8.5 10.2 6.4 6.4 5.5 4.5 6.7 9.0 6.9 7.7 Chemicals 9.9 10.5 10.8 13.7 14.9 10.0 10.0 7.2 6.1 11.3 Wood, pulp, and paper -0.1 2.4 4.2 4.5 2.0 0.5 5.0 2.4 1.8 4.9 Construction materials 7.4 5.1 2.8 4.8 6.9 7.2 7.1 3.9 2.0 8.5 Light industry 3.6 3.5 1.4 3.0 1.8 7.4 8.3 7.9 6.4 5.9 Food industry 7.3 6.2 4.2 5.3 11.2 4.5 7.4 5.6 5.7 6.0 Other industry 6.7 7.4 6.0 6.4 6.5 5.6 6.9 6.5 5.4 7.0 Construction 5.2 4.7 3.9 5.1 6.3 4.6 7.6 5.3 4.0 7.7 Agriculture 6.9 -3.0 -20.8 32.1 5.8 4.0 -1.6 6.3 -4.4 14.4 Transportation 7.2 8.0 8.3 9.3 12.0 6.4 8.7 6.9 5.1 6.6 Communications 5.9 6.2 5.9 7.1 10.4 10.5 10.3 7.2 8.7 7.5 Trade 3.9 5.8 4.1 3.9 6.1 7.9 7.4 7.4 5.4 7.0 Services 3.7 4.7 3.9 5.2 4.7 4.5 4.3 4.6 3.9 3.8 Housing 5.0 4.4 � 4.0 3.5 3.3 3.2 3.2 3.1 2.9 2.8 Utilities 9.2 8.4 8.0 7.7 7.2 6.1 5.7 5.2 5.0 5.4 Repair and personal care -8.2 -1.5 2.3 8.8 11.1 10.3 9.8 9.3 6.4 8.8 Recreation 3.6 2.3 0.9 7.3 3.8 0.7 6.1 4.3 1.3 1.7 Education 4.5 6.9 5.5 6.7 5.9 4.8 3.6 4.2 3.1 3.0 Health 4.0 3.8 2.9 4.0 4.4 3.8 2.8 4.6 3.9 3.0 Science 11.8 11.1 7.9 8.8 5.4 6.6 4.2 6.9 6.9 8.7 Credit and insurance 0 2.2 1.9 2.9 0.6 4.9 5.4 5.4 5.1 6.7 Government administrative services -1.1 2.0 0.4 4.2 5.5 5.5 7.0 5.7 5.1 2.7 General agricultural programs -9.7 -1.4 -1.4 3.7 2.9 5.9 9.4 7.5 1.5 -0.1 Forestry 0.7 2.9 2.3 1.8 -1.3 2.2 1.0 2.4 1.4 1.4 State administration and the administrative or- gans of social organiza- tions -0.5 1.6 -0.8 4.0 7.0 5.9 6.6 4.9 5.4 1.9 Culture 3.2 6.4 5.4 6.8 5.6 4.8 10.0 10.1 8.8 8.3 Municipal services 1.1 3.3 3.9 5.1 3.7 4.8 7.7 4.9 4.9 3.9 Civilian police -0.5 1.6 -0.8 4.0 7.0 5.9 6.6 4.9 5.4 1.9 Military personnel -2.2 4.1 3.6 3.2 2.2 1.9 3.8 4.8 4.3 2.1 Other branches 5.6 3.8 -1.1 11.0 6.3 5.1 4.6 6.0 2.9 7.7 Gross national product 5.6 3.8 -1.1 11.0 6.3 5.1 4.6 6.0 2.9 7.7 57 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-3 (Continued) Annual Growth Rates of GNP by Sector of Origin Percent 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 Industry 6.1 5.0 5.8 6.5 6.2 3.9 4.0 3.5 3.0 2.9 Ferrous metals 3.8 3.3 4.0 4.2 4.4 2.7 0.7 2.2 0.0 -0.3 Nonferrous metals 7.0 5.3 6.1 6.2 4.7 3.1 3.1 3.3 3.0 0.8 Fuel 4.8 4.7 4.9 4.9 5.9 3.7 4.2 3.1 3.0 2.3 Electric power 8.1 7.1 6.8 6.7 6.6 6.9 3.6 4.7 2.9 4.5 Machinery 8.1 6.9 8.3 8.5 7.7 5.5 5.6 5.6 5.6 4.3 Chemicals 8.1 6.7 9.0 9.5 9.7 4.8 5.2 3.6 0.2 5.2 Wood, pulp, and paper 2.8 2.0 2.7 1.8 3.6 -0.1 0.5 -0.5 -2.9 2.8 Construction materials 6.7 5.2 6.0 4.7 4.5 3.5 1.9 2.4 0.3 1.0 Light industry 4.5 0.7 2.8 2.7 2.9 4.2 2.5 2.6 1.8 2.0 Food industry 2.6 3.3 0.8 7.9 5.1 -1.1 4.0 -1.1 3.2 -1.4 Other industry 6.1 5.0 5.8 6.5 6.2 3.9 4.0 3.5 3.0 2.9 Construction 6.7 5.2 5.9 5.3 4.9 3.4 2.4 3.0 0.8 2.5 Agriculture -1.7 -8.5 16.7 -2.2 -13.3 11.4 3.5 3.5 -8.3 -7.3 Transportation 6.7 5.5 7.2 7.0 6.1 4.4 2.2 4.6 2.3 3.9 Communications 7.3 7.4 7.2 7.2 7.2 6.4 5.7 5.5 5.6 5.6 Trade 4.8 3.3 5.3 5.0 4.5 3.6 3.6 3.4 2.4 2.4 Services 3.7 3.5 3.3 3.3 3.1 2.5 2.5 3.1 3.0 3.1 Housing 2.7 2.7 2.7 2.6 2.6 2.4 2.3 2.3 2.1 2.1 Utilities 5.0 4.2 4.8 5.7 5.8 5.7 4.8 4.8 5.2 4.4 Repair and personal care 6.2 6.7 6.9 6.5 5.9 5.8 4.8 7.0 6.8 6.7 Recreation 2.7 1.4 2.1 1.9 1.3 -1.2 0.8 2.9 1.9 2.6 Education 2.9 2.3 1.8 2.2 2.0 1.9 1.7 2.9 2.1 3.6 Health 3.4 2.7 2.2 2.5 1.9 1.9 1.3 1.2 2.7 0.9 Science 6.7 7.4 6.8 4.4 4.9 1.4 2.6 3.5 4.3 4.3 Credit and insurance 6.6 6.6 5.2 6.3 5.1 5.2 4.9 5.2 4.6 2.8 Government administrative services 4.2 3.8 3.4 4.2 3.5 3.1 2.8 3.3 2.7 3.0 General agricultural programs 6.8 4.5 4.0 4.1 4.6 9.1 2.3 6.2 3.9 5.6 Forestry 0.4 2.3 -0.5 1.4 0.7 -0.9 0.4 1.3 0.0 0.4 State administration and the administrative or- gans of social organiza- tions 3.3 3.5 3.2 4.2 3.3 2.2 2.2 2.5 2.7 2.9 Culture 6.9 4.2 4.7 5.4 4.0 3.9 5.6 4.1 2.2 2.4 Municipal services 5.9 4.9 3.7 4.2 3.7 2.4 3.6 4.3 3.2 2.8 Civilian police 3.3 3.5 3.2 4.2 3.3 2.2 2.2 2.5 2.7 2.9 Military personnel 2.7 2.0 1.1 1.2 1.1 1.2 0.1 0.5 0.7 0.6 Other branches 3.9 1.9 7.3 3.9 1.7 4.8 3.2 3.4 0.8 1.4 Gross national product 3.9 1.9 7.3 3.9 1.7 4.8 3.2 3.4 0.8 1.4 58 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-4 Percentage Shares of GNP by Sector of Origin Percent 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Industry 20.4 22.2 22.7 23.5 24.7 25.3 25.3 26.2 26.6 27.4 Ferrous metals 1.5 1.6 1.8 1.8 1.9 1.9 1.9 2.0 1.9 2.0 Nonferrous metals 0.7 0.8 0.8 0.8 0.9 1.0 0.9 1.0 0.9 1.0 Fuel 2.2 2.3 2.3 2.4 2.5 2.6 2.7 2.9 2.9 2.9 Electric power 0.8 0.9 0.9 1.0 1.1 1.1 1.1 1.2 1.3 1.3 Machinery 6.2 6.6 6.8 7.1 7.3 7.6 7.5 7.7 7.7 7.9 Chemicals 0.8 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.1 1.2 Wood, pulp, and paper 2.8 3.1 3.1 3.0 3.2 3.1 3.0 3.1 3.1 3.2 Construction materials 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.7 1.9 Light industry 2.0 2.3 2.3 2.4 2.6 2.6 2.5 2.5 2.5 2.6 Food industry 1.9 2.2 2.2 2.3 2.4 2.4 2.5 2.6 2.6 2.7 Other industry 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.8 0.8 0.8 Construction 4.3 4.7 4.9 5.2 5.5 5.7 5.8 6.2 6.5 6.9 Agriculture 30.6 27.3 27.1 27.3 26.6 27.7 29.4 27.9 28.1 27.1 Transportation 3.9 4.2 4.4 4.6 4.8 5.3 5.4 5.9 6.1 6.4 Communications 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 Trade 5.0 5.3 5.5 5.8 6.1 6.1 6.2 6.4 6.6 6.6 Services 29.5 29.3 28.3 27.3 26.5 24.8 23.4 23.1 22.4 22.1 Housing 10.0 9.9 9.6 9.4 9.3 8.8 8.4 8.4 8.3 8.3 Utilities 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 Repair and personal care 1.6 1.6 1.5 1.5 1.4 1.4 1.2 1.2 1.2 1.2 Recreation 1.0 1.0 1.0 1.0 1.0 1.1 1.0 1.0 1.0 1.0 Education 5.1 5.2 5.0 4.9 4.9 4.7 4.4 4.3 4.1 4.0 Health 2.5 2.5 2.5 2.4 2.5 2.4 2.3 2.3 2.3 2.3 Science 1.1 1.1 1.2 1.2 1.2 1.2 1.2 1.3 1.4 1.4 Credit and insurance 0.8 0.8 0.8 0.7 0.7 0.6 0.6 0.5 0.5 0.4 Government administrative services 6.9 6.7 6.4 5.8 5.1 4.2 3.8 3.5 3.3 3.0 General agricultural programs 0.5 0.6 0.6 0.5 0.5 0.3 0.3 0.3 0.3 0.3 Forestry 0.5 0.5 0.5 0.4 0.4 0.3 0.3 0.3 0.2 0.2 State administration and the administrative or- gans of social organiza- tions 3.9 3.8 3.5 3.2 2.7 2.2 2.0 1.8 1.6 1.5 Culture 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 Municipal services 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 Civilian police 1.2 1.2 1.1 1.0 0.9 0.7 0.6 0.6 0.5 0.5 Military personnel 5.6 6.1 6.2 5.4 4.8 4.1 3.7 3.4 2.9 2.5 Other branches 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 59 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-4 (Continued) Percentage Shares of GNP by Sector of Origin Percent 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Industry 28.3 28.6 29.6 31.7 30.4 30.5 30.6 31.3 31.4 32.2 Ferrous metals 2.1 2.1 2.2 2.4 2.3 2.3 2.3 2.4 2.3 2.3 Nonferrous metals 1.0 1.0 1.1 1.2 1.1 1.1 1.2 1.2 1.3 1.3 Fuel 3.0 3.0 3.0 3.3 3.2 3.2 3.2 3.2 3.2 3.2 Electric power 1.4 1.5 1.6 1.8 1.8 1.9 2.0 2.0 2.1 2.2 Machinery 8.3 8.5 9.1 9.7 9.3 9.3 9.2 9.4 9.7 10.1 Chemicals 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 1.9 2.0 Wood, pulp, and paper 3.1 2.9 2.9 3.0 2.9 2.7 2.6 2.6 2.5 2.5 Construction materials 2.0 2.0 2.1 2.1 2.0 2.0 2.1 2.1 2.1 2.1 Light industry 2.6 2.6 2.6 2.6 2.4 2.3 2.4 2.5 2.5 2.6 Food industry 2.7 2.8 2.8 3.0 2.8 3.0 2.9 3.0 3.0 3.1 Other industry 0.8 0.8 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 Construction 7.1 7.1 7.1 7.5 7.1 7.1 7.1 7.3 7.2 7.3 Agriculture 25.5 25.9 24.2 19.4 23.0 22.9 22.7 21.4 21.4 19.9 Transportation 6.8 6.9 7.1 7.8 7.7 8.1 8.2 8.6 8.6 8.8 Communications 0.7 0.7 0.7 0.7 0.7 0.7 0.8 0.8 0.8 0.9 Trade 6.8 6.7 6.8 7.2 6.7 6.7 6.9 7.1 7.2 7.4 Services 22.1 21.7 21.9 23.0 21.8 21.5 21.4 21.3 21.0 21.2 Housing 8.4 8.4 8.4 8.9 8.3 8.0 7.9 7.8 7.6 7.6 Utilities 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.6 0.6 Repair and personal care 1.1 1.0 0.9 1.0 1.0 1.0 1.1 1.1 1.1 1.2 Recreation 1.0 1.0 0.9 1.0 0.9 0.9 0.9 0.9 0.9 0.9 Education 3.9 3.9 4.0 4.3 4.1 4.1 4.1 4.0 4.0 4.0 Health 2.3 2.2 2.2 2.3 2.2 2.1 2.1 2.1 2.1 2.1 Science 1.6 1.7 1.8 2.0 1.9 1.9 1.9 1.9 1.9 2.0 Credit and insurance 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Government administrative services 2.9 2.7 2.7 2.7 2.5 2.5 2.5 2.6 2.6 2.6 General agricultural programs 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Forestry 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 State administration and the administrative or- gans of social organiza- tions 1.3 1.3 1.2 1.2 1.2 1.2 1.2 1.2 1.2 1.2 Culture 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 Municipal services 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Civilian police 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Military personnel 2.4 2.2 2.3 2.4 2.2 2.1 2.0 2.0 2.0 2.0 Other branches 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 60 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-4 (Continued) Percentage Shares of GNP by Sector of Origin Percent 1977 1978 1979 1980 1970 1971 1972 1973 1974 1975 1976 Industry 32.0 32.7 33.7 33.2 34.0 35.5 35.2 35.5 35.5 36.3 36.8 Ferrous metals 2.3 2.3 2.3 2.3 2.3 2.3 2.3 2.2 2.2 2.2 2.1 Nonferrous metals 1.3 1.3 1.3 1.3 1.4 1.4 1.4 1.4 1.4 1.4 1.4 Fuel 3.1 3.2 3.3 3.2 3.2 3.4 3.3 3.4 3.3 3.4 3.4 Electric power 2.2 2.3 2.4 2.4 2.4 2.5 2.6 2.6 2.6 2.7 2.8 Machinery 10.1 10.5 11.0 11.1 11.6 12.3 12.4 12.7 12.9 13.5 13.9 Chemicals 2.0 2.1 2.2 2.2 2.4 2.5 2.5 2.6 2.6 2.6 2.7 Wood, pulp, and paper 2.4 2.4 2.4 2.3 2.3 2.3 2.2 2.2 2.1 2.0 2.0 Construction materials 2.1 2.1 2.2 2.2 2.2 2.3 2.2 2.2 2.2 2.2 2.2 Light industry 2.5 2.6 2.5 2.4 2.4 2.4 2.4 2.4 2.4 2.4 2.4 Food industry 3.0 3.0 3.0 2.9 3.0 3.1 2.9 2.9 2.8 2.9 2.8 Other industry 0.9 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.1 1.1 Construction 7.3 7.5 7.8 7.6 7.7 8.0 7.9 7.8 7.8 7.8 7.9 Agriculture 21.1 20.0 17.9 19.5 18.4 15.7 16.7 16.7 16.7 15.2 13.9 Transportation 8.7 9.0 9.3 9.3 9.5 10.0 9.9 9.8 9.9 10.1 10.3 Communications 0.9 0.9 0.9 0.9 1.0 1.0 1.0 1.1 1.1 1.1 1.2 Trade 7.3 7.4 7.5 7.3 7.4 7.6 7.5 7.6 7.6 7.7 7.7 Services 20.5 20.4 20.8 20.0 19.9 20.2 19.7 19.6 19.5 20.0 20.3 Housing 7.2 7.1 7.2 6.9 6.8 6.9 6.7 6.7 6.6 6.7 6.7 Utilities 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.7 0.7 Repair and personal care 1.2 1.2 1.3 1.3 1.3 1.4 1.4 1.4 1.4 1.5 1.6 Recreation 0.8 0.8 0.8 0.8 0.7 0.7 0.7 0.7 0.7 0.7 0.7 Education 3.8 3.8 3.8 3.6 3.5 3.5 3.4 3.4 3.4 3.4 3.5 Health 2.0 2.0 2.0 1.9 1.9 1.9 1.8 1.8 1.8 1.8 1.8 Science 2.0 2.1 2.2 2.2 2.2 2.3 2.2 2.2 2.2 2.3 2.3 Credit and insurance 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Government administrative services 2.5 2.5 2.6 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.6 General agricultural programs 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Forestry 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 State administration and the administrative organs of social organizations 1.2 1.1 1.2 1.1 1.1 1.1 1.1 1.1 1.1 1.1 1.1 Culture 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Municipal services 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Civilian police 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.3 0.4 0.4 Military personnel 1.9 1.9 1.9 1.8 1.8 1.7 1.7 1.6 1.6 1.6 1.6 Other branches 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 61 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-5 Indexes of GNP by Sector of Origin 1958 1970 = 1959 1950 1951 1952 1953 1954 1955 1956 1957 Industry 22.2 24.9 27.0 29.5 32.4 36.0 38.9 42.0 45.7 50.0 Ferrous metals 22.6 25.6 29.1 31.9 34.8 38.3 41.2 43.7 46.6 50.7 Nonferrous metals 19.0 21.5 24.2 27.0 29.6 34.7 36.8 38.9 41.0 44.4 Fuel 24.0 26.3 28.1 30.0 33.1 37.6 41.8 46.6 50.9 54.5 Electric power 12.5 14.2 16.2 18.3 20.5 23.1 26.0 28.5 32.0 36.0 Machinery 21.6 23.7 25.8 28.1 30.6 34.2 36.7 39.2 42.1 45.9 Chemicals 13.0 14.3 15.6 17.2 19.6 22.5 25.3 27.7 31.0 33.7 Wood, pulp, and paper 40.4 45.8 47.6 49.6 54.7 57.6 59.7 63.9 69.9 76.3 Construction materials 14.2 16.1 18.2 21.2 24.7 29.4 32.6 37.9 45.2 52.0 Light industry 27.8 32.7 34.7 38.1 42.6 45.6 48.3 50.5 54.5 58.7 Food industry 22.3 25.5 27.9 30.9 33.1 36.2 40.9 43.5 46.8 51.7 Other industry 22.2 24.9 27.0 29.5 32.4 36.0 38.9 42.0 45.7 50.0 Construction 20.4 23.3 25.7 28.3 31.5 35.7 38.9 43.1 48.7 54.7 Agriculture 50.4 46.4 48.8 51.7 52.8 59.8 68.6 67.6 73.2 74.7 Transportation 15.5 17.3 19.0 21.0 23.2 27.6 30.7 34.9 38.6 42.9 Communications 22.4 24.5 26.7 28.4 30.8 33.1 35.6 38.4 40.6 43.2 Trade 23.9 26.0 28.5 31.6 34.9 38.2 41.7 45.1 49.5 52.9 Services 50.2 51.4 52.7 53.4 54.3 55.1 56.4 57.7 60.4 62.9 Housing 48.1 49.4 50.7 52.1 53.6 55.4 57.3 59.8 63.0 66.7 Utilities 25.9 26.9 28.0 29.6 31.5 33.7 36.0 39.1 43.4 47.6 Repair and personal care 47.8 48.6 49.3 50.2 51.1 52.2 51.0 50.7 53.5 60.6 Recreation 41.9 43.5 45.5 47.8 52.7 60.3 62.6 64.9 69.1 70.5 Education 47.2 48.8 50.4 51.7 54.0 56.2 57.0 58.1 59.5 60.8 Health 44.0 45.8 47.6 49.3 52.7 56.0 57.6 60.2 63.4 66.4 Science 18.2 20.0 21.6 22.7 24.0 26.2 29.6 32.8 37.2 41.3 Credit and insurance 80.8 80.3 79.8 79.9 80.1 80.3 78.6 75.3 74.5 72.4 Government administrative services 96.4 96.4 96.4 92.7 86.0 76.6 75.1 71.7 72.6 70.7 General agricultural pro- grams 66.7 72.3 77.7 71.1 73.7 53.1 57.9 55.5 65.9 69.5 Forestry 121.8 123.9 126.0 113.3 109.3 105.6 103.2 97.4 94.2 87.9 State administration and the administrative or- gans of social organiza- tions 118.3 116.6 114.8 110.7 98.9 87.0 83.7 78.8 78.2 74.9 Culture 39.9 41.2 42.5 43.6 45.5 47.3 47.8 48.5 49.7 50.4 Municipal services 53.4 55.4 57.5 58.7 59.8 60.9 62.5 63.1 63.9 64.3 Civilian police 118.3 116.6 114.8 110.7 98.9 87.0 83.7 78.8 78.2 74.9 Military personnel 101.4 114.0 122.5 112.7 104.4 97.3 95.4 89.8 82.3 76.5 Other branches 34.9 35.9 38.0 40.0 41.9 45.5 49.3 51.2 55.1 58.3 Gross national product 34.9 35.9 38.0 40.0 41.9 45.5 49.3 51.2 55.1 58.3 62 100 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-5 (Continued) Indexes of GNP by Sector of Origin 1966 1967 1968 1970 = 1969 1960 1961 1962 1963 1964 1965 Industry 53.6 57.2 61.4 65.1 69.3 73.8 77.9 83.3 88.7 93.5 Ferrous metals 55.1 59.8 64.4 68.4 73.4 78.1 82.9 87.6 91.6 94.8 Nonferrous metals 48.4 52.4 57.1 61.5 65.2 69.9 76.7 83.5 90.2 94.7 Fuel 57.7 60.6 64.1 69.4 73.9 78.3 83.3 87.7 90.8 94.8 Electric power 39.7 44.5 50.2 55.8 62.0 68.3 73.5 79.1 86.1 92.9 Machinery 50.1 54.3 59.8 63.7 67.7 71.5 74.7 79.7 86.9 92.9 Chemicals 37.1 40.8 45.1 50.0 56.8 65.3 71.8 79.0 84.7 89.8 Wood, pulp, and paper 76.4 76.3 78.1 81.4 85.1 86.8 87.2 91.5 93.7 95.4 Construction materials 58.3 62.6 65.8 67.6 70.9 75.8 81.2 87.0 90.4 92.2 Light industry 62.1 64.3 66.6 67.5 69.5 70.7 76.0 82.3 88.8 94.4 Food industry 54.1 58.1 61.7 64.3 67.7 75.3 78.6 84.4 89.2 94.3 Other industry 53.6 57.2 61.4 65.1 69.3 73.8 77.9 83.3 88.7 93.5 Construction 58.9 62.0 64.9 67.4 70.9 75.3 78.8 84.8 89.3 92.8 Agriculture 73.3 78.3 75.9 60.2 79.5 84.1 87.4 86.0 91.4 87.4 Transportation 47.0 50.4 54.4 59.0 64.4 72.2 76.9 83.6 89.3 93.8 Communications 46.5 49.2 52.3 55.3 59.3 65.4 72.3 79.8 85.5 93.0 Trade 56.5 58.7 62.2 64.7 67.2 71.3 76.9 82.6 88.7 93.5 Services 65.5 67.9 71.1 73.9 77.7 81.3 85.0 88.6 92.7 96.3 Housing 70.6 74.1 77.4 80.5 83.3 86.0 88.8 91.6 94.5 97.3 Utilities 52.0 56.8 61.5 66.4 71.5 76.6 81.3 85.9 90.4 94.9 Repair and personal care 58.3 53.5 52.7 54.0 58.7 65.3 72.0 79.0 86.4 91.9 Recreation 73.2 75.8 77.6 78.3 84.0 87.2 87.8 93.1 97.1 98.3 Education 62.5 65.3 69.9 73.7 78.7 83.3 87.3 90.4 94.2 97.1 97.1 Health 69.4 72.2 75.0 77.2 80.3 83.8 86.9 89.4 93.4 Science 47.2 52.7 58.6 63.2 68.7 72.4 77.3 80.5 86.0 92.0 Credit and insurance 71.0 71.0 72.6 74.0 76.1 76.6 80.3 84.6 89.2 93.8 Government administrative services 69.8 69.0 70.4 70.7 73.7 77.7 81.9 87.7 92.7 97.4 General agricultural pro- grams 84.5 76.4 75.3 74.2 77.0 79.2 83.9 91.7 98.6 100.1 Forestry 86.2 86.9 89.4 91.5 93.1 91.9 94.0 94.9 97.2 98.6 State administration and the administrative or- gans of social organiza- tions 70.5 70.1 71.2 70.7 73.5 78.6 83.3 88.8 93.1 98.1 92.4 Culture 51.3 52.9 56.3 59.3 63.4 66.9 70.1 77.1 84.9 Municipal services 65.4 66.2 68.3 71.0 74.6 77.4 81.1 87.4 91.7 96.2 Civilian police 70.5 70.1 71.2 70.7 73.5 78.6 83.3 88.8 93.1 98.1 Military personnel 76.1 74.4 77.5 80.3 82.9 84.8 86.4 89.6 93.9 98.0 Other branches 60.6 64.0 66.4 65.7 72.9 77.4 81.4 85.1 90.3 92.9 Gross national product 60.6 64.0 66.4 65.7 72.9 77.4 81.4 85.1 90.3 92.9 63 100 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-5 (Continued) 1970= 100 Indexes of GNP by Sector of Origin 1978 1979 1980 1970 1971 1972 1973 1974 1975 1976 1977 Industry 100.0 106.1 111.4 117.9 125.5 133.2 138.4 143.9 148.9 153.4 157.8 Ferrous metals 100.0 103.8 107.3 111.6 116.3 121.5 124.7 125.6 128.4 128.4 128.0 Nonferrous metals 100.0 107.0 112.7 119.6 126.9 132.9 137.1 141.3 145.9 150.2 151.4 Fuel 100.0 104.8 109.8 115.1 120.7 127.8 132.5 138.1 142.5 146.7 150.1 Electric power 100.0 108.1 115.8 123.6 131.9 140.6 150.3 155.7 162.9 167.7 175.3 Machinery 100.0 108.1 115.6 125.3 136.0 146.4 154.5 163.2 172.4 182.0 190.0 Chemicals 100.0 108.1 115.3 125.7 137.7 151.0 158.3 166.6 172.5 172.9 181.9 Wood, pulp, and paper 100.0 102.8 104.8 107.7 109.6 113.6 113.4 114.0 113.4 110.2 113.2 Construction materials 100.0 106.7 112.3 119.0 124.6 130.2 134.8 137.4 140.7 141.2 142.6 Light industry 100.0 104.5 105.3 108.2 111.1 114.3 119.0 122.1 125.2 127.4 130.0 Food industry 100.0 102.6 105.9 106.7 115.2 121.1 119.7 124.5 123.2 127.2 125.4 Other industry 100.0 106.1 111.4 117.9 125.5 133.2 138.4 143.9 148.9 153.4 157.8 Construction 100.0 106.7 112.2 118.8 125.0 131.2 135.6 138.9 143.0 144.1 147.7 Agriculture 100.0 98.3 89.9 104.8 102.5 88.9 99.1 102.5 106.1 97.3 90.2 Transportation 100.0 106.7 112.6 120.7 129.2 137.0 143.0 146.2 152.9 156.5 162.5 Communications 100.0 107.3 115.2 123.5 132.4 142.0 151.1 159.6 168.4 177.9 187.9 Trade 100.0 104.8 108.3 114.0 119.7 125.1 129.6 134.2 138.7 142.0 145.3 Services 100.0 103.7 107.4 111.0 114.7 118.2 121.2 124.2 127.9 131.8 135.8 Housing 100.0 102.7 105.5 108.4 111.2 114.1 116.8 119.5 122.2 124.8 127.4 Utilities 100.0 105.0 109.4 114.7 121.3 128.3 135.7 142.2 149.0 156.7 163.6 Repair and personal care 100.0 106.2 113.4 121.2 129.1 136.7 144.6 151.6 162.2 173.2 184.9 Recreation 100.0 102.7 104.2 106.4 108.4 109.8 108.5 109.4 112.6 114.7 117.6 Education 100.0 102.9 105.2 107.1 109.5 111.7 113.8 115.8 119.2 121.7 126.1 Health 100.0 103.4 106.2 108.5 111.3 113.4 115.6 117.1 118.5 121.7 122.8 Science 100.0 106.7 114.6 122.4 127.8 134.1 136.1 139.6 144.5 150.7 157.2 Credit and insurance 100.0 106.6 113.6 119.5 127.0 133.5 140.4 147.3 155.0 162.2 166.8 Government administrative services 100.0 104.2 108.2 111.8 116.5 120.6 124.3 127.7 132.0 135.5 139.6 General agricultural pro- grams 100.0 106.8 111.6 116.1 120.8 126.5 138.0 141.1 149.9 155.7 164.4 Forestry 100.0 100.4 102.7 102.2 103.7 104.4 103.5 103.9 105.3 105.3 105.8 State administration and the administrative or- gans of social organiza- tions 100.0 103.3 107.0 110.4 115.0 118.8 121.3 124.0 127.2 130.6 134.3 Culture 100.0 106.9 111.5 116.7 123.0 127.9 132.8 140.3 146.1 149.2 152.9 Municipal services 100.0 105.9 111.1 115.2 120.0 124.4 127.4 132.0 137.6 141.9 146.0 Civilian police 100.0 103.3 107.0 110.4 115.0 118.8 121.3 124.0 127.2 130.6 134.3 Military personnel 100.0 102.7 104.7 105.9 107.2 108.4 109.7 109.9 110.4 111.2 111.8 Other branches 100.0 103.9 105.9 113.6 118.0 120.0 125.7 129.7 134.1 135.2 137.1 Gross national product 100.0 103.9 105.9 113.6 118.0 120.0 125.7 129.7 134.1 135.2 137.1 64 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-6 Billion 1970 Rubles GNP by End Use 1958 1959 1950 1951 1952 1953 1954 1955 1956 1957 Consumption 80.1 80.6 85.5 91.1 96.2 101.6 106.4 113.7 121.7 127.2 Consumer goods 50.3 49.9 53.6 58.1 61.6 65.1 68.6 74.3 80.2 83.3 Food 42.9 41.5 44.7 47.9 49.5 52.3 54.7 59.1 63.7 65.6 Animal products 21.3 21.6 22.2 23.4 24.6 25.3 27.5 30.2 34.3 35.8 Processed foods 2.7 3.5 3.9 4.7 3.9 4.8 5.2 5.4 5.6 5.9 Basic foods 17.0 14.2 16.1 17.1 17.9 18.7 18.4 19.5 19.6 19.8 Beverages 1.9 2.2 2.4 2.7 3.1 3.4 3.6 4.0 4.2 4.2 Soft goods 6.3 7.2 7.6 8.4 9.8 10.3 11.2 11.9 12.8 13.7 Durables 1.0 1.2 1.4 1.8 2.3 2.5 2.7 3.3 3.6 3.9 Consumer services 29.8 30.7 31.8 33.0 34.6 36.5 37.8 39.4 41.6 44.0 Housing 13.0 13.3 13.7 14.0 14.5 14.9 15.5 16.1 17.0 18.0 Utilities 0.9 1.0 1.0 1.1 1.2 1.2 1.3 1.4 1.5 1.6 Transportation 0.9 1.0 1.1 1.2 1.4 1.6 1.7 2.0 2.2 2.4 Communications 0.4 0.5 0.5 0.5 0.6 0.6 0.7 0.7 0.8 0.8 Repair and personal care 1.9 2.0 2.0 2.0 2.1 2.1 2.1 2.1 2.2 2.5 Recreation 1.4 1.5 1.6 1.6 1.8 2.1 2.2 2.3 2.5 2.6 Education 7.4 7.5 7.8 8.0 8.3 8.7 8.9 9.2 9.4 9.7 Health 3.9 4.0 4.1 4.4 4.8 5.2 5.4 5.7 6.0 6.4 Investment 19.0 22.6 22.7 26.2 28.1 34.1 38.8 43.3 48.1 53.4 New fixed investment 16.1 19.4 19.2 22.3 23.9 28.9 32.6 36.3 40.1 44.0 Machinery and equipment 3.5 3.5 3.8 4.0 4.7 5.8 7.3 8.0 9.0 9.8 Construction and other capital outlays 12.3 14.2 15.9 17.4 19.3 21.4 22.7 24.8 28.0 31.6 Net additions to livestock 0.3 1.7 -0.5 0.9 -0.2 1.7 2.6 3.5 3.1 2.7 Capital repair 2.9 3.2 3.5 3.9 4.3 5.2 6.2 7.1 7.9 9.3 Other government expenditures 34.5 34.5 37.7 36.1 36.3 38.8 43.9 39.2 41.4 42.8 Government administrative services 10.4 10.4 10.4 10.0 9.3 8.3 8.1 7.7 7.8 7.6 General agricultural pro- grams 0.7 0.7 0.8 0.7 0.8 0.5 0.6 0.6 0.7 0.7 Forestry 0.8 0.8 0.8 0.7 0.7 0.7 0.7 0.6 0.6 0.6 State administration and the administrative or- gans of social organiza- tions 6.0 5.9 5.8 5.6 5.0 4.4 4.2 4.0 4.0 3.8 Culture 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.8 0.8 0.8 Municipal services 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 Civilian police 1.9 1.8 1.8 1.7 1.6 1.4 1.3 1.2 1.2 1.2 Research and development 2.2 2.4 2.6 2.7 2.9 3.1 3.6 3.9 4.5 5.0 Outlays n.e.c. 21.9 21.6 24.7 23.3 24.2 27.4 32.3 27.5 29.1 30.2 Gross national product 133.6 137.7 145.8 153.4 160.7 174.5 189.1 196.2 211.2 223.4 65 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-6 (Continued) GNP by End Use 1966 1967 Billion 1970 Rubles 1968 1969 1960 1961 1962 1963 1964 1965 Consumption 133.9 137.8 143.3 150.0 152.1 160.3 169.0 178.8 189.5 198.6 Consumer goods 87.5 89.1 92.0 96.2 95.3 100.5 106.4 113.2 120.8 127.0 Food 68.3 69.3 71.5 75.6 73.7 77.2 80.9 85.4 90.4 94.3 Animal products 37.8 38.1 38.9 42.8 39.1 41.2 44.4 47.2 50.5 53.1 Processed foods 6.4 6.7 7.1 7.4 8.1 8.4 8.5 9.0 9.4 9.9 Basic foods 19.8 19.9 20.4 19.9 20.7 21.3 21.3 21.9 22.6 22.4 Beverages 4.4 4.7 5.1 5.5 5.8 6.2 6.7 7.3 7.9 8.9 Soft goods 14.8 15.3 15.8 15.9 16.4 17.5 19.0 20.7 22.5 24.2 Durables 4.5 4.5 4.8 4.8 5.2 5.8 6.5 7.1 7.8 8.5 Consumer services 46.4 48.6 51.2 53.8 56.8 59.8 62.7 65.6 68.8 71.6 Housing 19.0 20.0 20.9 21.7 22.5 23.2 23.9 24.7 25.5 26.2 Utilities 1.7 1.8 2.0 2.2 2.4 2.6 2.8 3.0 3.2 3.4 Transportation 2.7 2.9 3.3 3.6 3.9 4.3 4.8 5.3 5.8 6.2 Communications 0.9 1.0 1.0 1.1 1.1 1.3 1.4 1.5 1.7 1.8 Repair and personal care 2.5 2.3 2.3 2.4 2.6 2.9 3.2 3.5 3.9 4.2 Recreation 2.7 2.8 2.9 2.9 3.1 3.2 3.3 3.5 3.6 3.6 Education 10.2 10.8 11.7 12.6 13.4 14.2 14.9 15.5 16.2 16.8 Health 6.8 7.0 7.1 7.4 7.7 8.1 8.4 8.6 9.0 9.4 Investment 56.2 62.5 65.1 60.0 74.0 80.9 81.6 84.7 90.2 96.0 New fixed investment 46.4 51.9 53.5 46.8 59.7 65.7 66.0 68.7 73.3 78.5 Machinery and equipment 10.8 11.8 13.2 14.6 16.6 17.8 18.8 20.2 21.8 22.8 Construction and other capital outlays 34.1 35.6 37.4 38.8 40.5 43.6 45.4 49.6 52.3 54.9 Net additions to livestock 1.5 4.5 2.9 -6.6 2.6 4.3 1.7 -1.1 -0.8 0.8 Capital repair 9.8 10.6 11.6 13.2 14.4 15.2 15.7 16.0 16.9 17.6 Other government expenditures 42.1 45.0 46.2 41.6 53.2 55.6 61.2 62.8 66.2 61.2 Government administrative services 7.5 7.4 7.6 7.6 7.9 8.4 8.8 9.4 10.0 10.5 General agricultural pro- grams 0.9 0.8 0.8 0.8 0.8 0.8 0.9 0.9 1.0 1.0 Forestry 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 State administration and the administrative or- gans of social organiza- tions 3.6 3.6 3.6 3.6 3.7 4.0 4.2 4.5 4.7 5.0 Culture 0.8 0.8 0.9 0.9 1.0 1.0 1.1 1.2 1.3 1.4 Municipal services 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.8 0.8 0.8 Civilian police 1.1 1.1 1.1 1.1 1.2 1.2 1.3 1.4 1.5 1.5 Research and development 5.7 6.3 7.0 7.6 8.3 8.7 9.3 9.7 10.3 11.0 Outlays n.e.c. 29.0 31.2 31.6 26.5 37.0 38.5 43.1 43.7 45.9 39.7 Gross national product 232.3 245.3 254.5 251.7 279.4 296.8 311.9 326.3 346.0 355.9 66 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-6 (Continued) Billion 1970 Rubles GNP by End Use 1970 1971 1976 1977 1978 1979 1980 1972 1973 1974 1975 Consumption 207.8 215.3 220.4 229.5 238.1 247.5 253.0 260.4 268.0 275.5 281.8 Consumer goods 133.1 138.0 140.6 146.9 152.4 158.7 161.6 166.8 171.2 175.8 179.2 Food 97.8 100.1 100.3 104.7 108.0 111.3 111.6 114.2 116.8 119.1 119.4 Animal products 54.7 55.8 56.8 59.7 62.0 64.7 64.6 65.4 66.7 68.4 68.5 Processed foods 10.3 10.5 10.7 11.3 11.7 11.7 12.3 12.7 13.2 13.4 13.6 Basic foods 23.5 24.3 23.4 24.3 24.1 24.2 23.7 25.0 25.4 25.2 24.7 Beverages 9.3 9.5 9.5 9.3 10.2 10.7 11.0 11.0 11.6 12.1 12.6 Soft goods 25.9 27.1 27.9 28.8 29.8 31.5 33.0 34.1 35.0 36.5 38.3 Durables 9.4 10.7 12.4 13.4 14.5 16.0 17.0 18.6 19.4 20.2 21.5 Consumer services 74.6 77.3 79.8 82.5 85.7 88.7 91.5 93.6 96.8 99.7 102.6 Housing 27.0 27.7 28.4 29.2 30.0 30.7 31.5 32.2 32.9 33.6 34.3 Utilities 3.6 3.9 4.2 4.4 4.7 4.9 5.2 5.5 5.7 5.9 6.2 Transportation 6.7 7.1 7.6 8.1 8.7 9.4 9.9 9.9 10.3 10.7 11.2 Communications 1.9 2.1 2.2 2.4 2.6 2.7 2.9 3.1 3.3 3.4 3.6 Repair and personal care 4.6 4.9 5./ 5.6 5.9 6.3 6.7 7.0 7.5 8.0 8.6 Recreation 3.7 3.8 3.8 3.9 3 9 4.0 3.9 3.9 4.0 4.1 4.2 Education 17.2 17.7 18.0 18.4 18.9 19.4 19.9 20.4 21.0 21.4 22.0 Health 9.9 10.2 10.4 10.6 10.9 11.2 11.4 11.7 12.0 12.3 12.4 Investment 108.2 113.4 118.2 129.1 137.6 140.6 151.8 159.5 165.5 168.3 173.3 New fixed investment 89.7 92.8 95.7 103.5 109.9 113.3 121.9 127.3 131.3 133.1 136.6 Machinery and equipment 25.6 27.0 29.2 31.4 346 39.0 42.8 45.2 49.0 51.1 53.5 Construction and other capital outlays 59.6 63.4 66.6 70.1 73.3 76.4 78.3 79.2 80.8 81.3 83.0 Net additions to livestock 4.4 2.4 -0.1 2.0 2.0 -2.1 0.8 2.8 1.5 0.7 0.1 Capital repair 18.5 20.6 22.5 25.6 27,7 27.2 29.9 32.3 34.2 35.2 36.7 Other government expenditures 67.3 69.4 67.1 76.7 76.6 71.7 76.8 77.1 80.7 74.4 70.3 Government administrative services 10.7 11.2 11.6 12.0 12.5 12.9 13.3 13.7 14.1 14.5 14.9 General agricultural pro- grams 1.0 1.1 1.1 1.2 1.2 1.3 1.4 1.4 1.5 1.6 1.7 Forestry 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 State administration and the administrative or- gans of social organiza- tions 5.1 5.2 5.4 5.6 5.8 6.0 6.2 6.3 6.4 6.6 6.8 Culture 1.5 1.7 1.7 1.8 1.9 2.0 2.1 2.2 2.3 1.2 2.3 1.2 2.4 1.3 Municipal services 0.9 0.9 1.0 1.0 1.1 1.1 1.1 1.2 Civilian police 1.6 1.6 1.7 1.7 1.8 1.9 1.9 1.9 2.0 2.1 18.1 41.7 518.2 2.1 18.9 36.4 525.4 Research and development 12.0 12.8 13.8 14.7 15.4 16.1 16.3 16.8 17.4 Outlays n.e.c. 44.5 45.4 41.7 49.9 48.7 42.7 47.1 46.6 49.2 Gross national product 383.3 398.2 405.7 435.2 452.2 459.7 481.6 497.0 514.1 67 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-7 Percent Average Annual Rates of Growth of GNP by End Use 1971-75 1976-80 1951-55 1956-60 1961-65 1966-70 Consumption 4.9 5.7 3.7 5.3 3.6 2.6 Consumer goods 5.3 6.1 2.8 5.8 3.6 2.5 Food 4.0 5.5 2.5 4.8 2.6 1.4 Animal products 3.6 8.3 1.8 5.8 3.4 1.1 Processed foods 12.3 5.9 5.8 4.1 2.7 2.9 Basic foods 1.9 1.1 1.5 1.9 0.5 0.5 Beverages 12.1 5.0 7.2 8.5 2.8 3.3 Soft goods 10.3 7.4 3.4 8.2 4.0 4.0 Durables 19.4 12.5 5.4 10.2 11.1 6.2 Consumer services 4.2 4.9 5.2 4.5 3.5 3.0 Housing 2.9 5.0 4.0 3.1 2.7 2.2 Utilities 5.9 6.6 9.5 6.7 6.3 4.7 Transportation 12.0 10.8 10.0 9.1 7.1 3.5 Communications 8.1 7.0 7.1 8.9 7.3 5.8 Repair and personal care 2.0 2.9 3.4 9.5 6.7 6.4 Recreation 8.9 4.8 3.7 2.6 1.6 1.1 Education 3.3 3.3 6.8 4.0 2.4 2.6 Health 6.1 5.3 3.6 4.2 2.4 2.1 Investment 12.4 10.5 7.6 6.0 5.4 4.3 New fixed investment 12.4 9.9 7.2 6.4 4.8 3.8 Machinery and equipment 10.8 13.4 10.4 7.6 8.7 6.5 Construction and other capital outlays 11.6 9.7 5.1 6.4 5.1 1.7 Net additions to livestock 44.2 -3.0 24.0 0.4 NA NA Capital repair 12.2 13.7 9.1 4.0 8.0 6.1 Other government expenditures 2.4 1.7 5.7 3.9 1.3 -0.4 Government administrative services -4.5 -2.0 2.2 5.2 3.8 2.9 General agricultural programs -4.5 9.7 -1.3 4.8 4.8 5.4 Forestry -2.8 -4.0 1.3 1.7 0.9 0.3 State administration and the administrative organs of social organizations -6.0 -4.1 2.2 4.9 3.5 2.5 Culture 3.5 1.6 5.5 8.4 5.0 3.6 Municipal services 2.7 1.4 3.4 5.3 4.5 3.3 Civilian police -6.0 -4.1 2.2 4.9 3.5 2.5 Research and development 7.5 12.5 9.0 6.7 6.0 3.2 Outlays n.e.c. 4.5 1.1 5.9 2.9 -0.9 -3.1 Gross national product 5.5 5.9 5.0 5.2 3.7 2.7 68 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-8 Percent Annual Growth Rates of GNP by End Use 1958 1959 1960 1951 1952 1953 1954 1955 1956 1957 Consumption 0.7 6.0 6.7 5.6 5.6 4.7 6.9 7.0 4.5 5.3 Consumer goods -0.7 7.5 8.4 5.9 5.7 5.4 8.3 7.9 3.9 5.1 Food -3.2 7.6 7.3 3.2 5.6 4.6 8.1 7.8 3.1 4.0 Animal products 1.6 2.7 5.5 5.0 3.0 8.4 10.0 13.4 4.5 5.5 Processed foods 32.3 10.8 20.3 -18.0 23.4 9.2 3.4 4.6 4.9 7.5 Basic foods -16.6 13.6 5.8 5.3 4.2 -1.8 5.9 0.7 0.8 0.1 Beverages 11.9 11.6 12.4 12.5 12.2 4.3 10.7 5.2 -0.3 5.2 Soft goods 13.4 5.6 10.9 16.4 5.4 8.4 6.6 7.6 6.3 8.1 Durables 16.4 14.3 30.6 27.8 9.3 9.4 21.1 9.9 9.2 13.2 Consumer services 3.1 3.6 3.7 4.9 5.4 3.5 4.3 5.4 5.8 5.5 Housing 2.6 2.7 2.7 2.9 3.2 3.5 4.3 5.3 5.9 5.8 Utilities 6.3 6.6 5.7 5.4 5.6 5.7 5.2 7.5 7.7 6.9 Transportation 11.2 10.0 11.9 11.8 15.4 7.2 14.1 11.6 9.8 11.5 Communications 9.3 9.0 6.4 8.2 7.5 7.7 7.7 5.8 6.4 7.6 Repair and personal care 1.7 1.9 2.0 2.2 2.4 -2.5 -0.9 6.6 15.3 -2.8 Recreation 6.0 6.4 4.7 11.6 16.2 5.4 4.6 7.8 2.6 3.8 Education 2.4 3.1 2.6 4.2 4.2 2.9 2.5 3.0 3.1 5.2 Health 2.0 4.7 6.8 8.9 8.2 3.9 5.3 5.5 5.8 6.2 Investment 18.9 0.3 15.5 � 7.5 21.2 13.8 11.8 11.0 11.0 5.3 New fixed investment 20.5 -1.0 16.1 7.0 21.2 12.8 11.2 10.6 9.7 5.3 Machinery and equipment 0.0 9.1 5.6 18.4 22.2 25.5 10.1 13.2 8.1 10.8 Construction and other capital outlays 14.9 11.9 9.6 11.1 10.8 6.1 9.2 12.8 12.8 7.9 Net additions to livestock 528.3 NA NA NA NA 53.0 32.0 NA NA NA Capital repair 10.2 8.3 11.9 10.1 20.9 19.1 14.7 12.6 17.3 5.4 Other government expenditures -0.2 9.4 -4.3 0.7 6.8 13.3 -10.8 5.6 3.4 -1.6 Government administrative services -0.1 -0.1 -3.8 -7.4 -10.6 -2.0 -4.6 1.0 -2.7 -1.7 General agricultural pro- grams 8.4 7.5 -8.5 3.7 -27.9 9.0 -4.1 18.7 5.5 21.5 Forestry 1.7 1.7 -10.1 -3.5 -3.4 -2.2 -5.6 -3.3 -6.7 -1.9 State administration and the administrative or- gans of social organiza- tions -1.5 -1.5 -3.5 -10.7 -12.0 -3.8 -5.8 -0.7 -4.3 -5.9 Culture 3.4 3.2 2.5 4.5 4.0 1.0 1.5 2.5 1.3 1.7 Municipal services 3.9 3.7 2.1 2.0 1.9 2.6 0.9 1.2 0.7 1.8 Civilian police -1.5 -1.5 -3.5 -10.7 -12.0 -3.8 -5.8 -0.7 -4.3 -5.9 Research and development 9.9 8.2 5.0 5.8 9.0 13.2 10.8 13.3 10.9 14.4 Outlays n.e.c. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Gross national product 3.1 5.9 5.2 4.7 8.6 8.4 3.8 7.6 5.8 4.0 69 93-892 0 - 82 - 6 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-8 (Continued) Percent Annual Growth Rates of GNP by End Use 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 Consumption 2.9 4.0 4.7 1.4 5.4 5.5 5.8 6.0 4.8 4.6 Consumer goods 1.8 3.3 4.5 -0.9 5.4 5.9 6.4 6.7 5.2 4.8 Food 1.5 3.1 5.7 -2.4 4.7 4.7 5.6 5.8 4.4 3.6 Animal products 0.8 2.1 10.1 -8.6 5.3 7.7 6.4 6.9 5.3 2.9 Processed foods 4.6 6.4 4.2 9.2 4.5 1.2 5.8 4.2 5.2 4.1 Basic foods 0.9 2.3 -2.4 4.2 2.9 -0.3 2.9 3.5 -1.2 5.0 Beverages 6.2 10.2 6.5 6.0 7.3 7.5 9.2 7.9 13.5 4.4 Soft goods 3.4 3.5 0.5 3.1 6.8 8.8 8.9 8.8 7.5 7.0 Durables 1.7 5.1 -0.4 9.9 11.2 11.8 8.6 10.9 7.9 11.7 Consumer services 4.8 5.3 5.1 5.5 5.3 4.8 4.7 4.9 4.1 4.2 Housing 5.0 4.4 4.0 3.5 3.3 3.2 3.2 3.1 2.9 2.8 Utilities 9.9 10.2 9.6 9.2 8.5 6.9 6.3 7.1 7.0 6.5 Transportation 9.6 12.9 10.3 8.2 9.3 11.1 9.8 9.6 7.4 7.5 Communications 5.9 6.2 5.9 7.1 10.4 10.5 10.3 7.2 8.7 7.5 Repair and personal care -6.8 -0.4 3.1 9.9 12.3 10.7 10.5 9.9 7.4 9.0 Recreation 4.0 2.5 0.5 8.0 3.9 0.5 6.1 4.3 1.0 1.5 Education 6.1 8.1 7.0 6.9 5.8 4.9 3.9 4.6 3.8 2.7 Health 3.7 1.7 4.3 3.8 4.7 4.0 3.0 4.4 3.9 6.0 Investment 11.2 4.1 -7.7 23.3 9.3 0.9 3.7 6.5 6.4 12.7 New fixed investment 12.0 3.0 -12.5 27.5 10.2 0.3 4.2 6.6 7.1 14.3 Machinery and equipment 8.7 12.5 10.3 13.7 7.0 5.9 7.3 7.8 4.8 12.4 Construction and other capital outlays 4.6 4.9 3.7 4.5 7.8 4.1 9.2 5.5 4.9 8.6 Net additions to livestock 205.7 NA NA NA 68.3 NA NA NA NA 450.3 Capital repair 7.8 9.3 14.3 8.6 5.8 3.1 1.8 6.2 3.6 5.6 Other government expenditures 6.8 2.8 -9.9 27.8 4.5 10.1 2.6 5.4 -7.6 10.0 Government administrative services -0.9 2.1 0.5 4.2 5.5 5.4 7.0 5.6 5.1 2.7 General agricultural pro- grams -9.7 -1.4 -1.4 3.7 2.9 5.9 9.4 7.5 1.5 -0.1 Forestry 0.7 2.9 2.3 1.8 -1.3 2.2 1.0 2.4 1.4 1.4 State administration and the administrative or- gans of social organiza- tions -0.5 1.6 -0.8 4.0 7.0 5.9 6.6 4.9 5.4 1.9 Culture 3.2 6.4 5.4 6.8 5.6 4.8 10.0 10.1 8.8 8.3 Municipal services 1.1 3.3 3.9 5.1 3.7 4.8 7.7 4.9 4.9 3.9 Civilian police -0.5 1.6 -0.8 4.0 7.0 5.9 6.6 4.9 5.4 1.9 Research and development 11.8 11.1 7.9 8.8 5.4 6.6 4.2 6.9 6.9 8.7 Outlays n.e.c. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Gross national product 5.6 3.8 -1.1 11.0 6.3 5.1 4.6 6.0 2.9 7.7 70 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-8 (Continued) Annual Growth Rates of GNP by End Use Percent 1978 1979 1980 1971 1972 1973 1974 1975 1976 1977 Consumption 3.6 2.4 4.1 3.7 3.9 2.3 2.9 2.9 2.8 2.3 Consumer goods 3.6 1.9 4.5 3.7 4.2 1.8 3.2 2.6 2.7 1.9 Food 2.4 0.1 4.4 3.2 3.1 0.3 2.3 2.3 2.0 0.2 Animal products 2.1 1.7 5.2 3.9 4.2 -0.1 1.3 1.9 2.6 0.1 Processed foods 2.3 1.5 6.2 2.9 0.7 4.4 3.7 3.5 1.9 1.1 Basic foods 3.6 -4.1 4.0 -0.8 0.3 -1.7 5.3 1.5 -0.8 -1.7 Beverages 1.3 0.1 -1.4 9.2 5.2 2.4 0.5 5.0 4.5 4.3 Soft goods 4.7 3.0 3.2 3.5 5.5 4.7 3.3 2.9 4.2 4.8 6.8 2.9 2.1 4.5 Durables 13.5 15.4 8.4 8.4 9.7 6.6 9.2 4.2 4.1 3.0 Consumer services 3.6 3.3 3.4 3.8 3.6 3.1 2.3 3.4 Housing 2.7 2.7 2.7 2.6 2.6 2.4 2.3 2.3 2.1 Utilities 6.8 6.6 6.2 6:1 5.8 6.0 3.9 4.8 4.1 Transportation 6.9 7.4 5.8 8.0 7.6 5.9 -0.5 3.9 4.4 3.8 Communications 7.3 7.4 7.2 7.2 7.2 6.4 5.7 5.5 5.6 5.6 Repair and personal care 6.4 7.0 7.2 6.7 6.1 5.9 4.9 7.2 7.0 6.9 Recreation 2.3 1.0 1.9 1.5 1.0 -1.6 0.4 2.6 1.7 2.5 Education 2.9 1.3 2.2 2.9 2.8 2.3 2.4 3.1 2.2 2.8 Health 2.3 2.1 2.4 3.0 2.2 2.1 2.3 3.2 2.5 0.7 Investment 4.8 4.2 9.2 6.6 2.2 8.0 5.1 3.7 1.7 3.0 New fixed investment 3.5 3.1 8.2 6.2 3.2 7.6 4.4 3.1 1.4 2.6 Machinery and equipment 5.3 8.2 7.6 10.0 12.8 9.7 5.7 8.4 4.3 0.7 4.7 2.1 NA Construction and other capital outlays 6.4 5.0 5.2 4.6 4.3 2.4 1.2 1.9 Net additions to livestock NA NA NA NA NA NA 236.8 NA NA Capital repair 11.4 9.1 13.6 8.3 -1.7 9.6 8.0 6.1 2.9 4.2 -5.5 Other government expenditures 3.2 -3.4 14.2 -0.1 -6.3 7.1 0.4 4.6 -7.8 Government administrative services 4.2 3.8 3.3 4.2 3.4 3.0 2.8 3.3 6.2 1.3 2.6 3.9 0.0 3.0 5.6 0.4 General agricultural pro- grams 6.8 4.5 4.0 4.1 4.6 9.1 2.3 Forestry 0.4 2.3 -0.5 1.4 0.7 -0.9 0.4 State administration and the administrative or- gans of social organiza- tions 3.3 3.5 3.2 4.2 3.3 2.2 2.2 2.5 2.7 2.9 2.4 2.8 Culture 6.9 4.2 4.7 5.4 4.0 3.9 5.6 4.1 2.2 Municipal services 5.9 4.9 3.7 4.2 3.7 2.4 3.6 4.3 3.2 Civilian police 3.3 3.5 3.2 4.2 3.3 2.2 2.2 2.5 2.7 2.9 4.3 0.0 Research and development 6.7 7.4 6.8 4.4 4.9 1.4 2.6 3.5 4.3 Outlays n.e.c. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Gross national product 3.9 1.9 7.3 3.9 1.7 4.8 3.2 3.4 0.8 1.4 71 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-9 Per Capita GNP by End Use 1970 Rubles 1959 1950 1951 1952 1953 1954 1955 1956 1957 1958 Consumption 444.6 440.5 459.4 479.7 498.4 517.9 532.7 559.7 588.6 604.5 Consumer goods 279.2 272.7 288.4 306.0 319.0 331.7 343.4 365.6 387.6 395.5 Food 238.3 226.9 240.2 252.3 256.4 266.4 273.7 290.7 308.0 311.9 Animal products 118.2 118.2 119.4 123.4 127.5 129.2 137.6 148.8 165.7 170.1 Processed foods 14.9 19.3 21.1 24.8 20.1 24.4 26.1 26.5 27.3 28.1 Basic foods 94.5 77.5 86.7 89.7 93.0 95.3 92.0 95.8 94.7 93.9 Beverages 10.8 11.9 13.1 14.4 15.9 17.6 18.0 19.6 20.2 19.8 Soft goods 35.2 39.3 40.8 44.3 50.8 52.6 56.1 58.7 62.1 64.9 Durables 5.7 6.5 7.3 9.4 11.8 12.7 13.6 16.2 17.5 18.8 Consumer services 165.4 167.7 171.0 173.7 179.5 186.2 189.3 194.0 201.0 209.0 Housing 72.0 72.7 73.5 73.9 74.9 76.1 77.4 79.3 82.1 85.5 Utilities 5.1 5.3 5.6 5.8 6.0 6.2 6.4 6.7 7.0 7.4 Transportation 5.0 5.5 6.0 6.5 7.2 8.1 8.6 9.6 10.5 11.4 Communications 2.4 2.6 2.8 2.9 3.1 3.3 3.5 3.7 3.8 4.0 Repair and personal care 10.7 10.7 10.7 10.7 10.8 10.9 10.4 10.1 10.6 12.0 Recreation 7.7 8.0 8.4 8.6 9.5 10.8 11.2 11.5 12.2 12.3 Education 40.9 41.2 41.8 42.0 43.1 44.2 44.7 45.0 45.6 46.2 Health 21.5 21.6 22.3 23.3 24.9 26.6 27.1 28.1 29.1 30.2 Gross national product 741.7 752.2 784.0 807.3 832.4 889.2 946.8 965.7 1,021.1 1,061.2 Population (million) 180.1 183.0 186.0 190.0 193.0 196.2 199.7 203.2 206.8 210.5 72 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-9 (Continued) 1970 Rubles Per Capita GNP by End Use 1960 1961 1962 1963 1967 1968 1969 1964 1965 1966 Consumption 625.0 631.7 646.1 666.4 666.8 694.1 724.0 757.6 795.3 825.6 Consumer goods 408.5 408.7 415.2 427.3 417.9 435.2 455.6 479.7 506.7 528.0 Food 318.7 317.9 322.4 335.6 323.3 334.4 346.3 362.0 379.3 392.1 Animal products 176.3 174.6 175.3 90.1 171.6 178.5 90.1 200.1 211.8 220.9 Processed foods 29.7 30.5 31.9 32.8 35.3 36.5 36.5 38.2 39.4 41.1 Basic foods 92.3 91.4 92.0 88.4 90.9 92.4 91.1 92.8 95.0 93.0 Beverages 20.5 21.4 23.2 24.3 25.4 26.9 28.7 31.0 33.1 37.2 Soft goods 68.9 70.0 71.2 70.5 71.7 75.6 81.4 87.8 94.6 100.7 Durables 20.9 20.8 21.5 21.1 22.9 25.2 27.9 29.9 32.9 35.1 Consumer services 216.5 223.0 231.0 239.2 249.0 259.0 268.4 277.9 288.6 297.6 Housing 88.8 91.6 94.1 96.3 98.4 100.4 102.5 104.6 106.9 109.0 Utilities 7.8 8.4 9.1 9.9 10.6 11.4 12.0 12.7 13.4 14.2 Transportation 12.5 13.4 14.9 16.2 17.3 18.7 20.5 22.3 24.2 25.7 Communications 4.2 4.4 4.6 4.8 5.0 5.5 6.0 6.5 6.9 7.5 Repair and personal care 11.5 10.5 10.3 10.4 11.3 12.6 13.8 15.0 16.4 17.4 Recreation 12.6 12.8 12.9 12.8 13.7 14.0 13.9 14.6 15.1 15.1 Education 47.7 49.7 52.9 55.8 58.8 61.5 63.7 65.5 67.9 69.8 Health 31.5 32.1 32.1 33.0 33.8 35.0 35.9 36.6 37.8 38.9 Gross national product 1,083.8 1,124.6 1,148.1 1,118.1 1,224.7 1,285.5 1,335.9 1,382.6 1,451.8 1,479.0 Population (million) 214.3 218.1 221.7 225.1 228.1 230.9 233.5 236.0 238.3 240.6 73 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-9 (Continued) 1970 Rubles Per Capita GNP by End Use 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 Consumption 855.7 878.5 890.6 918.7 944.4 972.4 985.4 1,005.4 1,025.5 1,046.0 1,061.5 Consumer goods 548.4 563.0 568.0 588.2 604.5 623.7 629.1 644.0 655.2 667.4 674.9 Food 402.7 408.6 405.1 419.1 428.4 437.3 434.5 440.7 446.9 452.2 449.7 Animal products 225.1 227.7 229.4 239.1 246.1 254.1 251.5 252.6 255.1 259.7 257.9 Processed foods 42.4 42.9 43.2 45.4 46.3 46.2 47.7 49.1 50.3 50.9 51.0 Basic foods 96.8 99.3 94.4 97.2 95.5 94.9 92.5 96.5 97.1 95.6 93.2 Beverages 38.5 38.6 38.3 37.4 40.5 42.1 42.8 42.6 44.4 46.0 47.6 Soft goods 106.7 110.7 112.9 115.4 118.4 123.7 128.4 131.5 134.1 138.7 144.1 Durables 38.9 43.7 50.0 53.7 57.7 62.7 66.3 71.7 74.1 76.6 81.1 Consumer services 307.3 315.5 322.6 330.5 339.9 348.7 356.3 361.5 370.4 378.5 386.5 Housing 111.0 113.0 114.9 116.9 118.9 120.8 122.6 124.3 126.0 127.7 129.3 Utilities 15.0 15.9 16.8 17.6 18.6 19.4 20.4 21.1 21.9 22.6 23.4 Transportation 27.4 29.0 30.9 32.4 34.6 36.9 38.7 38.2 39.4 40.8 42.0 Communications 8.0 8.5 9.0 9.6 10.2 10.8 11.4 11.9 12.5 13.1 13.7 Repair and personal care 18.8 19.8 21.0 22.3 23.6 24.8 26.0 27.1 28.8 30.5 32.4 Recreation 15.2 15.4 15.4 15.6 15.7 15.7 15.3 15.2 15.5 15.6 15.9 Education 71.0 72.4 72.6 73.6 75.0 76.4 77.4 78.6 80.3 81.4 83.0 Health 40.9 41.5 41.9 42.5 43.4 43.9 44.4 45.1 46.1 46.9 46.8 Gross national product 1,578.5 1,624.6 1,639.3 1,742.2 1,793.7 1,806.5 1,875.4 1,919.1 1,967.5 1,967.3 1,978.9 Population (million) 242.8 245.1 247.5 249.8 252.1 254.5 256.8 259.0 261.3 263.4 265.5 74 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-10 Percent Average Annual Rates of Growth of Per Capita GNP by End Use 1966-70 1971-75 1976-80 1951-55 1956-60 1961-65 Consumption 3.1 3.8 2.1 4.3 2.6 1.8 Consumer goods 3.5 4.3 1.3 4.7 2.6 1.6 Food 2.3 3.7 1.0 3.8 1.7 0.6 Animal products 1.8 6.4 0.2 4.7 2.5 0.3 Processed foods 10.4 4.0 4.2 3.0 1.7 2.0 Basic foods 0.2 -0.6 0.0 0.9 -0.4 -0.4 Beverages 10.2 3.1 5.6 7.4 1.8 2.5 Soft goods 8.4 5.5 1.9 7.1 3.0 3.1 Durables 17.4 10.5 3.9 9.1 10.0 5.3 Consumer services 2.4 3.1 3.6 3.5 2.6 2.1 Housing 1.1 3.1 2.5 2.0 1.7 1.4 Utilities 4.1 4.7 7.8 5.7 5.3 3.8 Transportation 10.1 8.9 8.4 8.0 6.1 2.6 Communications 6.2 5.2 5.5 7.8 6.3 4.9 Repair and personal care 0.3 1.1 1.8 8.4 5.7 5.5 Recreation 7.1 3.0 2.2 1.6 0.6 0.3 Education 1.5 1.5 5.2 2.9 1.5 1.7 Health 4.3 3.5 2.1 3.2 1.4 1.3 Gross national product 3.7 4.0 3.5 4.2 2.7 1.8 Population 1.7 1.8 1.5 1.0 0.9 0.8 75 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-11 Percentage Shares of GNP by End Use Percent 1959 1950 1951 1952 1953 1954 1955 1956 1957 1958 Consumption 59.9 58.6 58.6 59.4 59.9 58.2 56.3 58.0 57.6 57.0 Consumer goods 37.6 36.3 36.8 37.9 38.3 37.3 36.3 37.9 38.0 37.3 Food 32.1 30.2 30.6 31.3 30.8 30.0 28.9 30.1 30.2 29.4 Animal products 15.9 15.7 15.2 15.3 15.3 14.5 14.5 15.4 16.2 16.0 Processed foods 2.0 2.6 2.7 3.1 2.4 2.7 2.8 2.7 2.7 2.6 Basic foods 12.7 10.3 11.1 11.1 11.2 10.7 9.7 9.9 9.3 8.8 Beverages 1.5 1.6 1.7 1.8 1.9 2.0 1.9 2.0 2.0 1.9 Soft goods 4.7 5.2 5.2 5.5 6.1 5.9 5.9 6.1 6.1 6.1 Durables 0.8 0.9 0.9 1.2 1.4 1.4 1.4 1.7 1.7 1.8 Consumer services 22.3 22.3 21.8 21.5 21.6 20.9 20.0 20.1 19.7 19.7 Housing 9.7 9.7 9.4 9.2 9.0 8.6 8.2 8.2 8.0 8.1 Utilities 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 Transportation 0.7 0.7 0.8 0.8 0.9 0.9 0.9 1.0 1.0 1.1 Communications 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Repair and personal care 1.4 1.4 1.4 1.3 1.3 1.2 1.1 1.0 1.0 1.1 Recreation 1.0 1.1 1.1 1.1 1.1 1.2 1.2 1.2 1.2 1.2 Education 5.5 5.5 5.3 5.2 5.2 5.0 4.7 4.7 4.5 4.4 Health 2.9 2.9 2.8 2.9 3.0 3.0 2.9 2.9 2.8 2.8 Investment 14.2 16.4 15.5 17.1 17.5 19.5 20.5 22.1 22.8 23.9 New fixed investment 12.0 14.1 13.2 14.5 14.9 16.6 17.2 18.5 19.0 19.7 Machinery and equipment 2.6 2.5 2.6 2.6 2.9 3.3 3.8 4.1 4.3 4.4 Construction and other capital outlays 9.2 10.3 10.9 11.3 12.0 12.3 12.0 12.6 13.3 14.1 Net additions to livestock 0.2 1.3 -0.3 0.6 -0.1 1.0 1.4 1.8 1.5 1.2 Capital repair 2.2 2.3 2.4 2.5 2.7 3.0 3.3 3.6 3.8 4.2 Other government expenditures 25.8 25.0 25.9 23.5 22.6 22.2 23.2 20.0 19.6 19.2 Government administrative services 7.8 7.6 7.1 6.5 5.8 4.7 4.3 3.9 3.7 3.4 General agricultural pro- grams 0.5 0.5 0.5 0.5 0.5 0.3 0.3 0.3 0.3 0.3 Forestry 0.6 0.6 0.6 0.5 0.4 0.4 0.4 0.3 0.3 0.3 State administration and the administrative or- gans of social organiza- tions 4.5 4.3 4.0 3.7 3.1 2.5 2.2 2.0 1.9 1.7 Culture 0.5 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.3 Municipal services 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Civilian police 1.4 1.3 1.2 1.1 1.0 0.8 0.7 0.6 0.6 0.5 Research and development 1.6 1.7 1.8 1.8 1.8 1.8 1.9 2.0 2.1 2.2 Outlays n.e.c. 16.4 15.7 16.9 15.2 15.0 15.7 17.1 14.0 13.8 13.5 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 76 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-11 (Continued) Percentage Shares of GNP by End Use Percent 1966 1967 1968 1969 55.8 1960 1961 1962 1963 1964 1965 Consumption 57.7 56.2 56.3 59.6 54.4 54.0 54.2 54.8 54.8 Consumer goods 37.7 36.3 36.2 38.2 34.1 33.9 34.1 34.7 34.9 35.7 Food 29.4 28.3 28.1 30.0 26.4 26.0 25.9 26.2 26.1 26.5 14.9 Animal products 16.3 15.5 15.3 17.0 14.0 13.9 14.2 14.5 14.6 Processed foods 2.7 2.7 2.8 2.9 2.9 2.8 2.7 2.8 2.7 2.8 Basic foods 8.5 8.1 8.0 7.9 7.4 7.2 6.8 6.7 6.5 6.3 Beverages 1.9 1.9 2.0 2.2 2.1 2.1 2.1 2.2 2.3 2.5 Soft goods 6.4 6.2 6.2 6.3 5.9 5.9 6.1 6.3 6.5 6.8 Durables 1.9 1.9 1.9 1.9 1.9 2.0 2.1 2.2 2.3 2.4 Consumer services 20.0 19.8 20.1 21.4 20.3 20.1 20.1 20.1 19.9 20.1 Housing 8.2 8.1 8.2 8.6 8.0 7.8 7.7 7.6 7.4 7.4 1.0 Utilities 0.7 0.8 0.8 0.9 0.9 0.9 0.9 0.9 0.9 Transportation 1.1 1.2 1.3 1.4 1.4 1.5 1.5 1.6 1.7 1.7 Communications 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 Repair and personal care 1.1 0.9 0.9 0.9 0.9 1.0 1.0 1.1 1.1 1.2 Recreation 1.2 1.1 1.1 1.1 1.1 1.1 1.0 1.1 1.0 1.0 Education 4.4 4.4 4.6 5.0 4.8 4.8 4.8 4.7 4.7 4.7 Health 2.9 2.9 2.8 3.0 2.8 2.7 2.7 2.6 2.6 2.6 Investment 24.2 25.5 25.6 23.9 26.5 27.3 26.2 26.0 26.1 27.0 New fixed investment 20.0 21.2 21.0 18.6 21.4 22.1 21.1 21.1 21.2 22.1 Machinery and equipment 4.7 4.8 5.2 5.8 5.9 6.0 6.0 6.2 6.3 6.4 Construction and other capital outlays 14.7 14.5 14.7 15.4 14.5 14.7 14.6 15.2 15.1 15.4 Net additions to livestock 0.6 1.8 1.1 -2.6 0.9 1.5 0.6 -0.3 -0.2 0.2 Capital repair 4.2 4.3 4.5 5.3 5.1 5.1 5.0 4.9 4.9 4.9 17.2 Other government expenditures 18.1 18.3 18.2 16.5 19.0 18.7 19.6 19.2 19.1 Government administrative services 3.2 3.0 3.0 3.0 2.8 2.8 2.8 2.9 2.9 2.9 General agricultural pro- grams 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 1.4 Forestry 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 State administration and the administrative or- gans of social organiza- tions 1.5 1.4 1.4 1.4 1.3 1.3 1.4 1.4 1.4 Culture 0.3 0.3 0.3 0.4 0.4 0.3 0.3 0.4 0.4 0.4 0.2 Municipal services 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Civilian police 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Research and development 2.4 2.6 2.8 3.0 3.0 2.9 3.0 3.0 3.0 3.1 Outlays n.e.c. 12.5 12.7 12.4 10.5 13.3 13.0 13.8 13.4 13.3 11.1 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 77 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-11 (Continued) Percentage Shares of GNP by End Use Percent 1971 1972 1978 1979 1980 1970 1973 1974 1975 1976 1977 Consumption 54.2 54.1 54.3 52.7 52.6 53.8 52.5 52.4 52.1 53.2 53.6 Consumer goods 34.7 34.7 34.7 33.8 33.7 34.5 33.5 33.6 33.3 33.9 34.1 Food 25.5 25.1 24.7 24.1 23.9 24.2 23.2 23.0 22.7 23.0 22.7 Animal products 14.3 14.0 14.0 13.7 13.7 14.1 13.4 13.2 13.0 13.2 13.0 Processed foods 2.7 2.6 2.6 2.6 2.6 2.6 2.5 2.6 2.6 2.6 2.6 Basic foods 6.1 6.1 5.8 5.6 5.3 5.3 4.9 5.0 4.9 4.9 4.7 Beverages 2.4 2.4 2.3 2.1 2.3 2.3 2.3 2.2 2.3 2.3 2.4 Soft goods 6.8 6.8 6.9 6.6 6.6 6.8 6.8 6.9 6.8 7.0 7.3 Durables 2.5 2.7 3.1 3.1 3.2 3.5 3.5 3.7 3.8 3.9 4.1 Consumer services 19.5 19.4 19.7 19.0 18.9 19.3 19.0 18.8 18.8 19.2 19.5 Housing 7.0 7.0 7.0 6.7 6.6 6.7 6.5 6.5 6.4 6.5 6.5 Utilities 1.0 1.0 1.0 1.0 1.0 1.1 1.1 1.1 1.1 1.1 1.2 Transportation 1.7 1.8 1.9 1.9 1.9 2.0 2.1 2.0 2.0 2.1 2.1 Communications 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 Repair and personal care 1.2 1.2 1.3 1.3 1.3 1.4 1.4 1.4 1.5 1.6 1.6 Recreation 1.0 0.9 0.9 0.9 0.9 0.9 0.8 0.8 0.8 0.8 0.8 Education 4.5 4.5 4.4 4.2 4.2 4.2 4.1 4.1 4.1 4.1 4.2 Health 2.6 2.6 2.6 2.4 2.4 2.4 2.4 2.3 2.3 2.4 2.4 Investment 28.2 28.5 29.1 29.7 30.4 30.6 31.5 32.1 32.2 32.5 33.0 New fixed investment 23.4 23.3 23.6 23.8 24.3 24.6 25.3 25.6 25.5 25.7 26.0 Machinery and equipment 6.7 6.8 7.2 7.2 7.6 8.5 8.9 9.1 9.5 9.9 10.2 Construction and other capital outlays 15.6 15.9 16.4 16.1 16.2 16.6 16.3 15.9 15.7 15.7 15.8 Net additions to livestock 1.2 0.6 0.0 0.5 0.4 -0.5 0.2 0.6 0.3 0.1 0.0 Capital repair 4.8 5.2 5.6 5.9 6.1 5.9 6.2 6.5 6.7 6.8 7.0 Other government expenditures 17.6 17.4 16.5 17.6 16.9 15.6 15.9 15.5 15.7 14.3 13.4 Government administrative services 2.8 2.8 2.9 2.8 2.8 2.8 2.8 2.8 2.8 2.8 2.8 General agricultural pro- grams 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Forestry 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 State administration and the administrative or- gans of social organiza- tions 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 1.3 Culture 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.5 Municipal services 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Civilian police 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 Research and development 3.1 3.2 3.4 3.4 3.4 3.5 3.4 3.4 3.4 3.5 3.6 Outlays n.e.c. 11.6 11.4 10.3 11.5 10.8 9.3 9.8 9.4 9.6 8.1 6.9 Gross national product 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 78 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-12 Indexes of GNP by End Use 1956 1957 1958 1970=100 1959 61.2 1950 1951 1952 1953 1954 1955 Consumption 38.5 38.8 41.1 43.9 46.3 48.9 51.2 54.7 58.6 Consumer goods 37.8 37.5 40.3 43.7 46.2 48.9 51.5 55.8 60.2 62.5 Food 43.9 42.5 45.7 49.0 50.6 53.5 55.9 60.4 65.1 67.1 65.5 Animal products 38.9 39.6 40.6 42.9 45.0 46.4 50.3 55.3 62.7 Processed foods 26.0 34.4 38.2 45.9 37.7 46.5 50.7 52.4 54.8 57.5 Basic foods 72.4 60.4 68.6 72.6 76.4 79.6 78.2 82.8 83.4 84.1 Beverages 20.8 23.3 26.0 29.2 32.9 36.9 38.5 42.6 44.8 44.7 Soft goods 24.5 27.7 29.3 32.5 37.8 39.8 43.2 46.1 49.6 52.7 Durables 10.8 12.6 14.4 18.8 24.1 26.3 28.8 34.8 38.3 41.8 Consumer services 39.9 41.1 42.6 44.2 46.4 48.9 50.7 52.8 55.7 59.0 66.7 Housing 48.1 49.4 50.7 52.1 53.6 55.4 57.3 59.8 63.0 Utilities 25.1 26.6 28.4 30.0 31.6 33.4 35.3 37.1 39.9 42.9 Transportation 13.6 15.1 16.6 18.6 20.8 24.0 25.7 29.4 32.8 36.0 Communications 22.4 24.5 26.7 28.4 30.8 33.1 35.6 38.4 40.6 43.2 Repair and personal care 42.1 42.9 43.7 44.6 45.6 46.6 45.4 45.0 48.0 55.3 Recreation 37.6 39.9 42.4 44.4 49.6 57.6 60.8 63.6 68.5 70.3 Education 42.8 43.8 45.1 46.3 48.3 50.3 51.8 53.1 54.7 56.4 Health 39.0 39.8 41.7 44.5 48.5 52.5 54.5 57.4 60.6 64.1 Investment 17.6 20.9 20.9 24.2 26.0 31.5 35.8 40.0 44.4 49.3 New fixed investment 17.9 21.6 21.4 24.9 26.6 32.2 36.4 40.5 44.8 49.1 Machinery and equipment 13.5 13.5 14.8 15.6 18.4 22.5 28.3 31.1 35.2 38.1 Construction and other capital outlays 20.7 23.8 26.6 29.2 32.4 35.9 38.1 41.6 47.0 53.0 60.9 Net additions to livestock 6.2 39.1 -10.4 20.3 -4.4 38.8 59.4 78.5 69.9 Capital repair 15.7 17.3 18.7 20.9 23.0 27.9 33.2 38.0 42.9 50.3 Other government expenditures 51.3 51.2 56.0 53.6 54.0 57.6 65.3 58.2 61.5 63.6 Government administrative services 97.0 97.0 96.8 93.2 86.3 77.1 75.5 72.1 72.8 65.9 70.8 69.5 87.9 74.9 General agricultural pro- grams 66.7 72.3 77.7 71.1 73.7 53.1 57.9 55.5 Forestry 121.8 123.9 126.0 113.3 109.3 105.6 103.2 97.4 94.2 State administration and the administrative or- gans of social organiza- tions 118.3 116.6 114.8 110.7 98.9 87.0 83.7 78.8 78.2 Culture 39.9 41.2 42.5 43.6 45.5 47.3 47.8 48.5 49.7 50.4 Municipal services 53.4 55.4 57.5 58.7 59.8 60.9 62.5 63.1 63.9 64.3 Civilian police 118.3 116.6 114.8 110.7 98.9 87.0 83.7 78.8 78.2 74.9 Research and development 18.2 20.0 21.6 22.7 24.0 26.2 29.6 32.8 37.2 41.3 Outlays n.e.c. 49.2 48.6 55.5 52.4 54.3 61.4 72.5 61.7 65.3 67.9 Gross national product 34.9 35.9 38.0 40.0 41.9 45.5 49.3 51.2 55.1 58.3 79 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-12 (Continued) Indexes of GNP by End Use 1970=100 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Consumption 64.5 66.3 68.9 72.2 73.2 77.1 81.4 86.1 91.2 95.6 , Consumer goods 65.7 66.9 69.1 72.2 71.6 75.5 79.9 85.0 90.7 95.4 Food 69.9 70.9 73.1 77.3 75.4 79.0 82.7 87.4 92.4 96.5 Animal products 69.1 69.7 71.1 78.3 71.6 75.4 81.2 86.4 92.3 97.2 Processed foods 61.8 64.7 68.9 71.7 78.4 81.9 82.8 87.6 91.3 96.1 Basic foods 84.1 84.9 86.8 84.7 88.3 90.8 90.5 93.2 96.4 95.2 Beverages 47.0 49.9 55.0 58.6 62.1 66.6 71.6 78.2 84.4 95.8 Soft goods 57.0 58.9 60.9 61.2 63.1 67.4 73.4 79.9 86.9 93.5 Durables 47.3 48.1 50.5 50.4 55.4 61.6 68.9 74.8 83.0 89.5 Consumer services 62.2 65.2 68.6 72.2 76.1 80.1 84.0 87.9 92.2 96.0 Housing 70.6 74.1 77.4 80.5 83.3 86.0 88.8 91.6 94.5 97.3 Utilities 45.9 50.4 55.5 60.9 66.5 72.1 77.1 81.9 87.7 93.9 Transportation 40.1 44.0 49.7 54.8 59.3 64.8 72.0 79.1 86.6 93.0 Communications 46.5 49.2 52.3 55.3 59.3 65.4 72.3 79.8 85.5 93.0 Repair and personal care 53.8 50.1 49.9 51.5 56.5 63.5 70.3 77.7 85.4 91.7 Recreation 73.0 75.9 77.8 78.2 84.4 87.7 88.2 93.6 97.6 98.6 Education 59.3 62.9 68.0 72.8 77.8 82.3 86.3 89.6 93.8 97.4 Health 68.0 70.5 71.7 74.8 77.6 81.3 84.5 87.0 90.8 94.3 Investment 51.9 57.8 60.1 55.5 68.4 74.8 75.5 78.3 83.4 88.7 New fixed investment 51.7 57.9 59.7 52.2 66.6 73.3 73.6 76.7 81.7 87.5 Machinery and equipment 42.2 45.9 51.6 57.0 64.8 69.3 73.4 78.7 84.8 88.9 Construction and other capital outlays 57.2 59.8 62.7 65.0 67.9 73.2 76.2 83.3 87.8 92.1 Net additions to livestock 33.4 102.2 65.1 -148.3 58.2 98.0 38.9 -23.9 -17.8 18.2 Capital repair 53.0 57.1 62.4 71.4 77.5 82.0 84.6 86.1 91.4 94.7 Other government expenditures 62.6 66.8 68.7 61.9 79.1 82.6 91.0 93.3 98.4 90.9 Government administrative services 69.6 68.9 70.3 70.7 73.7 77.7 81.9 87.7 92.6 97.4 General agricultural pro- grams 84.5 76.4 75.3 74.2 77.0 79.2 83.9 91.7 98.6 100.1 Forestry 86.2 86.9 89.4 91.5 93.1 91.9 94.0 94.9 97.2 98.6 State administration and the administrative or- gans of social organiza- tions 70.5 70.1 71.2 70.7 73.5 78.6 83.3 88.8 93.1 98.1 Culture 51.3 52.9 56.3 59.3 63.4 66.9 70.1 77.1 84.9 92.4 Municipal services 65.4 66.2 68.3 71.0 74.6 77.4 81.1 87.4 91.7 96.2 Civilian police 70.5 70.1 71.2 70.7 73.5 78.6 83.3 88.8 93.1 98.1 Research and development 47.2 52.7 58.6 63.2 68.7 72.4 77.3 80.5 86.0 92.0 Outlays n.e.c. 65.1 70.1 71.0 59.4 83.2 86.6 96.9 98.2 103.1 89.1 Gross national product 60.6 64.0 66.4 65.7 72.9 77.4 81.4 85.1 90.3 92.9 80 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-12 (Continued) Indexes of GNP by End Use 1970=100 1978 1979 1980 1970 1971 1972 1973 1974 1975 1976 1977 Consumption 100.0 103.6 106.1 110.5 114.6 119.1 121.8 125.3 129.0 132.6 135.6 Consumer goods 100.0 103.6 105.6 110.4 114.5 119.2 121.3 125.3 128.6 132.0 134.6 Food 100.0 102.4 102.5 107.1 110.4 113.8 114.1 116.7 119.4 121.8 122.1 Animal products 100.0 102.1 103.9 109.3 11:1.5 118.3 118.2 119.7 122.0 125.2 125.3 Processed foods 100.0 102.3 103.9 110.3 1115 114.2 119.2 123.6 127.9 130.4 131.8 Basic foods 100.0 103.6 99.4 103.3 102.5 102.8 101.0 106.4 108.0 107.1 105.3 Beverages 100.0 101.3 101.4 100.0 109.2 114.8 117.6 118.2 124.1 129.7 135.3 Soft goods 100.0 104.7 107.8 111.2 115.2 121.5 127.2 131.4 135.2 140.9 147.7 Durables 100.0 113.5 131.0 142.1 154.0 168.9 180.1 196.7 205.0 213.5 227.9 Consumer services 100.0 103.6 107.0 110.6 114.8 118.9 122.6 125.5 129.7 133.6 137.5 127.4 Housing 100.0 102.7 105.5 108.4 111.2 114.1 116.8 119.5 122.2 124.8 Utilities 100.0 106.8 113.8 120.8 128.2 135.7 143.8 149.5 156.6 163.0 170.4 Transportation 100.0 106.9 114.8 121.5 131.2 141.2 149.5 148.8 154.6 161.4 167.6 Communications 100.0 107.3 115.2 123.5 132.4 142.0 151.1 159.6 168.4 177.9 187.9 188.0 Repair and personal care 100.0 106.4 113.8 122.0 130.1 138.1 146.3 153.5 164.5 175.9 Recreation 100.0 102.3 103.4 105.4 107.0 108.0 106.3 106.7 109.5 111.4 114.3 Education 100.0 102.9 104.2 106.5 109.7 112.7 115.3 118.0 121.7 124.3 127.8 Health 100.0 102.3 104.5 107.0 110.2 112.6 114.9 117.5 121.3 124.3 125.2 Investment 100.0 104.8 109.2 119.3 127.1 129.9 140.2 147.4 152.9 155.5 160.2 152.4 New fixed investment 100.0 103.5 106.7 115.4 122.5 126.4 135.9 141.9 146.4 148.5 Machinery and equipment 100.0 105.3 113.9 122.5 134.8 152.0 166.8 176.2 191.0 199.2 208.6 Construction and other capital outlays 100.0 106.4 111.7 117.5 122.9 128.3 131.3 132.9 135.5 136.4 139.3 2.6 197.8 Net additions to livestock 100.0 53.6 -2.3 45.2 45.2 -47.7 19.1 64.2 34.6 16.9 Capital repair 100.0 111.4 121.5 138.0 149.5 147.0 161.1 174.0 184.6 189.9 Other government expenditures 100.0 103.2 99.7 113.9 113.8 106.6 114.1 114.6 119.9 110.5 104.4 Government administrative services 100.0 104.2 108.1 111.7 116.4 120.4 124.0 127.4 131.6 135.0 139.1 General agricultural pro- grams 100.0 106.8 111.6 116.1 120.8 126.5 138.0 141.1 149.9 155.7 164.4 Forestry 100.0 100.4 102.7 102.2 103.7 104.4 103.5 103.9 105.3 105.3 105.8 134.3 152.9 146.0 State administration and the administrative or- gans of social organiza- tions 100.0 103.3 107.0 110.4 115.0 118.8 121.3 124.0 127.2 130.6 Culture 100.0 106.9 111.5 116.7 123.0 127.9 132.8 140.3 146.1 149.2 Municipal services 100.0 105.9 111.1 115.2 120.0 124.4 127.4 132.0 137.6 141.9 Civilian police 100.0 103.3 107.0 110.4 115.0 118.8 121.3 124.0 127.2 130.6 134.3 Research and development 100.0 106.7 114.6 122.4 127.8 134.1 136.1 139.6 144.5 150.7 157.2 Outlays n.e.c. 100.0 102.0 93.7 112.2 109.3 95.8 105.9 104.8 110.4 93.7 81.8 Gross national product 100.0 103.9 105.9 113.6 118.0 120.0 125.7 129.7 134.1 135.2 137.1 81 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix B Sector-of-Origin Indexes Industry The derivation of the production index for each branch of industry, except for the other industry branch, is described by Ray Converse in JEC, Indus- try. The 1970 established-price weights for the branches of industry are derived in appendix D, table D-7, and the factor-cost weights are derived in appen- dix E. The index for the other industry branch is assumed to be equal to the index for total industry and is computed as a weighted average of the other 10 branches. The indexes for total industry and for all branches of industry are reproduced in appendix A, table A-5. Construction Scope and Coverage The construction sector in Soviet statistics includes new construction and capital repair of buildings and structures, oil and gas well drilling, design work connected with the construction and capital repair of buildings and structures, and geological survey work (USSR Gosplan, Metodicheskiye ukazaniye k sos- tavleniyu gosudarstvennogo plana razvitiya narod- nogo khozyaystvo SSSR, Moscow, Ekonomika, 1969, pp. 746-748, hereafter referred to as Ukazaniya). All construction activity is included regardless of whether it is performed by contract organizations or on force account. In recent years, about 90 percent of con- struction-installation work has been performed by contract organizations. In contrast to Western ac- counting practice, new construction and capital repair in the USSR include the cost of installing machinery and equipment. The United States uses the double deflation method to compute a value-added index in constant prices. Gross output in current prices is deflated using price indexes for several types of construction. Then materi- al inputs in current prices are deflated by a price 83 index constructed as a weighted average of price indexes for the various materials used by the construc- tion sector. Subtracting the deflated material pur- chases from the deflated gross output produces value added in constant prices. Price changes are notoriously difficult to measure in construction because there are few standard products for which comparable prices exist. The Soviet Union probably collects more data on construction costs than most nations, but has not published a price index, much less one backed by sufficient data for independ- ent testing. The lack of standard products makes it impossible to construct a physical output index. Faced with the same lack of Soviet data, Powell constructed a material-input index, consisting of a price-weighted average of the production of 28 types of construction materials, to measure real changes in the gross output of construction (Raymond P. Powell, "An Index of Soviet Construction, 1927/28 to 1955," The Review of Economics and Statistics 41, May 1959, pp. 170- 177). The same basic approach is used here. Input- output data for 1972 are used to derive weights for the purchase of 54 types of materials by the construction sector. Similar data for 1959 and 1966 are used to estimate changes in the share of the production of each material purchased by construction over time. The share for each year is combined with the corre- sponding production index to form an index of pur- chases of that type of material by construction. The construction output index is a weighted average of the 54 purchase indexes. This approach assumes that the ratio of material inputs to gross output is constant. The validity of this approach depends on the manner in which productivi- ty gains have been introduced. Productivity growth can influence the output of a sector through higher quality material inputs or through the better use of labor and capital resources. If the use of improved Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 materials permits a smaller value of materials to be used per unit of construction, then the ratio of material inputs to gross output would decline. On the other hand, if the use of improved materials permits the substitution of materials for labor and capital, then the ratio of material inputs to gross output would rise. The Soviet Union has published values for the gross output and net material product (NMP) of the construction sector for 1964-78 in current prices. The ratio of material inputs (gross output less NMP) to gross output declined slowly in this period (from 57 percent in 1964 to 54 percent in 1978), suggesting that the material-input approach is reasonably valid. This conclusion depends on the relative price stability between gross output and material inputs. The avail- able evidence does not suggest a divergence in the prices of construction output and its inputs. In addi- tion, US data show a stable ratio of material inputs to gross output in constant prices, ranging between 52 percent and 55 percent, since 1950. International comparisons are hazardous, but this stability also lends support to the use of a material-input index. Weights The weights used to combine the purchase indexes are derived from the 1972 Soviet input-output table. The construction column in that table enumerates the ruble value of purchases from each of 75 input-output sectors. The 1972 input-output table is available with 88 sectors. In order to make comparisons with the 1959 and 1966 input-output tables, however, tables in comparable 75-sector formats were used. The con- struction sector did not purchase any materials from 11 of these sectors in 1972. Production indexes are not available for an additional 10 sectors. The purchases by the construction sector from the remaining 54 sectors were summed and converted into percentage weights (table B-1). The construction sector purchased over half of its inputs from just two sectors�construc- tion materials and transportation and communica- tions. A desirable development would be to disaggre- gate the construction materials sector. The data needed to compute the purchase indexes for the separate construction materials sectors for other years, however, are not available. Description of the Index The construction index is a weighted average of 54 purchase indexes, each showing the purchases by construction from the input-output sectors listed in table B-1. Each purchase index is computed in a two- step procedure. First, the shares of the gross output of each of the 54 sectors sold to construction were computed from the 1959, 1966, and 1972 Soviet input-output tables. It is assumed that the rate of change in these shares between 1959 and 1966 and between 1966 and 1972 was linear. It is assumed also that there was no change in the shares before 1959 or after 1972. The resulting time series shows the share of each sector's gross output sold to construction. Second, the shares so derived were multiplied by the production index for that sector to arrive at an index of purchases by construction from each sector. Each purchase index was rebased so that 1972 = 100. A sample computation of a purchase index is shown in table B-2. To form the construction index, the 54 purchase indexes are multiplied by their corresponding weights from table B-1, and the products are added. The resulting index is shown in column 2 of table B-3. All but four of the 54 production indexes are for industrial sectors and were obtained from the index of industrial production described by Ray Converse in JEC, Industry. The indexes for the crops and animal husbandry sectors were derived from the data con- tained in the index of agricultural output as described by Margaret Hughes and Barbara Severin in JEC, Agriculture. The index for the transportation and communications sector is the index for freight trans- portation derived below in this appendix. The index for the trade sector is the index for wholesale trade derived below in this appendix. Although the material-input method is theoretically less desirable than either the gross output or double deflation method, it appears to produce reasonable results and to be the best available method given the data constraints. The material-input index can be 84 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-1 1972 Construction Input Weights Input-Output Sector Purchases by Con- Share of struction (thousand Purchases rubles, producers' (percent) prices) Input-Output Sector Purchases by Con- Share of struct ion (thousand Purchases rubles, producers' (percent) prices) Ferrous metals 3,103,673 8.6 Basic chemical products 129,655 0.4 Nonferrous metals 205,220 0.6 Aniline dye products 31,056 0.1 Refractory materials 165,739 0.5 Coal 105,696 0.3 Oil extraction 13,358 a Oil refining Gas Synthetic resins and plastics 41,847 0.1 Synthetic fibers 2,980 566,432 1.6 Organic-synthetic 25,594 0.1 a products 16,550 Peat 6,897 Oil shales 7,591 a a Electric power 504,205 1.4 Energy and power m&e b 35,779 0.1 Electrotechnical m&e 494,980 1.4 Machine tools 9,753 Forge-pressing m&e 2,458 a Precision instruments 52,269 0.1 Mining and metallurgical 240,970 0.7 m&e Pumps and chemical equipment 35,591 0.1 Logging and paper m&e 11,817 a Hoisting and transport equipment 67,871 0.2 Paint and lacquer 610,260 1.7 Rubber products 313,506 0.9 Other chemical products 132,410 0.4 Logging 437,967 1.2 Sawmill and lumber products 3,206,976 8.9 Furniture Paper and pulp Wood chemistry 26,348 79,506 4,031 Construction materials Glass Textiles Sewn goods Other light industry 12,621,215 379,175 187,357 375,049 69,220 Meat products 11,018 0.1 0.2 34.9 1.0 0.5 1.0 0.2 Construction m&e 198,056 0.5 Transport m&e 7,942 a Dairy products 7,025 Flour and bread 947 Automobiles 329,658 0.9 Agricultural m&e 148,592 0.4 Radioelectronics and other machine building 412,753 1.1 Sanitary engineering 1,131,383 products Other foods Crops 86,257 34,820 Animal husbandry 11,718 Transportation and 3.1 communications Other metalwares 540,714 1.5 Metal structures 1,713,501 4.7 Repair of m&e 914,314 2.5 5,841,370 0.2 0.1 16.1 Trade and distribution 465,452 1.3 Total 36,176,521 100.0 a = Less than 0.05 percent. b m&e = machinery and equipment. Source: Dimitri M. Gallik, Barry L. Kostinskiy, and Vladimir G. Treml, Input-Output Structure of the Soviet Economy: 1972, US Department of Commerce, Bureau of the Census, Washington, D.C., forthcoming. 85 83-892 0 - 82 - Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-2 Derivation of the Index of Purchases of Construction Materials by the Construction Sector Year Year (1) Percent Gross Output of Con- struction Mate- rials Sold to Construction (2) Construction Ma- terials Production (Index: 1972=100) (3) Purchases of Construction Ma- terials (Index: 1972=100) (1) Percent Gross Output of Con- struction Mate- rials Sold to Construction (2) Construction Ma- terials Production (Index: 1972=100) (3) Purchases of Construction Ma- terials (Index: 1972=100) 1950 74.55 10.1 9.8 1966 75.17 71.4 70.0 1951 74.55 12.2 11.9 1967 75.43 77.1 75.8 1952 74.55 14.3 13.9 1968 75.69 80.2 79.1 1953 74.55 16.5 16.0 1969 75.95 81.9 81.0 1954 74.55 19.3 18.7 1970 76.21 88.9 88.3 1955 74.55 23.2 22.5 1971 76.47 95.3 94.9 1956 74.55 26.0 25.2 1972 76.73 100.0 100.0 1957 74.55 30.6 29.7 1973 76.73 106.0 106.0 1958 74.55 37.1 36.1 1974 76.73 110.9 110.9 1959 74.55 43.3 42.0 1975 76.73 115.3 115.3 1960 74.63 49.1 47.8 1976 76.73 119.5 119.5 1961 74.72 53.5 52.1 1977 76.73 121.2 121.2 1962 74.81 56.4 55.0 1978 76.73 123.9 123.9 1963 74.90 58.3 57.0 1979 76.73 123.8 123.8 1964 74.99 61.0 59.6 1980 76.73 125.1 125.1 1965 75.08 66.0 64.6 Sources: Column 1: 1959, 1966, and 1972 are calculated from the respective input-output tables. These tables are published in Dimitri M. Gallik, Barry L. Kostinskiy, and Vladimir G. Treml, Conversion of Soviet Input-Output Tables to Producers' Prices: The 1959 Reconstructed Table, Foreign Economic Report 6, US Department of Commerce, Bureau of Economic Analysis, Washington D.C., 1975; Vladimir G. Treml, Dimitri M. Gallik, and Barry L. Kostinskiy, "1966 Ex-Post Input-Output Tables for the USSR: A Survey," in Vladimir G. Treml, ed., Studies in Soviet Input-Output Analysis, Praeger Publishers, New York, 1977, pp. 1-67; and Dimitri M. Gallik, Barry L. Kostinskiy, and Vladimir G. Treml, checked for reasonableness by comparing the gross output of the construction sector in current prices, as published in the Narkhoz, with our index in 1970 prices and computing the implicit annual price changes and implicit price index (table B-3). On the whole, the implicit price index is reasonable. It shows price declines in the early 1950s, especially in 1955, which conform with Soviet claims of price reductions. After 1955 there is a pattern of moderate price increases with two large increases in 1967 and 1969. The 1967 industrial price reform raised the prices of Input-Output Structure of the Soviet Economy: 1972, US Depart- ment of Commerce, Bureau of the Census, Washington, D.C., forthcoming. The values for 1950-58 are assumed to be equal to the 1959 value, and the values for 1973-80 are assumed to be equal to the 1972 value. The 1960-65 and 1967-71 values are linearly interpolated. Column 2: This was derived from the index of industrial production described by Ray Converse in JEC, Industry. Column 3: This is column 1 times column 2, rebased so that 1972=100. construction materials, and construction prices were explicitly increased in 1969. Since 1970 remarkably little price change is indicated. A second test compares an implicit price index de- rived from Soviet data with the price index derived in table B-3. First, a series showing expenditures on new construction and other capital outlays in current prices was derived by subtracting current-price esti- mates of capital repair of buildings and structures 86 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-3 Table B-4 Derivation of the Implicit Construction Price Index Year (1) Gross Output of Construc- tion (billion rubles) (2) Material- Input Construc- tion Index (1970 = 100) (3) Implicit Annual Price Change (percent) (4) Implicit Price Index (1970=100) 1950 12.1 20.4 NA 88.1 1951 13.6 23.3 -1.9 86.4 1952 15.3 25.7 2.2 88.3 1953 16.1 28.3 -4.8 84.1 1954 18.2 31.5 1.2 85.2 1955 18.4 35.7 -10.4 76.3 1956 20.3 38.9 1.4 77.4 1957 22.6 43.1 0.3 77.7 1958 25.7 48.7 0.4 78.0 1959 29.2 54.7 1.1 78.9 1960 31.9 58.9 1.6 80.1 1961 32.7 62.0 -2.6 78.1 1962 33.6 64.9 -1.9 76.6 1963 34.7 67.4 -0.6 76.1 1964 36.6 70.9 0.4 76.4 1965 40.3 75.3 3.6 79.2 1966 43.0 78.8 2.0 80.7 1967 50.0 84.8 8.0 87.2 1968 53.0 89.3 0.7 87.8 1969 60.0 92.8 8.8 95.6 1970 67.6 100.0 4.6 100.0 1971 74.7 106.7 3.6 103.6 1972 77.4 112.2 -1.5 102.0 1973 80.9 118.8 -1.3 100.8 1974 86.4 125.0 1.5 102.2 1975 91.7 131.2 1.1 103.4 1976 94.2 135.6 -0.6 102.7 1977 96.2 138.9 -0.2 102.5 1978 99.2 143.0 0.1 102.6 1979 NA 144.1 NA NA 1980 NA 147.7 NA NA Sources: Column 1: 1958-78 are from Narkhoz 1978, p. 41, and similar tables in other issues. 1950-57 are derived by linking a series of estimates of construction-installation work in current prices developed by Moorsteen and Powell (The Soviet Capital Stock, 1928-1962, p. 395, table A-7, columns 5 plus 8) to the 1958 value. Column 2: This was described in the text. Columns 3 and 4: Both were derived from a comparison of columns 1 and 2. 87 Derivation of an Implicit Price Index for Investment in New Construction and Other Capital Outlays Year (1) New Construc- tion and Other Capital Outlays (billion rubles) (2) (3) (4) Investment Implicit Implicit in New Annual Price Construe- Price Index tion Change (1970=100) (billion 1969 (percent) rubles) 1961 27.9 32.2 NA 82.2 1962 28.7 32.8 1.0 83.0 1963 29.6 33.8 0 83.0 1964 31.0 36.2 -2.1 81.3 1965 34.7 39.5 2.4 83.2 1966 36.8 42.5 -1.3 82.1 1967 43.4 46.1 8.8 89.3 1968 46.1 49.7 -1.5 88.0 1969 52.6 51.1 11.0 97.7 1970 59.8 56.7 2.4 100.0 1971 65.9 61.4 1.7 101.7 1972 68.1 65.5 -3.0 98.6 1973 70.8 67.6 0.7 99.3 1974 75.2 71.6 0.2 99.5 1975 79.3 76.4 -1.1 98.4 1976 80.7 77.9 -0.2 98.2 1977 81.5 79.9 -1.6 96.7 1978 83.2 83.8 -2.6 94.1 Sources: Column 1: This was derived from table B-3, column 1 less capital repair of buildings and structures (table C-2, column 2). Column 2: This was taken from Narkhoz 1972, p. 474, and similar tables in other issues. Columns 3 and 4: These were derived from a comparison of columns 1 and 2. from the current-price gross output series in table B-3. (See appendix C for the derivation of the capital repair series in current prices.) The resulting series is compared with the Narkhoz series on investment in new construction and other capital outlays in constant prices (table B-4). The implicit price index derived from this camparison (column 4 of table B-4) matches the index derived in table B-3 closely, especially the large price increases in 1967 and 1969. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-5 Selected Purchases by Agriculture of Material Inputs From Nonagricultural Sectors in 1972 Material-Input Category Input-Output Sector Purchases by Agriculture (thousand rubles, purchasers' prices) Share of Purchases (percent) Mineral fertilizer 2,102,579 16.3 Mineral chemistry products 59,649 Basic chemistry products 1,722,868 Organic synthetic products 12,570 Other chemicals 307,492 Electric power Electric power 317,298 2.5 Fuel and lubricants Oil refining 2,240,049 17.3 Machinery repair 3,993,145 30.9 Metallurgy 97,585 Machine building and metalworking 3,895,560 Fish meal Fish products 397,966 3.1 Bone meal Meat products 191,769 1.5 Milling byproducts Flour and cereals 2,758,112 21.3 Oilseed meal 168,282 1.3 Vegetable products 57,336 Other foods 110,946 Skim milk Dairy products 608,679 4.7 Sugar beets Sugar 151,593 1.2 Total 12,929,472 100.0 Source: See table B-1 for a reference to the 1972 input-output data. Agriculture Scope and Coverage The index of net agricultural production described by Margaret Hughes and Barbara Severin (JEC, Agri- culture) represents the gross value of agricultural output less the value of that output used within agriculture. In order to compute a value-added index for agriculture, it is necessary to subtract also the value of the materials and services purchased by agriculture on current account from nonagricultural sectors. This subtraction is described here. The index of purchases from nonagricultural sectors is by design a material-input index similar to the con- struction index described above. We have been able to construct indexes of 10 types of materials purchased by agriculture. These indexes are combined using weights derived from the 1972 Soviet input-output table. Weights Table B-5 shows the derivation of the weights used to combine the 10 indexes of material inputs purchased from nonagricultural sectors. The 1972 Soviet input- output table shows agriculture's purchases from all sectors. Those purchases which relate to each of the 10 material-input indexes were summed and convert- ed to percentage weights. The purchases selected in this manner represent 71 percent of agriculture's purchases from nonagricultural sectors in 1972. The most important types of inputs are fuel, machinery repair, and milling byproducts. 88 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-6 Derivation of the Index of Purchases of Nonagricultural Material Inputs by Agriculture Index: 1972= 100 Year Mineral Fertil- izer Electric Power Fuel and Lubri- cants Bone Meal Skim Milk Sugar Beets Total Current Purchases Machin- cry Repair Fish Meal Milling Byprod- ucts Oilseed Meal 1950 8.9 2.1 25.9 24.4 2.2 5.0 24.4 33.5 31.1 23.8 21.0 1951 9.5 2.6 28.4 26.8 3.3 5.5 27.8 40.7 32.9 30.6 23.4 1952 10.2 3.1 29.0 27.4 3.7 6.6 31.6 43.1 34.4 36.3 24.8 1953 1954 10.9 3.8 34.4 32.5 4.4 8.0 36.0 45.7 35.4 34.2 28.5 29.4 32.6 12.4 4.8 33.7 31.8 5.5 9.4 40.0 51.2 36.0 35.6 1955 14.0 6.1 37.4 35.3 6.6 10.2 44.3 47.3 42.9 30.3 1956 15.7 7.3 40.8 38.5 7.5 11.3 43.5 57.2 51.6 47.7 35.1 1957 17.2 9.1 45.1 42.5 7.9 13.5 47.4 61.7 58.8 48.9 38.7 41.3 44.1 1958 17.9 11.6 49.2 46.4 9.6 14.9 49.1 53.7 61.0 59.9 1959 18.5 14.3 51.9 48.9 12.7 18.2 51.6 64.2 66.8 79.3 64.3 1960 19.1 16.3 54.4 51.3 18.6 18.8 53.9 58.4 68.2 45.8 1961 20.3 19.2 57.6 54.4 23.0 21.0 62.4 60.2 72.3 81.1 50.0 1962 23.1 22.6 64.2 58.4 24.6 27.9 68.4 71.6 76.9 74.2 54.7 55.5 59.9 1963 27.8 25.5 66.8 65.0 30.5 35.6 56.5 73.1 71.9 68.3 1964 37.0 29.3 71.8 68.4 38.6 32.6 58.5 77.9 78.3 64.4 1965 46.2 34.7 74.7 73.5 52.0 45.3 68.5 86.0 99.3 118.3 68.1 73.3 1966 52.5 38.4 76.2 80.1 58.1 54.4 76.5 90.6 96.5 104.9 1967 58.4 44.1 79.2 86.6 71.3 65.5 81.6 99.8 98.1 108.4 78.8 1968 63.3 51.8 82.5 87.9 76.3 71.5 86.4 100.3 96.7 126.8 82.2 1969 69.1 61.3 86.1 90.3 82.0 68.0 88.9 100.9 88.3 130.8 85.0 88.6 1970 82.0 72.2 89.4 90.5 86.2 73.8 92.8 90.4 89.2 101.5 111.0 1971 1972 1973 92.1 85.9 94.8 93.3 93.6 90.3 93.3 97.7 94.6 93.5 100.0 107.6 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 110.1 114.6 105.5 109.8 111.0 101.7 101.7 107.8 114.7 105.8 120.9 104.9 1974 122.0 132.9 111.4 120.2 124.6 119.6 103.5 98.8 116.7 115.4 124.2 122.3 132.6 135.9 1975 1976 137.8 152.1 119.8 132.1 143.6 132.0 104.9 90.8 114.0 140.7 173.2 125.7 137.6 137.1 118.0 79.7 100.6 116.9 96.2 1977 145.6 184.7 131.3 142.5 127.0 124.6 107.0 104.9 130.4 132.4 1978 148.7 200.2 138.9 149.3 115.4 131.2 105.0 95.7 127.9 131.9 1979 146.4 215.8 146.8 151.0 112.1 134.0 111.2 92.2 122.7 124.5 107.7 138.8 144.1 1980 157.4 231.3 155.2 155.1 123.7 133.4 112.9 98.3 118.2 Source: See text. Description of the Index Table B-6 shows the construction of the index of agriculture's purchases of nonagricultural materials. It is a weighted average of 10 indexes of separate types of materials. The indexes are derived partly from data published in the Narkhoz and partly from 89 data gathered from Soviet monographs on agricul- ture. In particular, data for agriculture's use of mineral fertilizer and electric power are published in the Narkhoz. The index of use of skim milk is assumed to equal the index of industrially produced Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-7 Derivation of the Index of Value Added in Agriculture (5) Value Added (billion 1972 rubles) (6) Index of Value Added (1970=100) Year (1) Net Output (billion 1970 rubles) (2) Index of Column 1 (1972=100) (3) Net Output (billion 1972 rubles) (4) Nonagricultural Material Inputs (billion 1972 rubles) 1950 38.1 48.5 41.2 3.9 37.3 50.4 1951 35.8 45.5 38.6 4.3 34.4 46.4 1952 37.6 47.9 40.7 4.5 36.1 48.8 1953 40.3 51.3 43.5 5.2 38.3 51.7 1954 41.2 52.4 44.5 5.4 39.1 52.8 1955 46.5 59.2 50.2 6.0 44.3 59.8 1956 52.9 67.4 57.2 6.4 50.8 68.6 1957 52.9 67.3 57.1 7.1 50.0 67.6 1958 57.2 72.8 61.8 7.6 54.2 73.2 1959 58.7 74.7 63.4 8.1 55.3 74.7 1960 58.0 73.8 62.6 8.4 54.3 73.3 1961 62.1 79.1 67.1 9.2 58.0 78.3 1962 61.3 78.1 66.2 10.0 56.2 75.9 1963 50.6 64.5 54.7 10.2 44.5 60.2 1964 64.6 82.3 69.8 11.0 58.8 79.5 1965 69.2 88.1 74.7 12.5 62.3 84.1 1966 72.3 92.1 78.1 13.4 64.7 87.4 1967 72.3 92.1 78.1 14.4 63.7 86.0 1968 76.6 97.5 82.7 15.1 67.7 91.4 1969 74.3 94.6 80.3 15.6 64.7 87.4 1970 83.6 106.4 90.3 16.2 74.0 100.0 1971 83.2 105.9 89.9 17.1 72.8 98.3 1972 78.5 100.0 84.8 18.3 66.5 89.9 1973 90.1 114.7 97.3 19.7 77.6 104.8 1974 89.8 114.4 97.1 21.1 75.9 102.5 1975 82.0 104.4 88.6 22.8 65.8 88.9 1976 88.6 112.9 95.8 22.4 73.4 99.1 1977 92.8 118.1 100.2 24.3 75.9 102.5 1978 95.8 121.9 103.5 24.9 78.6 106.1 1979 90.2 114.8 97.4 25.4 72.0 97.3 1980 86.3 109.8 93.2 26.4 66.8 90.2 Sources: Column 1: This is from JEC, Agriculture, table A-1. Column 2: This is column 1 converted to index form (1972=100). Column 3: This is column 2 multiplied by the base-year (1972) value of 84.8 billion rubles. The derivation of the base-year value is described in the text. Column 4: This is column 11 of table B-6 multiplied by the base-year (1972) value of 18.3 billion rubles. The derivation of the base-year value is described in the text. Column 5: This is column 3 less column 4. Column 6: This is column 5 converted to index form (1970=100). 90 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 butter, and the index of sugar beets is assumed to equal the index of state procurements of sugar beets. The other indexes are estimated from a variety of sources. The detailed derivation of each index is too extensive to present here. Table B-7 shows the computation of the index of value added in agriculture. This calculation also is based on the 1972 input-output table. First an index of net agricultural output is computed in 1972 prices by multiplying the 1972 value derived from the input- output table by the index derived by Hughes and Severin in 1970 prices (JEC, Agriculture, table A-1) The 1972 value of net agricultural output is computed as follows: Billion Rubles Gross output of agriculture in 114.7 purchasers' prices Less: Purchases from the trade sector 4.6 Less: Purchases from the transporta- 1.4 tion and communiciations sector Less: Purchases from the agriculture 23.9 sector Equals: Net agricultural output 84.8 Similarly, the index of nonagricultural material in- puts is expressed in 1972 prices by multiplying it by the 1972 value of such purchases, 18.3 billion rubles. This value can be derived from the 1972 input-output table as the sum of all purchases from the nonagricul- tural sectors. Subtracting the material-input series from the net output series produces an estimate of value added in agriculture in 1972 rubles which can then be converted to index form. In the general discussion about the problems of measuring the real growth of value added, it was indicated that use of a gross output index may be preferable to the double deflation method unless the difference between the annual growth rates of gross output and the material inputs is 2 percentage points or more. Table B-8 shows the annual growth rates of gross output, total material inputs, and value added for agriculture. It is clear that frequently there is a large gap between the growth rates; therefore, the double deflation procedure described here is prefera- ble for this sector. 91 Table B-8 Annual Percentage Rates of Growth Gross Output, Total Material Purchases, and Value Added in Agriculture Year (1) Gross Output (2) Total Material Inputs (3) Value Added (4) Column 1 Less Column 2 1951 -4.9 3.2 -8.0 -8.1 1.6 -1.3 1952 4.4 2.9 5.1 1953 6.6 7.8 6.0 1954 2.8 4.6 2.0 -1.8 1955 12.7 11.5 13.3 1.2 1956 14.6 14.2 14.7 0.4 1957 1.6 8.8 -1.5 -7.2 0.3 1958 8.2 7.9 8.4 19.59 1.7 0.9 2.1 0.8 1960 -0.3 3.2 -2.0 -3.5 1.1 1961 6.3 5.1 6.9 1962 -0.3 5.4 -3.0 -5.7 1963 -15.1 -4.3 -20.8 -10.9 1964 21.7 4.9 32.1 16.7 0.8 1965 5.4 4.7 5.8 1966 6.7 12.4 4.0 -5.7 1967 0 2.9 -1.6 -2.9 1968 5.3 3.5 6.3 1.8 1969 -1.2 4.6 -4.4 -5.8 1970 11.5 6.7 14.4 4.9 1971 -0.3 2.2 -1.7 -2.5 1972 -5.0 1.2 -8.5 -6.2 1973 15.5 13.6 16.7 1.9 1974 -2.2 -2.3 -2.2 0.1 1975 -7.3 2.2 -13.3 -9.6 1976 8.4 4.4 11.4 4.1 1977 3.3 3.0 3.5 0.3 1978 4.3 5.5 3.5 -1.2 -5.1 1979 -4.8 0.3 -8.3 1980 -5.2 -2.4 -7.3 -2.8 Sources: Column 1: The gross output of agriculture is computed as the sum of the gross outputs of the livestock and crops sectors. The gross output of the livestock sector is published in JEC, Agriculture (table A-1). The gross output of the crops sector is equal to net crops output (ibid) plus the value of seed and waste (unpublished estimates). Column 2: Total material inputs are computed as the sum of non-ag- ricultural material purchases (table B-7, column 4) and agricultural material purchases. The latter (unpublished) is calculated as gross output less net output. Column 3: This was computed from table 8-7, column 6. Column 4: This is column 1 less column 2. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Transportation Scope and Coverage The transportation sector includes enterprises en- gaged in the transportation of freight, passengers, and associated activities by rail, sea, inland water, auto- mobile, air, oil and gas pipeline, urban electric transit, timber rafting, tug service, loading and unloading services, and maintenance of highways (Ukazaniya, pp. 742-745). Our index is a composite of 16 physical series of various types of freight and passenger transportation, aggregated with 1970 revenue weights. The procedure is similar to that used by N. M. Kaplan, Soviet Transport and Communications Output Indexes, 1928-62, Research Memorandum 4264-PR and Sup- plement, Santa Monica, Calif., the Rand Corporation, 1964 and 1965. Comparable results for 1950-63 given by Kaplan and the index derived here are nearly identical. The approach is also comparable to that taken by Kendrick to obtain an output index for transportation as part of an investigation of longrun productivity trends in the United States (John W. Kendrick, Postwar Productivity Trends in the United States, New York, National Bureau of Economic Research, 1973, pp. 186-193). The US GNP accounts also use a gross output index, but one which is primarily deflated current-price data. The coverage of the index is incomplete. Omitted entirely are timber rafting, road maintenance, tug service, and activities of independent enterprises en- gaged in loading and unloading; employment in such omitted activities is estimated to have been about 10 percent of total transport employment in 1970. A special problem arises with respect to freight hauled by trucks. Two physical series are published in the Narkhoz. One relates to common carriers only and the other to total truck haulage in the economy. Most of the trucking activity done by nontransport enterprises is believed to be short-haul work in con- nection with the current operations of the parent enterprise. This type of activity is considered part of the sectors to which the parent enterprise belongs in the US accounts and, therefore, the physical series relating to common carriers only is used here. This results in a lower weight for the truck index, but a higher growth rate. Total transportation revenue is calculated as the sum of freight and passenger revenue. Freight revenue is calculated as the sum of the revenue estimated for each of seven modes�rail, sea, inland water, truck, oil pipeline, air, and gas pipeline. The revenue for each mode is calculated as the product of a physical measure and a 1970 average revenue value. Passenger revenue is calculated as the sum of the revenue estimated for each of nine modes�rail, sea, inland water, bus, air, tram, trolley bus, subway, and taxi. The passenger index is virtually the same as the transportation component of the consumption index; its construction is described by Schroeder and Denton (JEC, Consumption). The only difference is that business travel expenses are not deducted for the sector-of-origin index. Weights The weights used to aggregate the seven freight subindexes are 1970 average revenue rates per ton- kilometer (tkm) (for gas pipelines, average revenue per cubic meter of gas transported). The weights and their sources are as follows: Mode Average Rate Source (kopecks) Rail 0.400 per ton- kilometer (tkm) Transport i svyaz', p. 111. Sea 0.263 per tkm Ibid, p. 151. Inland water 0.418 per tkm Ibid, p. 186. Truck 7.05 per tkm Oil pipeline 0.123 per tkm Ibid, pp. 222, 251. Ibid, p. 203 with 28- percent profit markup added. Air 15.63 per tkm See text. Gas pipeline 0.258 per cubic meter R. D. Margulov et al, Razvitiya gazovoy pro- myshlennosti, Moscow, Nedra, 1976, p. 11 with a 28-percent profit mark- up added. 92 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The average air revenue rate in 1970 was obtained by adding an arbitrary profit markup of 25 percent to the estimated 1970 average cost of 12.5 kopecks per tkm. An average cost of 17.7 kopecks per tkm in 1965 is given in N. N. Barkov, ed., Zheleznedorozhniy trans- port v sisteme edinoy transportnoy seti USSR, Mos- cow, Transport, 1967, p. 51. The average cost for 1965 was extrapolated forward to 1970 using the average rate of decrease of 7 percent per year calcu- lated from data for 1958-68 published in Flight International, 25 September 1969, p. 485. Description of the Index The physical data for freight transportation are shown in table B-9.The resulting values for gross revenue of freight, passenger, and total transportation are shown in table B-10 in ruble and index format. The sources for the freight transportation data are as follows: Mode Physical Measure Sources Rail, inland water, Ton-kilometers Transport i svyaz', p. 17, sea, air, and oil and similar tables in pipeline Narkhozy for subse- quent years. Truck Ton-kilometers Ibid, p. 222, and similar tables in Narkhozy for subsequent years. Gas pipeline Cubic meters Ibid, p. 204, and similar tables in Narkhozy for subsequent years. Ideally, the physical series for gas pipelines should take account of the increasing average distance that gas is transported as a result of the exploitation of Siberian fields. Unfortunately, we do not have suffi- cient data to estimate changes in the average distance transported. Hence, no adjustment is made to the gas pipeline index. Communications The index used for the communications sector is identical to that used for the communications compo- nent of the consumption index. The methodology and data used are described by Schroeder and Denton in JEC, Consumption. 93 Trade Scope and Coverage The trade sector in Soviet statistics encompasses a range of activity roughly equivalent to the wholesale and retail trade sectors in the US classification. Included are: retail trade, public dining, foreign trade, film rentals, material-technical supply (concerned with supplying production enterprises and farms), wholesale trade (concerned with supplying consumer goods to retail trade outlets), and agricultural pro- curement (concerned with state purchasing of farm products from producers). For a more detailed de- scription, see Ukazaniya, pp. 748-751. The index of value added in the trade sector is based on the assumption that value added is correlated with the volume of goods processed by the trade sector. The trade sector is divided into three major branches (retail trade, wholesale trade which includes material- technical supply, and agricultural procurement), and an index is computed of the value in 1970 prices of goods processed by each branch. The trade index is a weighted average of the three branch indexes. The weights are the value added of each branch in 1970. The coverage of the trade index is nearly complete. There is no explicit measurement of the activity associated with foreign trade, but much of this activi- ty is probably captured in the retail and wholesale trade indexes. Film rentals are not included, but the value added associated with them is tiny. The retail trade index implicitly includes the activities of public dining enterprises. An alternative procedure, used in the US accounts, is to deflate the current-price value of sales in the various trade channels. It is not employed here be- cause of the lack of reliable price deflators. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-9 Data Relating to the Activity of Various Modes of Freight Transportation Year (1) Rail (billion tkm) (2) Sea (billion tkm) (3) Inland Water (billion tkm) (4) Oil Pipeline (billion tkm) (5) Truck (billion tkm) (6) Air (billion tkm) (7) Gas Pipeline (billion cubic meters) 1950 602.3 39.7 46.2 4.9 0.9 0.14 1.5 1951 677.3 40.3 51.9 5.5 1.1 0.18 1.8 1952 741.3 44.3 58.2 6.4 1.2 0.20 2.1 1953 798.0 48.2 59.3 7.6 2.5 0.22 2.5 1954 856.8 56.6 62.8 10.2 4.2 0.24 3.0 1955 970.9 68.9 67.7 14.7 9.3 0.25 3.5 1956 1,079.1 82.4 70.5 20.5 11.9 0.31 6.0 1957 1,212.8 92.7 76.4 26.6 15.0 0.34 10.3 1958 1,302.0 106.3 85.5 33.8 18.4 0.40 17.8 1959 1,429.5 115.7 93.6 41.6 22.2 0.44 23.6 1960 1,504.3 131.5 99.6 51.2 27.2 0.56 32.8 1961 1,566.6 159.1 106.0 60.0 29.3 0.80 45.8 1962 1,646.3 173.4 109.9 74.5 31.7 0.89 60.3 1963 1,749.4 226.3 114.5 90.9 34.1 0.91 80.0 1964 1,854.1 297.6 124.5 112.1 38.7 1.14 97.9 1965 1,950.2 388.8 133.9 146.7 50.2 1.34 112.1 1966 2,016.0 442.8 137.7 165.0 52.2 1.45 128.8 1967 2,160.5 527.1 143.9 183.4 55.8 1.66 143.3 1968 2,274.8 586.8 155.4 215.9 57.5 1.80 155.1 1969 2,367.1 601.3 160.1 244.6 59.7 1.95 166.0 1970 2,494.7 656.1 174.0 281.7 64.2 1.88 181.5 1971 2,637.3 696.0 183.8 328.5 68.9 1.98 209.8 1972 2,760.8 698.4 180.3 375.9 73.6 2.19 219.9 1973 2,958.0 750.7 189.5 439.4 80.9 2.37 231.1 1974 3,097.7 778.1 212.3 533.4 89.2 2.49 245.7 1975 3,236.5 736.3 221.7 665.9 96.9 2.59 279.4 1976 3,295.4 762.2 222.7 794.6 102.6 2.71 309.5 1977 3,330.9 772.6 230.7 922.4 109.3 2.80 334.6 1978 3,429.4 827.6 243.7 1,049.1 115.8 2.86 351.1 1979 3,349.3 851.1 232.7 1,140.7 123.0 2.91 378.0 1980 3,435.0 848.3 244.7 1,216.0 130.7 3.09 417.7 Sources: See text. 94 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-10 Derivation of the Index of Value Added in Transportation Year (6) (1) (2) Freight Transportation (3) (4) Personal Transportation (5) Total Transportation Billion 1970 Rubles Index (1970=100) Billion 1970 Rubles Index (1970=100) Billion 1970 Rubles Index (1970=100) 1950 2.8 15.5 1.2 15.3 4.0 15.5 1951 3.1 17.4 1.3 17.1 4.5 17.3 19.0 1952 3.5 19.1 1.5 18.7 4.9 1953 3.8 21.0 1.6 20.9 5.4 21.0 1954 4.2 23.2 1.8 23.2 6.0 23.2 1955 5.1 28.1 2.0 26.4 7.1 27.6 1956 5.8 31.9 2.2 27.8 7.9 30.7 1957 6.6 36.4 2.4 31.3 9.0 34.9 1958 7.3 40.4 2.7 34.4 10.0 38.6 42.9 47.0 1959 8.2 45.2 2.9 37.5 11.1 1960 8.9 49.4 3.2 41.4 12.1 1961 9.5 52.6 3.5 45.2 13.0 50.4 1962 10.1 56.0 3.9 50.7 14.0 54.4 1963 10.9 60.5 4.3 55.4 15.2 59.0 64.4 1964 12.0 66.5 4.6 59.6 16.6 1965 13.6 75.3 5.0 64.9 18.6 72.2 1966 14.2 78.8 5.6 72.2 19.8 76.9 83.6 1967 15.4 85.3 6.1 79.4 21.6 1968 16.3 90.2 6.7 87.3 23.0 89.3 93.8 1969 17.0 93.9 7.2 93.7 24.2 1970 18.1 100.0 7.7 100.0 25.8 100.0 1971 19.3 106.6 8.3 107.0 27.5 106.7 112.6 1972 20.2 111.8 8.9 114.5 29.1 1973 21.8 120.7 9.3 120.6 31.1 120.7 1974 23.3 128.9 10.0 129.7 33.3 129.2 1975 24.6 136.1 10.8 139.3 35.4 137.0 1976 25.5 141.4 11.4 146.8 36.9 143.0 1977 26.5 146.5 11.3 145.6 37.7 146.2 1978 27.7 153.4 11.7 151.8 39.5 152.9 1979 28.1 155.6 12.3 158.5 40.4 156.5 1980 29.2 161.8 12.7 164.2 41.9 162.5 Sources: Column 1: For each year, the physical value in each column in table B-9 is multiplied by the average revenue rate given in the text and the results are summed. Column 2: This is an index of column 1. Column 3: The same procedure is followed as for column 1. 95 The physical values and the average revenue weights are given in JEC, Consumption. Column 4: This is an index of column 3. Column 5: This is column 1 plus column 3. Column 6: This is an index of column 5. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Weights Value added in the trade sector in 1970 is derived in appendix D, at 18.273 billion rubles. The value added in each of the three branches of the trade sector is shown in the following tabulation: Distribution of the Value Added Billion Rubles in the Trade Sector, 1970 Total Trade Retail Trade Wholesale Trade Agricultural Procurement Total value added 18.273 11.263 4.826 2.184 Wage bill 8.748 6.436 1.646 0.666 Other and imputed income 0.932 0.686 0.175 0.071 Social insurance 0.395 0.291 0.074 0.030 Depreci- ation 1.323 0.574 0.531 0.218 Profits 6.679 3.359 2.208 1.112 Subsidies -0.530 -0.530 0 0 Miscella- neous charges 0.726 0.447 0.192 0.087 Percent 100.0 61.64 26.41 11.95 The sources for each line item are: Total Value Added. This is derived as the sum of the components. Wage Bill. The total wage bill, 8.748 billion rubles, is divided among the branches using employment data for the USSR and wage data for Estonia. Average wages and employment in Estonia for 1970 for three branches (retail trade, wholesale trade, and public dining; material-technical supply; and agricultural procurement) are given in Narodnoe khozyaystvo Estonskoy SSR v 1972 godu, Tallin, Eesti Raamat, 1973, pp. 219 and 223. These data plus the implied average monthly wage rate for the total trade sector are shown in the tabulation below. Also shown is the ratio of the monthly wages in each of the three branches to the monthly wage rate for the entire trade sector: (1) Employment in Estonia (thousands) (2) Monthly Wages in Estonia (rubles) (3) Ratio of Monthly Wages to Average (percent) Total trade sector 54.2 105.9 100.0 Trade (whole- sale and retail) and public dining 46.1 103.5 97.7 Material- technical supply 6.0 121.5 114.7 Agricultural procurement 2.1 113.9 107.6 It is assumed that the structure of relative monthly wages was the same for the USSR as it was for Estonia. The first column in the tabulation below shows the average monthly wage rates implied by this assumption. They are calculated by multiplying the data in column 3 of the tabulation above by the average monthly wage for the total trade sector for the USSR of 95.1 rubles (Narkhoz 1979, p. 395). Employment in each branch is shown in column 2. Total trade and retail trade employment are given in Narkhoz 1973, pp. 575 and 671. Agricultural pro- curement employment is given in P. I. Vakhrin, Formirovaniye osnovnykh fondov kooperativnoy torgovli, Moscow, Ekonomika, 1974, p. 14. Wholesale trade and material-technical supply employment are derived as a residual. The annual wage bill implied for each branch by the average monthly wage rates and 96 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 employment is shown in column 3. Finally, these data are scaled up in column 4 so that the total wages equal 8.748 billion rubles. (1) Monthly Wages (rubles) (2) (3) Employment Annual (million Wage persons) Bill (billion rubles) (4) Adjusted Wage Bill (billion rubles) Total trade 95.1 sector 7.537 NA 8.748 Retail trade 92.9 and public dining 5.746 6.406 6.436 Wholesale 109.1 trade and material- technical supply 1.251 1.638 1.646 Agricultural 102.3 procurement 0.540 0.663 0.666 Other and Imputed Income. The total, 0.932 billion rubles, was distributed among the branches on the basis of their shares of the wage bill. Social Insurance. The total, 0.395 billion rubles, was distributed among the branches on the basis of their shares of the wage bill. Depreciation. Total depreciation in trade was distrib- uted among the branches on the basis of their relative shares in total amortization deductions as given in Narkhoz 1972, p. 723. The allocation between retail and wholesale trade was made by estimating amorti- zation deductions for wholesale trade and subtracting the result from the amount given for the two branches combined. The estimate for wholesale trade was made by assuming that the ratio of amortization to wages in that branch was the same as in material-technical supply. Profits. Total profits in the branches of trade are given in Narkhoz 1973, pp. 763 and 767. Since the 1970 value-added component for profits represents net profits (CIA, GNP 1970, p. 67), the component representing state enterprise profits (5.396 billion rubles) was distributed among the branches on the 97 basis of their shares in total profits of state enter- prises. Net profits equal total profits less the bonuses paid from profits which are also included in wages. Net profits of consumer cooperatives were included with retail trade and public dining. Subsidies. This item applies only to retail trade. It represents budget reimbursement for losses incurred in sales of slow-moving goods to the population at reduced prices (0.400 billion rubles) and a subsidy on the procurement of fresh vegetables by retail trade (0.130 billion rubles). Description of the Index Retail Trade. The value of total goods flowing through the state and cooperative retail trade network in 1970 prices is derived by deducting the value of collective-farm-market and commission sales and the value of household consumption in kind from our index of personal consumption of food expressed in ruble terms, and then adding ruble estimates of the consumption of soft goods and durables. The resulting series measures household purchases of goods in state and cooperative trade in real terms. Estimates of collective-farm-market sales and house- hold consumption in kind first were derived for the benchmark years of 1950, 1955, 1960, 1966, 1970, 1974, and 1976 as shown in tables B-11 and B-12. The procedure is similar to that used in CIA, GNP 1970. First, physical quantities of seven products sold on collective farm markets and nine products con- sumed in kind by households were estimated for each benchmark year. In general, gross output is divided into the amounts used in production, marketed out- put, and, as a residual, farm household consumption in kind. Collective-farm-market sales are then esti- mated as marketed output less state procurement, decentralized procurement, and the difference, if any, between the physical and accounting weight of pro- curements. Some of the major sources and procedures are indicated in the sources to tables B-11 and B-12. Greater detail is given in CIA, GNP 1970, table A-1, pp. 27-31. The quantities of each product for each Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-11 Valuation of Farm Household Consumption in Kind in 1970 Prices Price (rubles per ton) 1950 1955 1960 1966 1970 1974 1976 Grain 103 Thousand tons 15,000 16,000 10,000 6,000 3,000 3,000 3,000 Billion rubles 1.545 1.648 1.030 0.618 0.309 0.309 0.309 Potatoes 114 Thousand tons 30,000 15,000 16,500 18,600 21,843 17,000 13,932 Billion rubles 3.420 1.710 1.881 2.120 2.490 1.938 1.588 Vegetables 163 Thousand tons 3,175 4,380 5,259 3,686 3,170 2,951 1,606 Billion rubles 0.518 0.714 0.857 0.601 0.517 0.481 0.262 Meat: slaughter weight Thousand tons 2,400 2,700 2,700 3,000 2,878 2,820 2,500 Meat 2,327 Thousand tons 1,956 2,187 2,195 2,403 2,328 2,233 2,043 Billion rubles 4.552 5.089 5.108 5.592 5.418 5.197 4.753 Animal fat 1,900 Thousand tons 365 445 435 519 469 491 382 Billion rubles 0.693 0.846 0.826 0.986 0.891 0.932 0.727 Milk for home produced butter Thousand tons 2,599 2,599 2,509 2,509 2,350 2,260 2,102 Milk 196 Thousand tons 16,701 17,701 22,109 21,783 21,166 20,300 17,656 Billion rubles 3.273 3.469 4.333 4.270 4.148 3.979 3.461 Butter 3,450 Thousand tons 115 115 111 111 104 100 93 Billion rubles . 0.397 0.397 0.383 0.383 0.359 0.345 0.321 Eggs 100� Million 7,755 11,424 15,890 15,335 16,793 18,606 17,169 Billion rubles 0.775 1.142 1.589 1.533 1.679 1.861 1.717 98 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-11 (continued) 1974 1976 Price (rubles per ton) 1950 � 1955 1960 1966 1970 Fruit 282 Thousand tons 1,100 1,000 1,000 1,500 2,000 2,000 2,500 Billion rubles 0.310 0.282 0.282 0.423 0.564 0.564 0.705 Total (billion rubles) 15.483 15.298 16.290 16.526 16.376 15.606 13.842 a The price of eggs is 100 rubles per thousand eggs. Sources for this table: Grain. The quantities are estimated by the general methodology given in CIA, GNP 1970, p. 31. The 1974 and 1976 values are arbitrarily set equal to the 1970 value. The price is given in CIA, GNP 1970, p. 32. Potatoes. The quantities are derived as gross output less the amounts used for seed and marketed output. Gross output and marketed output are given in Narkhoz 1974, pp. 316 and 369, and similar tables in other issues. Seeding rates are derived separately for each year at 19 centners per hectare in 1950, 1955, and 1960; 20 centners per hectare in 1966 and 1974; and 25 centners per hectare in 1970. The price is given in CIA GNP 1970, p. 32. Vegetables. The quantities are derived in the same manner as potatoes. Twenty percent of the gross output is assumed to be fed to livestock. The price is from CIA, GNP 1970, p. 32. Meat. The slaughter weight of meat is derived in detail as described in CIA, GNP 1970, table A-3, p. 38. The slaughter weight is then di- vided into the quantities consumed as meat or animal fat. The percentages of the slaughter weight used for each year are: Meat Animal Fat 1950 81.5 15.2 1955 81.0 16.5 1960 81.3 16.1 1966 80.1 17.3 1970 80.9 16.3 1974 79.2 17.4 1976 81.7 15.3 99 The detailed derivation of these shares and the prices (not presented here) is based on estimates of the quantities and prices of several types of meat. See CIA, GNP 1970, pp. 27-38, for the general procedure used. Milk. The quantities of total milk are derived in the same manner as potatoes. Milk consumed is equal to total milk less the quantity used for butter, calculated at 22.6 tons of milk per ton of butter. The quantities of butter for 1960, 1970, 1974, and 1976 are given in Narkhoz 1974, p. 187, and similar tables in other issues. The quantities for 1950 and 1955 are assumed to be equal to the value published for 1953, and the quantity for 1966 is assumed to be equal to the value published for 1965. The price for milk is from CIA, GNP 1970, p. 34. Thirteen percent of the gross output is assumed to be used in production. Eggs. The quantities are derived in the same manner as potatoes. The number of hatching eggs are calculated as described in CIA, GNP 1970, p. 29. The price is given in CIA, GNP 1970, p. 35. Fruit. The quantities consumed in kind are estimated to be 40 percent of the gross output in 1950, 30 percent in 1955, 20 percent in 1960, 19 percent in 1966, 17 percent in 1970, and 16 percent in 1974. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-12 Valuation of Collective Farm Ex�Village Market and Commission Sales in 1970 Prices Price (rubles per ton) 1950 1955 1960 1966 1970 1974 1976 Grain 248 Thousand tons 3,290 2,330 2,270 2,100 2,004 1,500 1,500 Billion rubles 0.816 0.578 0.563 0.521 0.497 0.372 0.372 Potatoes 179 Thousand tons 6,460 6,530 5,690 5,610 6,002 5,910 5,960 Billion rubles 1.156 1.169 1.019 1.004 1.074 1.058 1.067 Vegetables 381 Thousand tons 1,560 1,940 1,580 1,460 1,781 1,790 1,138 Billion rubles 0.594 0.739 0.602 0.556 0.679 0.682 0.434 Meat: slaughter weight Thousand tons 793 776 686 894 1,093 900 1,060 Meat 2,378 Thousand tons 646 629 558 716 884 713 866 Billion rubles 1.537 1.495 1.326 1.703 2.103 1.695 2.059 Animal fat 1,900 Thousand tons 121 128 110 155 178 157 162 Billion rubles 0.229 0.243 0.210 0.294 0.339 0.298 0.308 Milk 316 Thousand tons 2,420 2,860 1,860 1,360 1,048 910 958 Billion rubles 0.765 0.904 0.588 0.430 0.331 0.288 0.303 Eggs 126a Million 1,370 3,140 3,170 2,780 2,522 2,130 1,963 Billion rubles 0.173 0.396 0.399 0.350 0.318 0.268 0.247 Total (billion rubles) 5.270 5.523 4.707 4.858 5.340 4.660 4.790 a The price of eggs is 126 rubles per thousand eggs. Sources: The quantities for 1950, 1955, and 1960 are taken from Jerzy F. Karcz, "Quantitative Analysis of the Collective Farm Market," American Economic Review 54, June 1964, unpublished appendix. The quantities for 1966 are derived by extending the Karcz series by means of commodity indexes for collective-farm- market sales presented in Narkhoz 1968, p. 654. The quantities for 1970, 1974, and 1976 are calculated as in CIA, GNP 1970�that is, marketed output less all procurements and the difference, if any, between the physical and accounting weight of procurements. The prices are from CIA, GNP 1970, pp. 32-35. 100 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 benchmark year are then multiplied by 1970 prices and summed to obtain total ruble values for collective- farm-market and commission sales and for household consumption in kind. Ruble values for collective-farm-market sales and household consumption in kind for all other years were obtained by interpolation. The ruble values for both consumption categories in each benchmark year were expressed as percentages of the total consump- tion of food. The percentages between each bench- mark year were interpolated based on equal percent- age rates of change. The interpolated percentages were then multiplied by the total consumption of food to obtain ruble values. These calculations and the resulting retail trade index are shown in table B-13. Wholesale Trade. The wholesale trade network serves as an intermediary between industrial enterprises and retail trade enterprises. The material-technical supply system serves as an intermediary between state pro- duction enterprises. The index used to measure both types of activity is a weighted average of nine gross output indexes of branches of industry. All branches except for electric power and "other industry" are included. The industrial production indexes are de- scribed by Ray Converse in JEC, Industry. The derivation of the wholesale trade index is shown in table B-14. The 1970 gross outputs of the nine branches were computed in producers' prices as part of the factor-cost adjustment described in appendix E and are shown in the following tabulation: Estimated Gross Outputs of Selected Branches of Industry, 1970 (Producers' Prices) Billion Rubles Percent Total 363.618 100.00 Ferrous metals 24.702 6.79 Nonferrous metals 12.374 3.40 Fuels 22.442 6.17 Machinery 92.800 25.52 Chemicals 22.414 6.16 Wood, pulp, and paper 19.419 5.34 Construction materials 15.990 4.40 Light industry 62.988 17.32 Food industry 90.489 24.89 101 Agricultural Procurement. The value of 16 agricul- tural products purchased from state and collective farms and from private individuals for use by state production enterprises or retail trade outlets forms our index of agricultural procurement activity. The data exclude decentralized procurement, which in 1970 amounted to only about 4 percent of the value of all slate procurement. The physical series are aggregated with 1970 average procurement prices. The average prices for eight products�grain, potatoes, vegetables, sunflower seeds, meat, milk, wool, and eggs�were calculated directly from data on quantities and prices for the three procurement channels (state farms, collective farms, and individuals) given in CIA, GNP 1970, pp. 32-35. Average procurement prices for the remaining products were obtained as explained and documented in JEC, Agriculture. The derivation of the percentage weights to combine the 16 products is shown in table B-15 and the physical quantities in table B-16. The resulting index is shown in table B-17. The Total Trade Index The three branch indexes are combined using the weights developed above. The branch indexes and the resulting total trade index are shown in table B-17. Services The end-use housing, utilities, repair and personal care, recreation, education, and health indexes are described by Schroeder and Denton in JEC, Con- sumption. Only the differences from those indexes arid the remaining service indexes are described here. The end-use utilities index is a weighted average of the housing stock and household consumption of electricity and natural gas. The sector-of-origin utili- ties index does not include an electricity component because the activity of the urban electric power network is believed to be included with the electric power branch of industry. The natural gas component is measured by total production rather than personal consumption in order to reflect the fact that the 93-892 0 - 82 - 8 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-13 Derivation of the Retail Trade Index Year (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Consumption Income in Kind Collective Farm Sales Retail Trade Sales of Food (billion Percent Billion Percent Billion Food Soft Goods Durables Total Index 1970 of (1) 1970 of (1) 1970 (billion (billion (billion (billion (1970= rubles) Rubles Rubles 1970 1970 1970 1970 100) rubles) rubles) rubles) rubles) 1950 42.7 36.3 15.5 12.4 5.3 21.9 10.8 1.5 34.3 23.7 1951 42.1 34.4 14.5 11.9 5.0 22.6 12.3 1.8 36.7 25.3 1952 45.7 32.6 14.9 11.4 5.2 25.6 13.0 2.1 40.6 28.1 1953 49.6 31.0 15.3 10.9 5.4 28.8 14.4 2.7 45.9 31.7 1954 51.2 29.4 15.0 10.5 5.4 30.8 16.7 3.4 51.0 35.2 1955 54.9 27.9 15.3 10.1 5.5 34.1 17.6 3.7 55.5 38.3 1956 57.3 26.8 15.4 9.3 5.3 36.6 19.1 4.1 59.9 41.4 1957 61.9 25.8 16.0 8.5 5.3 40.6 20.4 5.0 66.0 45.6 1958 66.2 24.9 16.5 7.9 5.2 44.5 22.0 5.5 71.9 49.7 1959 67.8 23.9 16.2 7.2 4.9 46.7 23.3 6.0 76.0 52.5 1960 70.6 23.1 16.3 6.7 4.7 49.6 25.2 6.7 81.6 56.4 1961 72.3 22.3 16.1 6.5 4.7 51.5 26.1 6.9 84.4 58.3 1962 75.4 21.6 16.3 6.3 4.7 54.4 27.0 7.2 88.6 61.2 1963 79.4 20.9 16.6 6.1 4.8 58.0 27.1 7.2 92.2 63.7 1964 79.3 20.2 16.0 5.9 4.7 58.6 28.0 7.9 94.4 65.2 1965 83.3 19.6 16.3 5.7 4.8 62.2 29.9 8.8 100.8 69.6 1966 87.2 18.9 16.5 5.6 4.9 65.9 32.5 9.8 108.2 74.7 1967 92.6 17.9 16.6 5.4 5.0 71.0 35.4 10.7 117.1 80.9 1968 98.1 17.0 16.6 5.2 5.2 76.4 38.5 11.8 126.7 87.5 1969 103.9 16.0 16.7 5.1 5.3 81.9 41.4 12.8 136.1 94.0 1970 107.9 15.2 16.4 4.9 5.3 86.2 44.3 14.3 144.8 100.0 1971 110.3 14.6 16.2 4.7 5.2 89.0 46.4 16.2 151.6 104.7 102 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-13 (Continued) Derivation of the Retail Trade Index Year (1) (2) (3) Consumption Income in Kind of Food (4) (5) (6) (7) Collective Farm Sales Retail Trade Sales (billion Percent Billion Percent Billion 1970 of (1) 1970 of (1) 1970 rubles) Rubles Rubles (8) (9) (10) Food (billion 1970 rubles) Soft Goods (billion 1970 rubles) Durables (billion 1970 rubles) Total (billion 1970 rubles) Index (1970= 100) 1972 110.4 14.1 15.6 4.4 4.9 89.9 47.7 18.7 156.3 1973 114.0 13.6 15.5 4.2 4.7 93.8 49.3 20.3 163.3 1974 118.7 13.1 15.6 3.9 4.7 98.5 51.0 22.0 171.4 1975 122.6 12.5 15.3 3.8 4.6 102.6 53.8 24.1 180.5 1976 123.6 11.2 13.8 3.9 4.8 105.0 56.3 25.7 187.0 1977 126.2 11.0 13.8 3.8 4.8 107.6 58.2 28.0 193.9 1978 129.9 10.7 13.9 3.7 4.8 111.2 59.9 29.2 200.3 1979 133.0 10.5 13.9 3.6 4.8 114.3 62.4 30.4 207.2 1980 134.4 10.2 13.7 3.5 4.7 116.0 65.4 32.5 213.9 Sources: Column 1: The consumption of food in 1970 established prices is computed by multiplying the index of consumption of food by the 1970 value of 107.9 billion rubles (table 9). The food index is derived in JEC, Consumption. Columns 2 and 4: The values for 1950, 1955, 1960, 1966, 1970, 1974, and 1976 are derived by dividing columns 3 and 5, respectively, by column 1. Intervening years are interpolated by assuming equal percentage rates of change.The values for 1977-80 are assumed to decrease at an annual rate of 0.25 percentage points for income in kind (column 2), and 0.1 percentage points for collective-farm-market sales (column 4). 103 108.0 112.8 118.4 124.7 129.2 133.9 138.4 143.1 147.8 Columns 3 and 5: The values for 1950, 1955, 1960, 1966, 1970, 1974, and 1976 are from tables B-11 and B-12. The values for all other years are derived as column 1 times columns 2 and 4, respectively. Column 6: This is column 1 less columns 3 and 5. Columns 7 and 8: The base-year (1970) ruble values of consumption of soft goods and durables are multiplied by our indexes of consumption of soft goods and durables as derived in JEC, Consumption. The 1970 values are from table 9. Column 9: This is the sum of columns 6, 7, and 8. Column 10: This is the index of column 9. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-14 1970=100 Derivation of the Wholesale Trade Index Year Wood, Pulp, and Paper Construction Light Materials Industry Food Industry Total Ferrous Metals Non- ferrous Metals Fuels Machinery Chemicals 1950 22.6 19.0 24.0 21.6 13.0 40.4 14.2 27.8 22.3 23.1 1951 25.6 21.5 26.3 23.7 14.3 45.8 16.1 32.7 25.5 26.2 1952 29.1 24.2 28.1 25.8 15.6 47.6 18.2 34.7 27.9 28.4 1953 31.9 27.0 30.0 28.1 17.2 49.6 21.2 38.1 30.9 31.0 1954 34.8 29.6 33.1 30.6 19.6 54.7 24.7 42.6 33.1 34.0 1955 38.3 34.7 37.6 34.2 22.5 57.6 29.4 45.6 36.2 37.5 1956 41.2 36.8 41.8 36.7 25.3 59.7 32.6 48.3 40.9 40.7 1957 43.7 38.9 46.6 39.2 27.7 63.9 37.9 50.5 43.5 43.5 1958 46.6 41.0 50.9 42.1 31.0 69.9 45.2 54.5 46.8 47.2 1959 50.7 44.4 54.5 45.9 33.7 76.3 52.0 58.7 51.7 51.5 1960 55.1 48.4 57.7 50.1 37.1 76.4 58.3 62.1 54.1 54.9 1961 59.8 52.4 60.6 54.3 40.8 76.3 62.6 64.3 58.1 58.4 1962 64.4 57.1 64.1 59.8 45.1 78.1 65.8 66.6 61.7 62.3 1963 68.4 61.5 69.4 63.7 50.0 81.4 67.6 67.5 64.3 65.4 1964 73.4 65.2 73.9 67.7 56.8 85.1 70.9 69.5 67.7 69.1 1965 78.1 69.9 78.3 71.5 65.3 86.8 75.8 70.7 75.3 73.7 1966 82.9 76.7 83.3 74.7 71.8 87.2 81.2 76.0 78.6 77.8 1967 87.6 83.5 87.7 79.7 79.0 91.5 87.0 82.3 84.4 83.4 1968 91.6 90.2 90.8 86.9 84.7 93.7 90.4 88.8 89.2 88.8 1969 94.8 94.7 94.8 92.9 89.8 95.4 92.2 94.4 94.3 93.7 1970 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 1971 103.8 107.0 104.8 108.1 108.1 102.8 106.7 104.5 102.6 105.2 1972 107.3 112.7 109.8 115.6 115.3 104.8 112.3 105.3 105.9 109.6 1973 111.6 119.6 115.1 125.3 125.7 107.7 119.0 108.2 106.7 114.8 1974 116.3 126.9 120.7 136,0 137.7 109.6 124.6 111.1 115.2 122.1 1975 121.5 132.9 127.8 146.4 151.0 113.6 130.2 114.3 121.1 129.1 1976 124.7 137.1 132.5 154.5 158.3 113.4 134.8 119.0 119.7 132.9 1977 125.6 141.3 138.1 163.2 166.6 114.0 137.4 122.1 124.5 138.0 1978 128.4 145.9 142.5 172.4 172.5 113.4 140.7 125.2 123.2 141.7 1979 128.4 150.2 146.7 182.0 172.9 110.2 141.2 127.4 127.2 145.8 1980 128.0 151.4 150.1 190.0 181.9 113.2 142.6 130.0 125.4 148.8 Source: See text. 104 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-15 Computation of the Weights for the Agricultural Procurement Index Percentage Share of Procurement Value Product 1970 Average Procurement Price (rubles per ton) 1970 Procurement Volume (thousand tons) 1970 Value of Procurement (billion rubles) Total NA NA 50.341 100.0 Grain 97 73,284 7.109 14.1 Potatoes 74 11,233 0.831 1.7 Vegetables 106 10,918 1.157 2.3 Fruit 282 6,180 1.743 3.5 Meat 1,472 12,595 18.540 36.8 Milk 192 45,681 8.771 17.4 Eggs 94a 18,054b 1.697 3.4 Wool 4,651 440.9 2.051 4.1 Silk 5,100 33.7 0.172 0.3 Cotton 555 6,890 3.824 7.6 Flax fiber 2,344 431.4 1.011 2.0 Sugar beets 26 71,385 1.856 3.7 Sunflower seeds 180 4,613 0.830 1.6 Tobacco 2,086 228 0.476 0.9 Makhorka 582 30 0.017 Tea 940 272.7 0.256 0.5 a The price of eggs is 100 rubles per thousand eggs. b Million eggs. c Less than 0.05 percent. Sources: Column 1: See text. Column 2: See table B-16. Column 3: This is column 1 times column 2. Column 4: This was computed from column 3. 105 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-16 Derivation of the Agricultural Procurement Index Thousand Tons Year Grain Potatoes Vegetables Fruit Meat Milk Eggs (million) Wool 1950 32,311 6,906 2,043 597 2,277 8,479 1,912 136.0 1951 33,600 5,195 1,819 796 2,719 9,201 2,147 156.0 1952 34,700 5,554 1,803 995 3,161 9,923 2,382 176.0 1953 31,107 5,422 2,485 1,193 3,604 10,646 2,618 197.0 1954 34,600 6,615 2,974 1,267 3,886 12,076 2,752 224.0 1955 36,901 5,869 3,877 1,341 4,168 13,506 2,886 230.0 1956 54,107 9,206 3,783 1,300 4,449 17,337 3,272 246.0 1957 35,411 7,897 4,162 1,700 5,053 20,454 4,284 281.0 1958 56,600 7,049 4,179 1,900 5,661 22,095 4,536 315.0 1959 46,600 6,826 4,500 1,908 7,508 24,957 5,662 354.0 1960 46,736 7,066 5,105 1,951 7,880 26,311 6,452 357.6 1961 52,109 7,000 5,477 2,303 7,334 28,305 7,376 368.8 1962 56,649 5,680 6,242 2,937 8,564 29,215 8,500 374.5 1963 44,822 8,024 6,347 3,061 9,339 28,541 8,677 380.0 1964 68,275 11,113 7,891 3,415 8,255 31,397 8,296 352.7 1965 36,331 9,946 7,724 4,477 9,280 38,700 10,478 368.5 1966 74,984 9,341 7,954 4,473 10,270 40,069 11,561 380.0 1967 57,234 11,680 9,469 4,680 11,533 42,457 12,890 410.0 1968 69,047 11,724 9,099 6,004 11,927 43,996 14,061 428.8 1969 55,540 10,628 9,638 5,817 11,724 43,782 15,444 401.7 1970 73,284 11,233 10,918 6,180 12,595 45,681 18,054 440.9 1971 64,119 11,482 11,467 6,351 14,163 47,078 21,570 457.4 1972 59,971 11,087 11,234 5,325 15,023 48,443 24,299 451.6 1973 90,529 15,410 14,126 7,793 14,695 52,978 27,544 470.1 1974 73,285 11,156 14,657 7,933 16,187 55,768 30,892 506.8 1975 50,213 14,527 13,883 8,541 16,756 56,296 33,065 510.9 1976 92,127 13,435 16,022 9,684 15,108 56,220 32,897 480.5 1977 68,027 17,122 16,171 9,439 16,286 60,762 36,831 512.1 1978 95,900 14,951 18,374 9,268 17,034 60,368 39,288 528.2 1979 62,834 16,400 18,010 10,827 16,692 58,954 41,050 538.3 1980 69,400 11,100 17,700 10,003 15,900 57,300 43,100 523.0 106 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-16 (Continued) Thousand Tons Year Silk Cotton Flax Sugar Fiber Beets Sunflower Tobacco Seeds Makhorka Tea 1950 24.8 3,539 174.0 19,705 1,084 59 86 84.9 1951 25.2 3,727 159.0 23,377 1,156 66 85 94.9 1952 25.6 3,780 189.0 21,991 1,346 73 83 97.7 1953 25.9 3,853 145.0 22,891 1,796 81 82 110.0 1954 26.5 4,200 192.0 19,523 1,188 93 68 110.2 1955 24.4 3,881 347.0 30,664 2,316 81 108 121.0 1956 28.1 4,332 427.0 31,457 2,391 79 119 110.0 1957 23.9 4,211 387.0 38,535 1,760 102 88 112.4 1958 28.3 4,340 392.0 51,023 2,615 100 102 138.2 1959 29.6 4,645 333.0 41,369 1,861 112 71 145.7 1960 29.7 4,289 369.0 52,198 2,293 103 70 163.7 1961 28.9 4,518 368.8 47,742 2,923 100 33 161.6 1962 30.6 4,304 394.8 43,946 3,082 102 30 178.9 1963 33.9 5,210 368.5 41,455 3,035 122 28 195.6 1964 33.3 5,285 316.8 76,124 3,933 184 43 193.7 1965 34.8 5,662 432.6 67,500 3,888 169 43 197.0 1966 34.7 5,981 426.3 69,715 4,663 178 38 238.2 1967 36.9 5,970 446.9 81,579 4,867 215 32 234.4 1968 36.1 5,945 355.5 84,168 4,906 215 46 229.0 1969 35.7 5,708 447.2 65,283 4,312 195 39 244.6 1970 33.7 6,890 431.4 71,385 4,613 228 30 272.7 1971 36.7 7,101 461.3 64,329 4,359 230 24 280.2 1972 41.4 7,296 439.1 68,043 3,753 275 17 291.1 1973 39.9 7,664 420.7 77,799 5,553 273 26 305.4 1974 38.7 8,409 364.1 67,484 5,228 292 18 329.9 1975 39.1 7,864 477.7 61,880 3,841 287 9 352.3 1976 45.1 8,278 482.7 85,142 3,770 299 12 375.4 1977 43.1 8,758 440.4 84,869 4,447 300 7 434.2 1978 46.5 8,500 331.9 80,061 4,028 273 7 453.8 1979 47.0 9,161 296.0 69,300 4,225 295 5 480.0 1980 45.0 9,960 247.0 64,400 3,360 260 4 530.0 Sources: The data for all products are from Narkhoz 1978, pp. 203, 224, 229-231, 234-235, and 253-255, and similar tables in Narkhozy for other years. Data for fruit, meat, milk, eggs, silk, tobacco, and makhorka for 1951, 1952, and 1954 are interpolated. 107 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-17 1970=100 Derivation of the Index of Value Added in Trade Year (1) Retail Trade (2) Wholesale Trade (3) (4) Agricultural Total Procurement Trade 1950 23.7 23.1 26.4 23.9 1951 25.3 26.2 28.6 26.0 1952 28.1 28.4 31.0 28.5 1953 31.7 31.0 32.5 31.6 1954 35.2 34.0 35.4 34.9 1955 38.3 37.5 38.8 38.2 1956 41.4 40.7 46.0 41.7 1957 45.6 43.5 45.8 45.1 1958 49.7 47.2 53.9 49.5 1959 52.5 51.5 58.4 52.9 1960 56.4 54.9 60.9 56.5 1961 58.3 58.4 61.8 58.7 1962 61.2 62.3 67.0 62.2 1963 63.7 65.4 68.1 64.7 1964 65.2 69.1 73.4 67.2 1965 69.6 73.7 74.5 71.3 1966 74.7 77.8 86.4 76.9 1967 80.9 83.4 89.8 82.6 1968 87.5 88.8 94.6 88.7 1969 94.0 93.7 90.1 93.5 1970 100.0 100.0 100.0 100.0 1971 104.7 105.2 104.4 104.8 1972 108.0 109.6 106.7 108.3 1973 112.8 114.8 118.3 114.0 1974 118.4 122.1 120.9 119.7 1975 124.7 129.1 118.6 125.1 1976 129.2 132.9 124.3 129.6 1977 133.9 138.0 126.9 134.2 1978 138.4 141.7 133.7 138.7 1979 143.1 145.8 127.5 142.0 1980 147.8 148.8 124.7 145.3 utilities sector supplies all urban customers, not just households. The weights used to combine the two components of the sector-of-origin utilities index are: natural gas, 25.3 percent, and the housing stock, 74.7 percent. The weights used to combine the subindexes of the repair and personal care and recreation indexes are derived by disaggregating the value-added compo- nents of these two sectors and, therefore, differ from the end-use weights. The weights used are: Percent Repair and personal care 100.0 State provided services 79.9 Privately provided services 20.1 Recreation 100.0 Entertainment 51.5 Vacation resorts 14.0 Leisure 34.4 The education and health sector-of-origin indexes are the man-hour components of the end-use education and health indexes. The following sections describe the remaining services-science, credit and insurance, and government administrative services. Science Scope and Coverage. As defined here, science com- prises the activities of scientific research organiza- tions subordinate to ministries or the academies of sciences. More specifically, the organizations included are: (1) academies, institutes, observatories, archives, botanical gardens, museums, and libraries engaged in scientific research; (2) surveying and geological explo- ration of a general nature; (3) independent design organizations and selected experimental stations; (4) hydrometeorological service; and (5) ancillary or- ganizations servicing scientific organizations, such as machine-testing stations (Ukazaniya, pp. 757-759). The sector encompasses the Soviet classification cate- gory "science and scientific services," for which em- ployment and wage data are regularly reported. The activities are financed partly by the state budget and partly by charges to enterprise costs and profits. The sector encompasses most but not all Soviet activity in the area of research and development. Some of the scientific research done at higher educa- tional institutions is not included-about 2 percent of total reported outlays according to B. M. Grinchel', lzmereniye effectivnosti nauchno-tekhnicheskogo 108 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 progressa, Moscow, Ekonomika, 1974, P. 40. Presum- ably, the associated employment and earnings are counted in the education sector. Also not included are research and development activities carried out in the laboratories and design organizations of individual producing enterprises (Ibid, pp. 39-40). These expend- itures are sizable, but are considered a part of the production activity of each enterprise and are charged to product costs. Science is treated as a separate producing sector here because employment and wage data are given sepa- rately in Soviet statistics. In the US national accounts by sector of origin, employment in comparable activi- ties would be included mainly in the government, services, and manufacturing sectors. There are no data on the basis of which to distribute reported Soviet employment in science among employment categories comparable to US practice. The science index is a weighted composite of indexes of man-hour employment and material inputs. The inclusion of a materials component in the index is designed to capture some manufacturing type of activity, mainly of prototypes or unique custom-built equipment, that apparently takes place in research institutes under branch ministries. Weights. The weights of the man-hour employment and material-input indexes are the estimated ruble expenditures for both components in 1970. The weight for the man-hour employment component (5.296 billion rubles) is the sum of wages and social security allowances (table D-7). The weight for the material-input component (4.463 billion rubles) is estimated in table B-18 as a part of the material-input index. Description of the Index. Man-Hour Employment. The man-hour employment data, column 4 of table B-19, are from Stephen Rapawy, Civilian Employ- ment in the USSR: 1950 to 1978, Washington, D. C., Department of Commerce, Bureau of the Census, 1980, p. 23 for 1950-78 and extended to 1980 by the same methodology. 109 Material Inputs. This is a deflated current-price index. The derivation of the series in current prices is shown in table B-18. Data in current prices are available for 1960-72 in Soviet sources. Values for other years are calculated as estimated shares of "outlays on science from the state budget and other sources," which are published in the Narkhoz. The expenditures on material inputs in current prices are converted to 1970 prices by a weighted average of wholesale price indexes for 10 branches of industry (ferrous metallurgy, coal, oil, electric power, machin- ery, chemicals, wood products, construction materials, light industry, and food industry). The weights to combine the 10 indexes are obtained from the struc- ture of purchases by science and administration in 1970 published by V. M. Rutgayzer, Resursy razvi- tiya neproizvodstvenno sfery, Moscow, Mysl', 1975, p. 168. Science purchases were about 86 percent of this total. All of the price indexes except the one for machinery are the official indexes published in the Narkhoz (for example, Narkhoz 1979, p. 164). The official index for machinery is believed to understate price increases badly in that branch. Accordingly, an alternative price index estimated by Abraham Becker for 1958-70 ("The Price Level of Soviet Machinery in the 1960s," Soviet Studies 26, July 1974, pp. 363- 379) was used. Estimates for 1950-57 were obtained by extrapolation on the basis of annual changes given by the official index. Since 1970, a rate of increase of 1 percent annually was assumed, except for 1971 and 1973, when price reductions were assumed to offset the general inflationary pressures from other sources. The resulting aggregate price index and the derivation of the total science index are shown in table B-19. Credit and Insurance Scope and Coverage. This sector includes the activi- ties of the state bank (Gosbank), the construction bank (Stroybank), the foreign trade bank, the system of savings banks, and the insurance enterprises (Ukazan- p. 760). Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-18 Derivation of the Index of Material Purchases by Science Year (1) (2) (3) Total Material Total Material Inputs of Science Expenditures Science Expenditures of the as a Percent (billion rubles) Nonproductive of Total Sphere Nonproductive (billion rubles) Material Expenditures (4) Material Inputs of Science (billion rubles) (5) Column 4 as a Percent of Column 3 1950 1.0 0.376 37.6 1951 1.1 0.414 37.6 1952 1.2 0.451 37.6 1953 1.3 0.489 37.6 1954 1.4 0.526 37.6 1955 1.6 0.601 37.6 1956 2.0 0.752 37.6 1957 2.4 0.902 37.6 1958 2.8 1.053 37.6 1959 3.3 1.241 37.6 1960 8.1 18.1 3.9 1.466 37.6 1961 8.5 20.1 4.5 1.708 38.0 1962 9.2 20.9 5.2 1.923 37.0 1963 9.9 21.3 5.8 2.109 36.4 1964 10.7 22.5 6.4 2.407 37.6 1965 11.5 22.6 6.9 2.599 37.7 1966 12.4 23.0 7.5 2.852 38.0 1967 13.4 23.0 8.2 3.082 37.6 1968 14.5 24.0 9.0 3.480 38.7 1969 15.6 24.5 10.0 3.822 38.2 1970 17.3 25.8 11.7 4.463 38.1 1971 18.4 26.5 13.0 4.876 37.5 1972 19.7 27.2 14.4 5.358 37.2 1973 15.7 5.842 37.2 1974 16.5 6.140 37.2 1975 17.4 6.475 37.2 1976 17.7 6.586 37.2 1977 18.3 6.810 37.2 1978 19.3 7.182 37.2 1979 20.2 7.517 37.2 1980 21.5 8.000 37.2 Sources: Column 1: V. M. Rutgayzer, Resursy razvitiya neproiz- vodstvennoy sfery, Moscow, Mysl', 1975, p. 157. Column 2: Ibid., p. 158. Column 3: 1950, 1960, and 1965-79 are from Narkhoz 1975, p. 744, and similar tables in other issues. 1961-64 are from UNESCO, Science Policy and Organizations of Research in the USSR, Paris, UNESCO, 1967, p. 54. 1951-59 are interpolated based partly on growth rates published in Narkhoz 1959, p. 805. 1980 is from Tsifrakh 1980, p. 81. Column 4: 1960-72 are column 1 times column 2. 1950-59 and 1973- 80 are column 3 times column 5. Column 5: 1960-72 are column 4 divided by column 3. Values for 1950-59 are assumed to be equal to the 1960 value. Values for 1973- 80 are assumed to be equal to the 1972 value. 110 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-19 Derivation of the Index of Value Added in Science Year (1) Material Inputs (billion rubles) (2) Price Index for Material Inputs of Science (1970=100) (3) Material Inputs (billion 1970 rubles) (7) Index of Science Expenditures (1970=100) (4) Man-Hour Employment (million) (5) Wage Income (billion 1970 rubles) (6) Total Science Expenditures (billion 1970 rubles) 1950 0.376 135.3 0.278 1,538 1.498 1.775 18.2 1951 0.414 116.6 0.355 1,639 1.596 1.951 20.0 1952 0.451 107.9 0.418 1,737 1.691 2.110 21.6 1953 0.489 100.5 0.486 1,774 1.728 2.214 22.7 1954 0.526 97.2 0.541 1,849 1.800 2.342 24.0 1955 0.601 92.3 0.652 1,952 1.901 2.553 26.2 1956 0.752 87.8 0.856 2,088 2.034 2.890 29.6 1957 0.902 86.3 1.045 2,216 2.158 3.203 32.8 1958 1.053 85.0 1.239 2,454 2.390 3.629 37.2 1959 1.241 85.5 1.451 2,644 2.575 4.026 41.3 1960 1.466 87.2 1.681 3,003 2.924 4.605 47.2 1961 1.708 87.8 1.947 3,286 3.200 5.147 52.7 1962 1.923 88.3 2.178 3,634 3.539 5.717 58.6 1963 2.109 89.1 2.366 3,901 3.799 6.166 63.2 1964 2.407 89.9 2.678 4,140 4.032 6.709 68.7 1965 2.599 90.5 2.872 4,311 4.198 7.070 72.4 1966 2.852 91.3 3.125 4,533 4.414 7.539 77.3 1967 3.082 95.3 3:234 4,744 4.620 7.854 80.5 1968 3.480 98.8 3.522 5,005 4.874 8.396 86.0 1969 3.822 99.1 3.856 5,258 5.120 8.976 92.0 1970 4.463 100.0 4.463 5,438 5.296 9.759 100.0 1971 4.876 100.4 4.857 5,709 5.559 10.417 106.7 1972 1973 5.358 100.4 5.339 6,003 5.846 11.184 114.6 5.842 100.5 5.815 6,299 6.134 11.950 122.4 1974 1975 6.140 100.6 6.103 6,542 6.371 12.474 127.8 6.475 101.0 6.413 6,857 6.678 13.091 134.1 1976 6.586 101.7 6.476 6,984 6.802 13.278 136.0 1977 6.810 102.5 6.646 7,166 6.978 13.624 139.6 1978 7.182 103.3 6.950 7,346 7.154 14.104 144.5 150.7 1979 7.517 104.2 7.212 7,698 7.497 14.709 1980 8.000 104.6 7.645 7,908 7.701 15.346 157.2 Sources: Column 1: See table B-18, column 4. Column 2: See text. Column 3: This is column 1 deflated by column 2. Column 4: See text. 111 Column 5: The 1970 value is from table D-7. All other values are computed by converting column 4 to index form (1970=100) and multiplying it by the 1970 value in this column. Column 6: This is column 3 plus column 5. Column 7: This is the index of column 6. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Description of the Index. The index is based on man- hour employment, which probably understates growth since the accounting operations that form a large part of this sector's work have been gradually mechanized. The data on employment and man-hours are obtained from Rapawy, Civilian Employment, pp. 2 and 14 for 1950-78 and extended to 1980 by the same method- ology. These data and the resulting index are shown in table B-20. Government Administrative Services Scope and Coverage. These services represent activi- ties that are usually financed and treated statistically as part of the government (nondefense) sector in the national accounts of Western countries. Soviet statis- tical practice in the treatment of government types of activities differs from Western practice. Accordingly, to obtain a group of activities for the Soviet Union which are reasonably comparable to the Western concept of general government, several Soviet statisti- cal categories had to be combined and others estimat- ed independently from a variety of information. This procedure is better than using the single Soviet cate- gory "apparat of organs of state and economic admin- istration, administrative organs of cooperative and social organizations," for which employment and oth- er types of data are reported but which is extremely narrow in scope. The problems of reconciling Soviet and Western concepts and definitions of government and administrative employment are discussed in some detail in Stephen Rapawy, Comparison of U.S. and U.S.S.R. Civilian Employment in Government: 1950- 1969, Washington, D. C., US Department of Com- merce, Bureau of Economic Analysis, 1972, Interna- tional Population Reports Series P-95, No. 69; and Gertrude E. Schroeder, "A Critique of Official Statis- tics on Public Administration in the USSR," ACES Bulletin 18, Spring 1976, pp. 23-44. Activities explicitly included in this sector are: general agricultural programs, forestry, state administration and the administrative organs of social organizations, culture, municipal services, and civilian police. Each of these categories is discussed below. The coverage of this group is hard to compare with general govern- ment activities in the United States. Major activities known to be excluded are upkeep of highways (includ- ed in transportation) and research and development (included in science). Table B-20 Derivation of the Index of Value Added in Credit and Insurance Year (1) Employment (thousands) (2) Hours Worked (million) (3) Index (1970=100) 1950 264 571 80.8 1951 263 567 80.3 1952 262 563 79.8 1953 263 564 79.9 1954 264 566 80.1 1955 265 567 80.3 1956 266 555 78.6 1957 261 532 75.3 1958 260 526 74.5 1959 260 512 72.4 1960 265 502 71.0 1961 277 502 71.0 1962 283 513 72.6 1963 289 522 74.0 1964 296 538 76.1 1965 300 541 76.6 1966 313 567 80.3 1967 329 598 84.6 1968 346 630 89.2 1969 363 662 93.8 1970 388 706 100.0 1971 411 753 106.6 1972 439 802 113.6 1973 465 844 119.5 1974 493 897 127.0 1975 519 943 133.5 1976 546 992 140.4 1977 574 1,040 147.3 1978 604 1,095 155.0 1979 632 1,146 162.2 1980 650 1,178 166.8 Sources: Column 1: 1950-78 are from Rapawy, Civilian Employ- ment, p. 2. 1979 is from Narkhoz 1979, p. 388. 1980 is from Tsifrakh 1980, p. 161. Column 2: Rapawy, Civilian Employment, p. 14, was used for 1950- 78, and extended to 1980 by the growth rate of column 1. Column 3: This is the index of column 2. 112 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Description of the Index. The index of government administrative services is a weighted average of the separate measures of man-hour employment in the six subsectors. The weights for the subsectors are the value added in each subsector as shown in table D-7. To the extent that labor productivity has increased, man-hour employment understates the growth of the real product rendered by this group of services. An alternative procedure�to deflate current expendi- tures on these activities by appropriate price index- es�cannot be used because there is little information on nonwage outlays for the sector and suitable price deflators are not available. The procedure used in US accounts is to deflate general government expendi- tures largely by input price indexes. The man-hour employment data for each subsector are shown in table B-21. General Agricultural Program. These programs pro- vide general services to agriculture and are apparently financed largely if not entirely from the state budget. The services include plant and animal disease control, general veterinary services and inspection, erosion control and land improvement, management of land tenure procedures, and the like. Activity is measured by an index of man-hour employment obtained as follows: (1) Employment is estimated in each year as the difference between total reported employment in state agriculture and employment in "state farms, interfarm economic enterprises, subsidiary and other productive agricultural enterprises." Data given in Trud v SSSR, Moscow, Statistika, 1968, p. 26, suggest that nearly all of this residual group consists of employees providing veterinary and other services to agriculture. (2) The average annual number of man-hours was assumed to be the same as in state agriculture as a whole. The latter was calculated for 1950-78 from data on average annual employment and total man-hours worked given in Stephen Rapawy, Civilian Employment, p. 24. The average number of man-hours in 1979 and 1980 was assumed to be the same as in 1978. 113 Forestry. This activity encompasses enterprises and organizations engaged in the management and protec- tion of state forests and parks; it is financed largely from the state budget. The man-hour employment data used to measure this activity are given for 1950- 78 in Rapawy, Civilian Employment, p. 14, and extended to 1980 by the same methodology. State Administration and the Administrative Organs of Social Organization. This activity includes the operations of state administrative bodies at all levels (ministries, state committees, and the like), legislative and judicial organs, administrative organs of state security and defense, and the administrative organs of trade unions, the Communist Party and other so- called social organizations. The activity of this sector is financed mainly from state budget funds, but also partly from charges to enterprise costs. Social organi- zations include the administrative organs of the All- Union Society of Consumer Cooperatives, the Com- munist Party and Komsomol, the trade unions and professional unions, and a number of other groups that are permitted to function (for example, the Red Cross, civil defense, and nature societies). Their activ- ities are financed largely from dues paid by members. The man-hour employment data used to measure this activity are given for 1950-78 in Rapawy, Civilian Employment, p. 14, and extended to 1980 by the same methodology. Culture. Public libraries, museums, parks, zoos, clubs, and children's camps are the principal institutions covered by this sector. Rapawy published data for education and culture combined (Civilian Employ- ment, p. 14). The education component is derived in JEC, Consumption as part of the consumption index. The remainder forms the index of culture. Municipal Services. These services consist mainly of the upkeep of city streets and municipal facilities, garbage and trash collection, fire protection, and similar functions. Activity is measured by an index of man-hour employment obtained in the "housing-com- munal economy and personal services" category of Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-21 Million Man-Hour Employment in Government Administrative Services Year General Agricultural Services Forestry State Adminis- Municipal Services Civilian Police Culture tration and the Administrative Organs of Social Organizations 1950 748 960 3,979 385 1,425 585 1951 811 977 3,920 400 1,404 605 1952 871 993 3,860 415 1,382 624 1953 797 893 3,723 424 1,333 640 1954 827 862 3,326 432 1,191 668 1955 596 832 2,926 440 1,048 695 1956 650 814 2,814 452 1,007 702 1957 623 768 2,649 456 948 712 1958 739 742 2,631 461 942 730 1959 780 693 2,518 464 901 739 1960 948 680 2,370 473 848 752 1961 856 685 2,358 478 844 776 1962 844 705 2,396 494 858 826 1963 832 721 2,376 513 851 871 1964 863 734 2,472 539 885 930 1965 888 725 2,645 559 947 981 1966 940 741 2,802 586 1,003 1,028 1967 1,029 748 2,987 631 1,069 1,131 1968 1,106 766 3,132 663 1,122 1,246 1969 1,122 777 3,301 695 1,182 1,355 1970 1,121 788 3,363 722 1,204 1,467 1971 1,198 791 3,474 765 1,244 1,569 1972 1,252 810 3,597 802 1,288 1,635 1973 1,301 806 3,712 832 1,329 1,712 1974 1,355 817 3,867 867 1,384 1,805 1975 1,418 823 3,994 899 1,430 1,876 1976 1,547 816 4,080 920 1,461 1,949 1977 1,582 819 4,172 953 1,494 2,059 1978 1,681 830 4,277 994 1,531 2,143 1979 1,746 830 4,392 1,025 1,572 2,190 1980 1,844 834 4,518 1,054 1,617 2,243 Sources: See text. 114 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Soviet employment data. The share of municipal (2) services in this employment category was estimated at 13 percent in 1970 (CIA, GNP 1970, p. 54). In the absence of other information, this share was assumed to be the same in all other years. Man-hour employ- ment in "housing-communal economy and personal services" in 1950-78 is given in Rapawy, Civilian Employment, p. 14, and extended to 1980 by the same methodology. Civilian Police. As a category in Soviet annual statistics on employment in the state sector, civilian police does not exist. In the 1959 population census the Soviets explicitly reported employment for "work- ers in protection of socialist property and public order"-429,000 persons. The 1970 census does not list such a category. Whether civilian police (militia) are included somewhere in the total number in the state labor force (workers and employees) reported annually in the statistical handbooks is uncertain. Civilian police might be: (1) considered to be part of the armed forces, (2) omitted entirely from unpub- lished figures on military manpower and from report- ed data on employment, or (3) included somewhere in the regularly published annual statistics on state (4) employment. The first possibility is ruled out for constructing GNP accounts because of the definition of armed forces that has been adopted. The second treatment is possible, but it seems unlikely that the Soviets would omit them altogether; they are a highly visible and entirely legitimate activity in a modern state. The third possibility seems plausible and is the approach adopted here. The estimate relies in part on the work of Stephen Rapawy, Comparison of U.S. and U.S.S.R. Civilian Employment in Government. The argument supporting this approach is as follows: (1) A large unexplained residual of employment exists in the Soviet category "Other branches of materi- al production." Rapawy estimated this residual at 551,000 in 1966 by deducting from total reported employment in "other branches of material pro- duction" the reported employment in component subgroups. No employment was reported for the subgroup "interdepartmental guard," which is classified in "other branches of material produc- tion" (Ukazaniya, pp. 751-752). 115 (3) This approach yields an estimate for police em- ployment that seems appropriate to the size and extent of urbanization of the USSR and to the nature of the society. By way of comparison, total government employment in police protection in the United States�a much more urban society� in 1966 was 437,000 (Statistical Abstract of the United States, Washington, D. C., Government Printing Office, 1967, p. 439). To obtain a time series for police employment, the estimate for 1966 was extrapolated on the as- sumption that the trend in police employment is the same as reported for state administration and the administrative organs of social organizations. Both groups would be likely to have been affected by the shakeup in the police and bureaucracy that occurred during the 1950s; this phenomenon is reflected in the statistics. This approach yields a figure of 452,000 for police employment in 1959; the 1959 census reported 429,000 persons as em- ployed in "protection of socialist property and public order." The alternative to the procedure adopted here is to assume that the function of police protection is omitted from Soviet published employment statis- tics. To account for what is obviously a sizable activity it would then be necessary to adopt an arbitrary estimate for the number of police, their average wages, and other costs and to make an equally arbitrary assumption about trends over time. Although arbitrary assumptions are also involved in the procedure used here, the results produce a plausible measure of levels and trends in police protection activity. The index used to measure police protection activity is an index of man-hour employment. Average annual employment was estimated for 1966, as explained above, and extrapolated on the basis of trends in man- hour employment in state administration and the Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 administrative organs of social organizations. Average annual man-hours worked by police were assumed to be the same as for state administration. Military Personnel Scope and Coverage All uniformed personnel of the armed forces�includ- ing border guards, internal security, construction troops, and railroad troops�are included in this activity. It should be noted that substantial definition- al differences complicate any comparison of the activ- ities of US and Soviet armed forces. Description of the Index Separate indexes are computed in established prices and factor-cost prices. The index in established prices is the sum of wages, social security payments, and outlays for subsistence, all computed in 1970 prices. The index takes account of changes in the mix of conscripts, officers, and noncommissioned officers. For the factor-cost index, the conscript costs are replaced by an estimate that attempts to allow for the opportunity cost of conscripts. For this we have used a minimum industrial wage, which is slightly higher than expenditures on military pay and subsistence. Other Branches The index for this sector is assumed to be equal to the index for total GNP. 116 Approved for Release: 2019/07/19 C05210421 Appendix C End-Use Indexes Consumption The indexes of consumption are described by Ger- trude Schroeder and Elizabeth Denton in JEC, Consumption. Investment Investment is the sum of new fixed investment and capital repair. New fixed investment is the sum of machinery and equipment (producer durables), new construction and other capital outlays, and net addi- tions to livestock. Soviet investment data are equivalent in concept to the machinery and equipment and construction and other capital outlays components of new fixed invest- ment. The Soviet investment data in each edition of the Narkhoz are published in "comparable estimate" prices of some base year (primarily 1955 or 1969). Western economists have debated about whether these data are valid measures of the real growth. For example, Becker used the Soviet data for his constant price accounts without any discount for inflation (Becker, Soviet National Income, p. 116). On the other hand, Nove asserts that the Soviet data so overstate growth that real investment may actually have fallen in recent years (Alec Nove, "A Note on Growth, Investment and Price Indexes," Soviet Stud- ies, January 1981). The uncertaint: about the official data has led Western economists to consider alterna- tive series. In this report, we use one such alternative for the construction and other capital outlays compo- nent of new fixed investment. We have not yet found an acceptable alternative for the machinery and equipment component. Although our index of indus- trial production contains a producer durables catego- ry, it is not a suitable substitute because of problems relating to foreign trade and inventory changes. 117 Approved for Release: 2019/07/19 C05210421 Machinery and Equipment Scope and Coverage. Investment in machinery and equipment includes all expenditures by state enter- prises and organizations and collective farms. Private investment is negligible. By the Soviet definition, this sector now includes the purchase of all new equipment costing more than 100 rubles and lasting longer than one year. Capital repair of machinery and equipment is not included. Soviet investment data do not include expenditures for certain producer durables by budget- ary institutions. An estimate of these expenditures in 1970 was made, however, and these purchases are implicitly assumed to have grown at the same rate as other purchases of machinery and equipment. Description of the Index. The index is based on reported Soviet data on investment in machinery and equipment. These data are said to be in constant prices. There is considerable controversy over the existence and amount of price inflation in the machin- ery sector. It seems clear from the published data that the Soviets have made some attempt to account for price changes in their investment data. Because a large share of producer durables, perhaps as much as one-third, consists of unique products, all of the inflation in the investment data may not have been eliminated. Nevertheless, it was not possible to con- struct an alternative series. Over the years, the Soviets have published investment data in constant 1955, 1969, and 1973 estimate prices. In the 1950s the published data excluded collective farm investment. Table C-1 presents the published values for state investment and estimates of collective farm investment. The values in the various prices are linked to form the index of investment in machinery and equipment. Construction and Other Capital Outlays Scope and Coverage. This sector includes all new construction of buildings and structures (including private housing) and certain other expenditures for design work, geological exploration, and drilling. As 93-892 0 - 82 - 9 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-1 Derivation of the Index of Investment in Machinery and Equipment Year (1) (2) (3) Expenditures in 1955 Prices (billion rubles) (4) Expenditures in 1969 Prices (billion rubles) (5) Expenditures in 1973 Prices (billion rubles) (6) Index (1970=100) Collective Farms State Organizations Total 1950 0.2 3.0 3.2 13.5 1951 0.2 3.0 3.2 13.5 1952 0.2 3.2 3.4 14.8 1953 0.3 3.3 3.6 15.6 1954 0.3 4.0 4.3 18.4 1955 0.5 4.8 5.3 22.5 1956 0.6 6.0 6.6 28.3 1957 0.6 6.7 7.3 31.1 1958 0.9 7.4 8.3 35.2 1959 1.0 7.9 8.9 38.1 1960 1.0 8.9 9.9 42.2 1961 0.9 9.9 10.8 11.6 45.9 1962 1.1 11.0 12.1 13.1 51.6 1963 1.3 12.1 13.4 14.5 57.0 1964 1.5 13.7 15.2 16.4 64.8 1965 1.7 14.6 16.3 17.5 16.9 69.3 1966 17.2 18.5 73.4 1967 18.6 19.9 78.7 1968 20.3 21.5 84.8 1969 20.9 22.5 88.9 1970 25.3 24.4 100.0 1971 26.6 25.7 105.3 1972 28.8 27.8 113.9 1973 31.1 29.9 122.5 1974 34.1 32.9 134.8 1975 38.5 37.1 152.0 1976 40.7 166.8 1977 43.0 176.2 118 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-1 (Continued) Year (6) Index (1970=100) (1) (2) (3) Expenditures in 1955 Prices (billion rubles) (4) Expenditures in 1969 Prices (billion rubles) (5) Expenditures in 1973 Prices (billion rubles) Collective Farms State Organizations Total 1978 46.6 191.0 1979 48.6 199.2 1980 50.9 208.6 Sources: Column 1: 1950-55 are estimated by assuming that the share of machinery and equipment in total kolkhoz investment was constant. Total kolkhoz investment in machinery and equipment for 1951-55 is derived as total investment in machinery and equipment (19.8 billion rubles�Narkhoz 1969, p. 502) less non-kolkhoz investment in machinery and equipment (18.3 billion rubles� Narkhoz 1965, p. 529). Annual data on total kolkhoz investment are from Kapital'noye stroitel'stvo v SSSR, Moscow, Gosstatizdat, 1961, p.40; and Narkhoz 1965, p. 536. The implied share of machinery and equipment in kolkhoz investment for 1951-55 is 22 percent. This share is assumed to hold for 1950 also. 1956-60 are first estimated by multiplying the share of machinery and equipment in total agricultural investment (Kapital'noye stroitel'stvo, p. 159) by total kolkhoz investment. These estimates are with investment in machinery and equipment, the Central Statistical Administration may not have com- pletely eliminated inflation from the construction statistics. Measurement of the real change in con- struction has proved troublesome in Western econo- mies as well as in the Soviet Union. In the United States, price deflators are used based on certain types of standard construction projects, but it is suspected that the real growth of investment in construction has been significantly understated. Description of the Index. Because of the Soviet definition of its construction sector, an independent index of the construction component of investment can be estimated. The Soviets define the entire output of the construction sector as capital expenditures. Therefore, our sector-of-origin index of the output of the construction sector in constant prices, described in appendix B, represents the growth of new construction and other capital outlays plus capital repair of build- ings and structures. In order to derive the index of new construction and other capital outlays, we first 119 then adjusted to agree with control totals for 1956-58 and 1959-60. Kolkhoz investment in machinery and equipment for 1956-58 and 1959-60 are derived from data in Strana soveta za 50 let, Moscow, Statistika, 1967, pp. 198-199; Narkhoz 1969, p. 502; and Narkhoz 1965, p. 529. 1961-65 are calculated as column 3 less column 2. Column 2: This is from Narkhoz 1965, p. 529. Column 3: 1950-60 are column 1 plus column 2. 1961-69 are from Narkhoz 1969, p. 502. Columns 4 and 5: These are from Narkhoz 1975, p. 503, and similar tables in other issues. Column 6: This was derived by linking the data in columns 3, 4, and 5. Data for 1961-64 and 1966-69 are derived from column 4, and data for 1950-60 are derived from column 3. estimate capital repair expenditures on buildings and structures in current prices (see below) and then subtract that series from the Soviet published values on the gross output of the construction sector in current prices. The result is an estimate of new construction and other capital outlays in current prices. Both component series are then deflated by the implicit price index obtained by comparing our index of construction output in constant prices with the Soviet gross output series in current prices. Table C-2 shows the derivation of our estimated series on new construction and other capital outlays in current prices and in 1970 prices. Our estimates in 1970 prices are also compared with Narkhoz data in 1969 prices (column 5) and an implicit price index is derived (column 6). The series in 1970 prices shows slower growth over the 1961-78 period (4.9 percent per year versus 5.8 percent). The relationship is not consistent, however, as the implicit price index declines in several years. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-2 Derivation of Investment in New Construction and Other Capital Outlays Year (1) (2) Gross Output Capital Repair of Construction of Buildings Sector and Structures (billion rubles) (billion rubles) (3) Investment in New Construction and Other Capital Outlays (billion rubles) (4) Investment in New Construction and Other Capital Outlays (billion 1970 rubles) (5) Investment in New Construction and Other Capital Outlays (billion 1969 rubles) (6) Implicit Price Index (1970=100) 1950 12.1 1.2 10.9 12.4 NA NA 1951 13.6 1.3 12.3 14.2 NA NA 1952 15.3 1.3 14.1 15.9 NA NA 1953 16.1 1.4 14.7 17.5 NA NA 1954 18.2 1.6 16.5 19.4 NA NA 1955 18.4 2.0 16.4 21.5 NA NA 1956 20.3 2.7 17.7 22.8 NA NA 1957 22.6 3.3 19.3 24.9 NA NA 1958 25.7 3.8 21.9 28.1 NA NA 1959 29.2 4.2 25.0 31.7 NA NA 1960 31.9 4.5 27.4 34.2 NA NA 1961 32.7 4.8 27.9 35.8 32.2 94.9 1962 33.6 4.9 28.7 37.5 32.8 92.2 1963 34.7 5.1 29.6 38.9 33.8 91.6 1964 36.6 5.5 31.0 40.6 36.2 94.0 1965 40.3 5.6 34.7 43.8 39.5 95.1 1966 43.0 6.2 36.8 45.6 42.5 98.3 1967 50.0 6.6 43.4 49.8 46.1 97.6 1968 53.0 6.9 46.1 52.5 49.7 99.8 1969 60.0 7.4 52.6 55.1 51.1 97.8 1970 67.6 7.8 59.8 59.8 56.7 100.0 1971 74.7 8.8 65.9 63.6 61.4 101.8 1972 77.4 9.3 68.1 66.8 65.5 103.4 1973 80.9 10.1 70.8 70.3 67.6 101.4 1974 86.4 11.2 75.2 73.5 71.6 102.7 1975 91.7 12.4 79.3 76.7 76.4 105.1 1976 94.2 13.5 80.7 78.5 77.9 104.7 1977 96.2 14.7 81.5 79.5 79.9 107.3 1978 99.2 16.0 83.2 81.0 83.8 109.1 1979 NA NA NA 83.3 NA NA 1980 NA NA NA 84.7 NA NA Sources: Column 1: See table B-3, column 1. Column 2: See text. Column 3: This is column 1 less column 2. Column 4: This is column 3 deflated by the price index derived in table B-3, column 4. Figures for 1979 and 1980 are estimated using the growth rate of the gross output of total construction in 1970 prices (table B-3, column 2), and the assumption that the growth rate of capital repair expenditures is double that of new construction and other capital outlays. Column 5: See Narkhoz 1972, p. 474, and similar tables in other issues. Column 6: This is derived from a comparison of columns 4 and 5. 120 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Net Additions to Livestock This index is derived by Margaret Hughes and Barba- ra Severin in JEC, Agriculture. Capital Repair Scope and Coverage. This sector includes the capital repair of machinery and equipment and of buildings and structures. It defies comparison with similar activities in US or other Western GNP accounts because much of the comparable activity evidently is either charged to current expenses or included with new fixed investment in Western statistics. Description of the Index. The index is the sum of two deflated current-price series�capital repair of ma- chinery and equipment and capital repair of buildings and structures. Both series are derived in an unpub- lished working paper by Scot Butler ("The Growth of Capital Repair in the USSR, 1950-77"). First total capital repair expenditures are estimated, based main- ly on current-price amortization deductions for capital repair. A series on capital repair of buildings and structures is then derived based mainly on budgetary expenditure data. Using estimated expenditures in 1970, the two indexes are converted to 1970 ruble values, and expenditures for capital repair of machin- ery and equipment are derived as a residual. The two components of capital repair are deflated separately to constant 1970 prices. The price deflator for total construction (table B-3, column 4) is used also for capital repair of buildings and structures. Expenditures for capital repair of machinery and equipment are deflated by a price index based on a comparison of the gross output of the machinery sector in current and constant prices. The current- price series for machinery output is built up from data on wages, social security deductions, the ratio of wages and social security deductions to production costs, and profits. The index of machinery output in constant prices is derived in the same manner as the index of the value added in the machinery sector (described by Ray Converse in JEC, Industry), but gross output weights are used to combine the various machinery subsector indexes rather than value-added weights. The deflated machinery capital repair series and the derivation of the total capital repair series are shown in table C-3. 121 Other Government Expenditures Government Administrative Services The indexes used to measure this activity are the same as those used for the sector-of-origin indexes. Theoret- ically, a separate measure of real trends in material purchases should be added to the measure of trends in employment. Despite a considerable amount of re- search, it has not proved feasible to produce reliable estimates of material purchases, nor can a suitable price deflator be obtained. According to one Soviet estimate, material expenditures in administration in current prices increased at about the same rate as man-hour employment during 1960-72 (V. M. Rut- gayzer, Resursy razvitiya neproizvodstvennoy sfery, pp. 157-158). The weights used to combine the subsec- tor indexes are the end-use expenditures in 1970. Research and Development This index is the same as that used for science as a sector of origin. Outlays Not Elsewhere Classified (n.e.c.) The item is derived as a residual by subtracting all identified end-use components from total GNP de- rived from the sector-of-origin data. Defense As stated in the main report, defense expenditures are not computed as a separate component of GNP by end use because it is believed that other components, primarily investment and research and development, include substantial amounts of defense expenditures. The CIA does periodically estimate the cost of Soviet defense activities based on a detailed list of the physical elements of their defense programs and ruble values derived from a variety of sources. Using data in this report, we have converted these estimates to factor-cost prices. Table C-4 shows these estimates as ranges. Although it has not been possible to integrate the estimates of total defense expenditures with our GNP data, we have made some sample calculations based Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-3 Derivation of the Index of Capital Repair Expenditures Year (1) Capital Repair of Machinery and Equipment (current prices) (2) Machinery Price Index (1970=100) (3) Capital Repair of Machinery and Equipment (billion 1970 rubles) (4) Capital Repair of Buildings and Structures (billion 1970 rubles) (5) Total Capital Repair (billion 1970 rubles) 1950 1.5 NA 1.6 1.4 3.0 1951 1.6 NA 1.8 1.5 3.3 1952 1.8 NA 2.1 1.4 3.6 1953 2.1 NA 2.3 1.7 4.0 1954 2.2 NA 2.4 1.9 4.4 1955 2.3 86.6 2.6 2.6 5.3 1956 2.1 NA 2.8 3.5 6.3 1957 2.1 NA 3.0 4.2 7.2 1958 2.3 69.9 3.3 4.9 8.1 1959 3.1 73.4 4.2 5.3 9.5 1960 3.4 77.2 4.5 5.6 10.1 1961 3.8 81.0 4.7 6.1 10.9 1962 4.4 80.4 5.5 6.4 11.9 1963 5.7 82.9 6.9 6.7 13.6 1964 6.2 83.1 7.4 7.3 14.7 1965 7.0 83.2 8.5 7.1 15.6 1966 7.6 90.4 8.4 7.7 16.1 1967 8.3 94.0 8.8 7.5 16.4 1968 9.1 95.9 9.5 7.8 17.4 1969 10.1 98.0 10.3 7.7 18.0 1970 11.2 100.0 11.2 7.8 19.0 1971 12.2 96.1 12.6 8.5 21.2 1972 13.7 97.7. 14.0 9.1 23.1 1973 15.2 93.5 16.2 10.0 26.2 1974 16.5 94.6 17.4 11.0 28.4 1975 15.3 96.1 15.9 12.0 27.9 1976 16.4 93.8 . 17.5 13.1 30.6 1977 17.5 93.6 18.7 14.4 33.1 1978 18.6 95.5 19.4 15.6 35.1 1979 19.5 96.6 20.2 15.8 36.1 1980 20.6 97.6 21.1 16.5 37.6 Sources: Columns 1 and 2: See text. Data are not available to calculate the current-price machinery series for 1950-54 and 1956- 57 and, hence, the price index. Column 3: This is column 1 deflated by the price index in column 2. The values for 1950-54 and 1956-57 are estimated by using a series of expenditures for capital repair of machinery and equipment in 1937 prices derived from data estimated by Moorsteen and Powell, The Soviet Capital Stock, 1928-1962, pp. 386-387. Column 4: This is table C-2, column 2, deflated by the price index in table B-3, column 4. Column 5: This is column 3 plus column 4. 122 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-4 Estimated Soviet Defense Expenditures, 1951-80 Billion 1970 Rubles, Factor-Cost Prices Year Upper Bound Lower Bound 1951 33 19 1952 33 20 1953 30 19 1954 31 20 1955 36 24 1956 34 23 1957 30 21 1958 30 22 1959 29 22 1960 31 23 1961 34 26 1962 38 29 1963 39 31 1964 42 34 1965 43 35 1966 44 36 1967 47 39 1968 50 42 1969 52 43 1970 53 44 1971 54 45 1972 56 46 1973 58 48 1974 62 51 1975 65 53 1976 69 56 1977 70 56 1978 72 57 1979 75 59 1980 79 62 123 on assumptions about the proportions of the identified components of GNP which might represent defense expenditures. These calculations indicate that the independent estimates of defense expenditures are reasonably consistent with our GNP data. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix D Revised 1970 GNP Accounts in Established Prices The original estimate of Soviet GNP for 1970 was documented in CIA, GNP 1970. This appendix revises that estimate by incorporating new information and reinterpreting some old evidence. The basic account- ing structure is unchanged. The first part of this appendix summarizes the most important changes we have made in the four basic accounts (household incomes and outlays and public-sector incomes and outlays) and the consequent changes in the combina- tion of those accounts to form GNP. The rest of the appendix consists of the revised basic tables which comprise the GNP accounts, several supporting ta- bles, and detailed sources for all tables. Household Incomes There are three significant revisions to the estimate of household incomes (table D-1). First, total income, which is determined by total outlays, is 1.7 billion rubles lower than in CIA, GNP 1970. Second, mili- tary subsistence has been revised upward by 1.2 billion rubles. Third, the first two revisions plus other, smaller changes mean that the unidentified money income residual has been reduced by 3.6 billion rubles. The residual is determined as total outlays less all identified incomes. In addition there have been numerous small changes. In particular, earnings in the various private services have been reestimated. Included is an increase in private earnings in health and education from 1 to 5 percent of the wage bills of state health and education based on reports of widespread private activities of this type. There is one small change in the accounting structure of household incomes from that published in CIA, GNP 1970. The profits distributed to consumer cooperative members are now considered to be a transfer receipt rather than earned income. This change does not affect the value of GNP because these profits are now reflected as an income of the public sector. 125 Household Outlays Household outlays are 1.7 billion rubles lower than in CIA, GNP 1970 (table D-2). The lower total is mainly the result of reductions in our estimates of household expenditures for goods, transportation, private hous- ing construction, and recreation. Offsetting these reductions are upward revisions of estimated expendi- tures for repair and personal care, health, and educa- tion services and for military subsistence. Expenditures for goods have been reduced by 2.1 billion rubles to eliminate expenditures for second- hand goods in commission stores, business travel, and materials which are also included in the cost of certain repair services. Transportation expenditures have been reduced by 25 percent, or 1.8 billion rubles, to eliminate business travel expenditures. The value of private housing construction reported in the Narkhoz was previously thought to be in 1955 prices and was adjusted to 1970 prices. We now believe that it is reported in current prices. This reinterpretation reduces investment ex- penditures by 0.3 billion rubles. Expenditures on hotels (part of recreation expenditures) have been reduced by 0.1 billion rubles to eliminate business travel expenditures. Household expenditures for repair and personal care services were increased to include the value of materi- als used for the repair and custom making of clothing and knitted goods. At the same time deductions were made to eliminate sales to enterprises of all repair and personal care services. The net increase in household outlays for repair and personal care services is 0.8 billion rubles. Household expenditures for health and education and the value of military subsistence were all increased in the same manner as household in- comes from these sources. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Trade union and other dues were considered an element of consumption in CIA, GNP 1970. They are now classified as a transfer outlay since the dues are used mainly to finance social-cultural and administra- tive activities rather than to provide services to mem- bers of the trade unions and other organizations. This change does not affect total household outlays or total GNP, but it does lower total consumption expenditures. Public-Sector Incomes Public-sector incomes have increased 6.7 billion ru- bles (table D-3). The most important changes are: (1) the addition of several charges to enterprise costs for special funds (2.1 billion rubles), (2) an increase in the miscellaneous charges component of taxes and other payments to the budget (1.6 billion rubles), (3) the deletion of the subsidy on milk products (0.8 billion rubles), and (4) the addition of trade union and other dues to transfer receipts (2.1 billion rubles). The charges to enterprise costs represent funds col- lected to support expenditures on certain components of GNP by end use (for example, science expendi- tures) which are charged to current expenses in the Soviet accounting system. The information on the number of these funds and their size, however, is sparse. The likelihood of large percentage errors in these estimates remains. The method used to estimate the miscellaneous charges component of taxes and other payments to the budget has been completely revised. Although the revised value is 1.6 billion rubles higher than in CIA, GNP 1970, it actually has been reduced because we now explicitly include income earned from foreign trade. This item, 7.6 billion rubles, was previously excluded from GNP. Foreign trade income results from the differences between the domestic prices of traded goods and their equivalent foreign trade prices. We now consider the price differences to be equiva- lent to a tax or subsidy and, in agreement with Western accounting practices, include the income as a part of GNP. The subsidy on milk products was deleted because new information indicates it is netted against the value of profits reported in the Narkhoz. Trade union and other dues are now considered as a transfer payment as described above. Public-Sector Outlays Total income provides the control total for the public sector and, therefore, public-sector outlays have also risen 6.7 billion rubles (table D-4). There have been substantial structural changes in addition to the in- creased total. Expenditures for communal and admin- istrative services have decreased by 6.0 billion rubles while investment outlays increased 4.6 billion rubles and outlays n.e.c. increased 7.4 billion rubles. Expenditures on communal services (education, health, and physical culture) are estimated by a new methodology and are considerably lower than the estimates published in CIA, GNP 1970. Previously we used Narkhoz data relating to expenditures on sum- mary groups of services from the budget and other sources. Because of many ambiguities in these data and the discovery that they include imputed deprecia- tion charges of unknown size, we now estimate expen- ditures for communal services as the sum of wages, social insurance, and other current outlays. In addi- tion, expenditures for art have been deleted because they already were included with recreation expendi- tures, and expenditures for physical culture were reduced to account for the trade union subsidy on resort passes. Expenditures for government administrative services have been reduced by 0.9 billion rubles. Most of this amount is the result of a decision to lower the share of other current outlays in total expenditures from one- third to one-fourth. Investment expenditures have been increased by 4.6 billion rubles. The primary changes are the addition of an estimate for the acquisition of equipment by 126 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 budget institutions and a revised method for estimat- ing the value of new construction and other capital outlays. In addition, smaller revisions were made to the value of net additions to livestock inventories and capital repair expenditures. Outlays n.e.c., determined as total public-sector in- comes less identified public-sector outlays, is 7.4 billion rubles larger than in CIA, GNP 1970. The revised accounting of foreign trade income, however, means that net exports, a component of outlays n.e.c., are now valued in foreign trade prices. As a result, the portion of outlays n.e.c. which might be associated with defense expenditures, changes in strategic re- serves, or a statistical discrepancy is virtually un- changed from that computed in CIA, GNP 1970 (p. 16). GNP by End Use The GNP of the Soviet Union is estimated by combin- ing the relevant portions of the outlays of the house- hold and public sectors (table D-5). As a result of the changes made in these accounts, total GNP is now 2.5 billion rubles higher than calculated in CIA, GNP 1970. The changes in the important components of GNP by end use are shown in the following tabulation: GNP by End Use (percent) Original Estimate Current Estimate Consumption 57.7 55.1 Goods 44.0 43.4 Services 13.7 11.6 Investment 31.6 32.5 Other government expenditures 10.8 12.5 127 GNP by Sector of Origin The growth of GNP in 1970 prices is measured as an aggregation of the growth rates of the various sectors of origin. In order to compute the growth of GNP, it is necessary to estimate how much of each type of income (table D-6) was earned in each sector of origin (table D-7). Tables D-8 through D-16 show the distri- bution of each type of income by sector of origin. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-1 Billion Rubles Soviet Household Incomes, 1970 I. State wages and salaries 132.032 2. Net income of households from agriculture 41.709 a. Money wage payments by collective farms 14.453 (I) Payments to collective farm members (2) Payments to hired workers b. Net income from sales of farm products c. Net farm income in kind (1) Consumption in kind (2) Investment in kind 3. Income of the armed forces a. Military pay and allowances 14.040 0.413 8.314 18.942 18.347 0.595 6.580 3.380 b. Military subsistence 3.200 4. Other money income currently earned and 10.598 statistical discrepancy a. Private money income currently earned (1) Private earnings in construction (2) Private earnings in services (a) Housing repair 3.134 0.290 2.844 0.804 (b) Other private repair and personal care 0.836 services (c) Private room rentals (d) Education (e) Health b. Unidentified money income and statistical discrepancy 0.484 0.470 0.250 7.464 5. Imputed net rent 1.080 6. Imputed value of owner-supplied 0.579 construction services 7. Total income currently earned 192.578 8. Transfer receipts 24.628 a. Pensions and allowances 22.300 b. Stipends 1.300 c. Interest income 1.035 d. Net new bank loans to households -0.034 e. Profits distributed to 0.027 consumer cooperative members 9. Total income 217.206 Sources to this table: 1. State wages and salaries are from CIA, GNP 1970, p. 23. 2. Net income of households from agriculture a. Money wage payments by collective farms. (1) Payments to collective farm members are from CIA, GNP 1970, p. 23. (2) Payments to hired workers are from CIA, GNP 1970, p. 23. b. Net income from sales offarm products. This item (8.314 billion rubles) is derived as the difference between gross income from the sale of farm products (9.238 billion rubles-CIA, GNP 1970, p. 23) and purchases of materials and services (0.924 billion rubles-Ibid). c. Net farm income in kind. (1) Consumption in kind is from CIA, GNP 1970, pp. 24-25. (2) Investment in kind, a monetary valuation of the net additions to private livestock inventories, is estimated at 0.595 billion rubles on the basis of the change in numbers of cattle, hogs, sheep and goats, and poultry and the estimated average realized price per head for each animal. The calculation is presented below: Valuation of the Net Additions to Private-Sector Livestock Inventories, 1970 (1) (2) Inventory of Animals (thousand head) (3) (4) (5) Net Additions to Livestock Inventories End End 1969 1970 Thou- sand Head Rubles Per Head Billion Rubles Cattle 24,989 24,953 -36 442 -0.016 Hogs 13,830 16,562 2,732 173 0.473 Sheep and goats 31,665 33,180 1,515 37 0.056 Poultry 360,126 376,480 16,354 5 0.082 Total 0.595 Sources: All data are from CIA, GNP 1970, p. 57, except for poultry. The poultry inventory data are from Selkhoz 1971, p. 273. The poultry price is derived by Margaret Hughes and Barbara Severin in JEC, Agriculture, p. 51. 3. Income of the armed forces a. Military pay. This is a CIA estimate. b. Military subsistence. This is a CIA estimate. 4. Other money income currently earned and statistical discrepancy a. Private money income currently earned. (1) Private earnings in construction (0.290 billion rubles) are based on total expenditures for private housing construction (1.636 billion rubles-Narkhoz 1972, p. 486) and assumptions about the distribu- tion of those expenditures. Contrary to the view expressed in CIA, ' GNP 1970, p. 43 we now believe that the reported value for private housing construction is in current prices rather than 1955 prices. Private housing is constructed by state organizations and by private groups. The value of state-provided private housing construc- tion and repair services in 1970 was 394.7 million rubles (Narkhoz 1972, p. 621). This value is believed to include sales to enterprises, as do the reported sales of other state-provided services. They probably represent repairs done for enterprises without their own repair crews. Based on data published by V. I. Dmitriev (Metodologicheskiye osnovy prognozirovaniya sprosa na bytovyye uslugi, Moscow, Legkaya Industriya, 1975, p. 98), sales to enterprises are estimated 128 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 at 5 percent of state-provided services, or 19.7 million rubles. The remainder (375.0 million rubles) are sales to households. These sales are arbitrarily divided roughly equally between new construction and repair. The resulting distribution of state-provided private housing construction and repair services is as follows: Million Rubles Total sales 394.7 Sales to enterprises 19.7 Sales to households 375.0 Housing repair 187.0 New construction 188.0 Privately provided private housing construction is calculated as total private housing construction (1.636 billion rubles) less state-provided private housing construction (0.188 billion rubles), or 1.448 billion rubles. Of this amount, 60 percent is assumed to be labor payments and 40 percent, materials. The labor payments are further assumed to be one-third hired labor and two-thirds owner-supplied construc- tion services. The resulting distribution of private housing construc- tion expenditures is: Billion Rubles Total private housing construction expenditures 1.636 State-provided construction 0.188 � Privately provided construction 1.448 Materials 0.579 Labor payments 0.869 Private earnings in construction 0.290 Owner-supplied construction services 0.579 (2)Private earnings in services (a) Housing repair earnings (0.804 billion rubles) are estimated as total expenditures on housing repair less purchases of state-provided services and of materials used in privately provided repair services. Household expenditures for housing repair are estimated at 1.258 billion rubles (CIA, GNP 1970, p. 41). Purchases from state enterprises were estimated above in item 4,a,(1) at 0.187 billion rubles; this figure implies that purchases of privately supplied housing repair services were 1.071 billion rubles. Of this amount, expenditures for materials are estimated at 0.267 billion rubles. Private earnings in housing repair are calculated as a residual (1.071 billion rubles less 0.267 billion rubles). The material expenditures of 0.267 billion rubles are determined as total retail sales of construction materials to households (1.221 billion rubles-CIA, GNP 1970, p. 39) less other uses of those materials. Construction materials purchased by households are assumed to be used for privately provided housing repair, for state- provided private housing repair and construction, and for privately provided housing construction. In item 4,a,(1) above the materials used in privately provided housing construction were estimated at 129 0.579 billion rubles. As with other services included in the retail trade statistics, the entire value of state-provided housing construc- tion and repair services is assumed to be included in the listed purchases of construction materials. The residual retail sales of construction materials to households are 0.267 billion rubles: Total retail sales of construction materials to households Billion Rubles 1.221 Less: Materials used in privately provided new 0.579 housing construction Materials used in state-provided private 0.375 housing repair and construction services Equals: Materials used in privately provided housing 0.267 repair services (b) Other private repair and personal care earnings (0.836 billion rubles) are estimated at 90 percent of household expenditures on these services. Expenditures (0.929 billion rubles) are derived as the difference between total household expenditures on privately provid- ed services (2.0 billion rubles-CIA, GNP 1970, p. 42), and expenditures on privately provided housing repair services (1.071 billion rubles-item 4,a,(2),(a) above). (c)Private room rental earnings are from CIA, GNP 1970, p. 42. (d) Education earnings (0.470 billion rubles) are equal to household expenditures for private educational services, which are assumed to be 5 percent of the state wage bill for education. The state wage bill (9.400 billion rubles) is derived in item 1,a of table D-4. (e) Health earnings (0.250 billion rubles) are equal to household expenditures for private health services, which are assumed to be 5 percent of the state wage bill for health. The state wage bill (5.004 billion rubles) is derived in item 1,b of table D-4. b. Unidentified money income and statistical discrepancy. This item is derived as the difference between total income (item 9, below) and the sum of items 1; 2; 3; 4,a; 5; 6; and 8. 5. Imputed net rent. This is from CIA, GNP 1970, p.41. 6. Imputed value of owner-supplied construction services. See item 4,a,(1)above. 7. Total income currently earned. This was derived as the sum of items 1 through 6. 8. Transfer receipts a. Pensions and allowances. See Narkhoz 1972, p. 535. b. Stipends. See CIA, GNP 1970, p. 26. c. Interest income. See CIA, GNP 1970, p. 26. d. Net new bank loans to households. See CIA, GNP 1970, p. 26. e. Profits distributed to consumer cooperative members. See CIA, GNP 1970, p. 23. 9. Total income. This is equal to total outlays (table D-2, item 8). Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-2 Soviet Household Outlays, 1970 Billion Rubles I. Retail sales of goods for consumption 144.931 a. State, cooperative, and commission sales 141.096 (1) Food 84.104 (2) Soft goods 42.734 (3) Durables 14.258 b. Collective farm ex-village market sales 3.835 (1) Food 3.617 (2) Soft goods 0.218 2. Consumer services 23.337 a. Housing 3.429 (1) Gross rent 2.733 (2) Repair 0.696 b. Other services 19.908 (1) Utilities 3.478 (2) Transportation 5.400 (3) Communications 1.200 (4) Repair and personal care 5.497 (5) Recreation 2.547 (6) Education 1.441 (7) Health 0.345 3. Consumption in kind 21.547 a. Farm consumption in kind 18.347 (1) Food 18.235 (2) Soft goods 0.112 b. Military subsistence 3.200 (1) Food 1.970 (2) Soft goods 1.230 4. Total outlays for consumption 189.815 5. Investment 2.231 a. Private housing construction 1.636 b. Farm investment in kind 0.595 6. Total outlays for consumption and investment 192.046 7. Transfer outlays 25.160 a. Net savings 9.720 b. Direct taxes 12.737 c. Other payments to the state 2.703 8. Total outlays 217.206 Sources to this table: I. Retail sales o f goods for consumption a. State, cooperative, and commission sales. Total sales to households of consumption goods are estimated as follows: Billion Rubles Total state and cooperative retail sales, including 155.208 commission sales Less: Sales to institutions 7.177 Producer goods sold to farm households Construction materials sold to households Kerosene 0.462 1.221 0.131 Film rentals Commission sales and sales to rental agencies Business travel expenditures Services included in retail sales Equals: 0.195 0.699 0.301 3.926 Sales of goods to households for consuption 141.096 The values for all items are from CIA, GNP 1970, p. 39 except for commission sales and sales to rental agencies, business travel expenditures, and services included in retail sales. An arbitrary deduction of 1.0 billion rubles is made to cover sales of secondhand goods in commission stores, sales to rental agencies, and purchases of restaurant meals by persons on business travel. These items are known to be included in reported retail sales, but their amounts are unknown. It is further assumed that the latter is equal to 2 percent of the reported sales of public catering establishments (15.033 billion rubles-Narkhoz 1972, p. 578), or 0.301 billion rubles. This amount was subtracted from the 1.0-billion-ruble total to obtain the value for sales of secondhand goods in commission stores and sales to rental agencies. The values of services included in retail trade have been modified from those listed in CIA, GNP 1970, p. 39, as follows: � Sales of laundry and photo services have been added because they are classified as productive services (Ukazaniya, pp. 763-764). � Sales of housing construction and repair services have been deleted because they are believed to be included in the reported retail sales of construction materials, which are deducted as a separate item in the list above. � The values published in the Narkhoz for the repair and tailoring of clothing and the repair of knitwear were doubled to account for the materials used by these services. These materials are included in 130 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 retail sales data but not in the reported sales of the services. A com- parison of the reported sales of these two items with and without materials (Narkhoz 1968, p. 664; and Narkhoz 1969, p. 660) shows that materials are roughly one-half of total sales. The value of productive services included in retail sales is derived in the following tabulation: Producer 0.462 0.462 goods sold to farm house- holds Billion Rubles Con- 1.221 1.221 struction Total productive services 3.9259 materi- als sold Shoe repair 0.3499 to house- Repair and tailoring of clothing 2.0902 holds Processing expenses 1.0451 Kerosene 0.131 0.131 Materials 1.0451 Film rentals 0.195 0.195 Repair of knitwear 0.2404 Commis- 0.699 0.140 0.559 Processing expenses 0.1202 sion sales and Materials 0.1202 sales to Repair of durables 0.4428 rental Furniture repair 0.1006 agencies Dry cleaning 0.0951 Business 0.301 0.301 travel Laundries 0.1647 expendi- Photo services 0.1491 tures Other productive services 0.2931 Services 3.926 3.087 0.839 included Retail sales to households of goods for consumption are divided among food, soft goods, and durables in the tabulation below: in retail Billion Rubles Total Food Soft Durables Other sales Uniden- tified re- tail sales -2.052 -2.053 4.105 Goods and Equals: Uniden- Sales to 141.096 84.104 42.734 14.258 tified house- Total state and cooper- ative retail sales, includ- ing commis- sion sales 155.208 88.948 45.092 14.856 6.312 holds of goods for con- sump- tion Less: Sales to in- 7.177 4.543 1.052 1.253 0.329 stitut ions 131 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-2 (Continued) Sources to this table (Continued): Total sales of food include the entire food category in the enumeration of retail sales by type of good (86.168 billion rubles- Narkhoz 1972. p. 584) plus sales of tobacco goods (2.780 billion rubles-Ibid. p. 585). Total identified sales of soft goods are derived from the Narkhoz data (Ibid. pp, 584-585)as follows: Billion Rubles Total retail sales of soft goods 45.092 Cloth 5.026 Clothing 15.278 Knitwear 8.567 Shoes 7.693 Laundry soap 0.262 Synthetic cleaning materials 0.435 Toilet soap and perfumes 1.176 Haberdashery 3.638 Matches 0.137 Kerosene 0.131 Notebooks and paper 1.015 Publications 1.734 Total identified sales of durables are derived from the Narkhoz data (Ibid. p. 585)as follows: Billion Rubles Total retail sales of durables 14.856 Furniture, carpets, and metal beds 3.604 Metal dishes 0.961 Glass dishes 0.617 Sporting goods 0.542 Radio goods 2.832 Musical instruments 0.281 Toys 0.649 Bicycles and motorbikes 1.009 Watches 0.578 Jewelry 0.533 Electrical goods 2.050 Sewing machines 0.104 Automobiles 0.520 Other household goods 0.576 Other and unidentified retail sales include: window glass (0.050 billion rubles); lumber, cement, and other construction materials (1.500 billion rubles); and an unidentified residual (5.282 billion rubles). The sales to institutions are allocated as in CIA, GNP 1970, pp. 61-62. The 0.329 billion rubles in the other and unidentified column represents institutional purchases of window glass and lumber, cement, and other construction materials. Producer goods sold to farm households and film rentals are assumed to be in the unidentified residual. The value of construction materials sold to households is the difference between: (a) total sales of window glass and lumber, cement, and other construction materials and (b) institutional purchases of the same. Commission sales and sales to rental agencies are believed to consist mainly of used cars, appliances, furniture, jewelry, and the like. Since these are durable goods, it is assumed that 80 percent of these sales are durables and 20 percent are soft goods. The sales of productive services included in retail sales were divided between soft goods and durables. Those allocated to soft goods are: shoe repair, repair and tailoring of clothing, repair of knitwear, dry cleaning, laundries, and 50 percent of other productive services. Those allocated to durables are: repair of durables, furniture repair, photo services, and 50 percent of other productive services. The remaining unidentified retail sales (4.625 billion rubles) were allocated approximately equally between soft goods and durables. b. Collective farm ex-village market sales. The total value of these sales and their allocation between food and soft goods is from CIA, GNP 1970, pp. 40 and 61-62. 2 Consumer services a. Housing. The components of this item have been regrouped to conform more closely with the accounting procedures of the United States and the United Nations. Expenditures on housing now consist of: Billion Rubles Total housing expenditures 3.429 Gross rent 2.733 Cash rent for urban public housing 1.016 Charges paid by members of housing 0.075 cooperatives for maintenance Imputed gross rent on urban private and 1.642 rural housing Repair expenditures by tenants of 0.696 public housing This accounting conforms with the US and UN standard, which treats maintenance expenditures by tenants as a final expenditure and maintenance expenditures by owner-occupiers as a portion of gross rent. b. Other services (I) Utilities are from CIA, GNP 1970, p.41. (2) Transportation expenditures are reduced from those in CIA, GNP 1970, p. 42 by 25 percent to remove estimated business travel expenditures. (3) Communications expenditures are from CIA, GNP 1970, p. 42. (4)Repair and personal care expenditures are derived as the sum of expenditures on state-provided everyday services (4.481 billion 132 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 rubles), privately provided services (0.929 billion rubles), and other services (0.087 billion rubles). The state-provided everyday services are from Narkhoz 1972, p. 621. The Narkhoz data must be adjusted to exclude sales of housing repair and construction and sales to enterprises of all types of services. They also must be adjusted to include the value of materials used in repair and tailoring of clothing and repair of knitwear, which was deducted from the retail sales of goods to households for consumption (item 1, above). According to data published by Dmitriev (Metodologicheskiye osnovy prognozir- ' ovaniya sprosa na bytovyye uslugi, p. 98), 7.6 percent of the total sales reported in the Narkhoz (307.4 million rubles) represent purchases by enterprises. This amount presumably includes sales to enterprises of housing construction and repair services, estimated above at 5 percent of the sales of these services. In order to avoid dou- ble counting these sales, only 95 percent of the published value of housing construction and repair value is deducted. Similarly, the purchases of clothing and knitted materials must be added, net of the portion sold to enterprises. The latter is estimated at 4 percent of reported sales. Total sales of state-provided everyday services to the population are estimated as follows: Million Rubles Total reported sales of everyday services 4,044.4 Less: Enterprise purchases of everyday services 307.4 95 percent of sales of housing construction and 375.0 repair services Plus: 96 percent of materials used in tailoring and 1,003.3 repair of clothing 96 percent of materials used in repair of knitwear 115.4 Equals: Sales of everyday services to households 4,480.7 Household expenditures on privately provided services were estimat- ed in table D-1, item 4,a, (2),(b). Expenditures on other services are from CIA, GNP 1970, p. 42. (5) Recreation expenditures (2.547 billion rubles) have been reduced by 0.100 billion rubles from the value derived in CIA, GNP 1970, p. 42 in order to account for business travel expenses on hotel accommodations. This deduction is an arbitrary value. Household expenditures on recreation are computed as follows: Billion Rubles Total household expenditures on recreation 2.547 Entertainment 1.500 Passes to resorts and the like 0.447 Hotels, motels, and the like 0.062 Private room rentals 0.538 (6)Education expenditures by households consist of expenditures for private services (0.470 billion rubles) and fees for public education (0.971 billion rubles). The former is derived in table D-1, item 4,a,(2), (d) and the later in CIA, GNP 1970, pp. 42-43. 133 (7) Health expenditures by households consist of expenditures for private services (0.250 billion rubles) and fees paid by parents for children's nursery care (0.095 billion rubles). The former is derived in table D-1, item 4,a,(2),(e) and the latter in CIA, GNP 1970, p. 43. 3. Consumption in kind a. Farm consumption in kind. See table D-1, item 2,c,(1). (1) Food is from CIA, GNP 1970, p. 61. (2)Soft goods is from CIA, GNP 1970, pp. 61-62. b. Military subsistence. See table D-1, item 3,b. (1) Food is a CIA estimate. , (2)Soft goods is a CIA estimate. 4. Total outlays for consumption. This was derived as the sum of items 1, 2, and 3. 5. Investment a. Private housing construction. See Narkhoz 1972, p. 486. b. Farm investment in kind. See table D- I, item 2,c,(2). 6. Total outlays for consumption and investment. This was derived as the sum of items 4 and 5. 7. Transfer outlays a. Net savings. This is from CIA, GNP 1970, p. 43. b. Direct taxes. This is from CIA, GNP 1970, p. 43. c. Other payments to the state. This item (2.703 billion rubles) is estimated as the sum of: (1) trade union and other dues (2.066 billion rubles), (2) net lottery ticket purchases (0.254 billion rubles), (3) taxes on land and buildings owned by individuals and coopera- tives (0.211 billion rubles), (4) collective-farm-market fees paid by households (0.050 billion rubles), and (5) other state budget revenue from the population (0.122 billion rubles). Trade union and other dues are now treated as transfer outlays because they are used to finance various social-cultural and administrative activities that are included in public-sector outlays. They are estimated as in CIA, GNP 1970, pp. 40-41, except for Communist Party dues. These dues (0.390 billion rubles) are derived on the basis of: (1) estimated total membership in 1970 of 14,192,174; the average of member- ship figures for 1 January 1970 and 1 January 1971 given in Partiinaya zhizn', No. 14, 1973, pp. 9-10; (2) an estimated average annual wage of members of 1830 rubles-25 percent above the level for all state employees (Narkhoz 1972, p. 516); and (3) a dues rate of 1.5 percent of wages, the applicable rate given in Ustav kommunisticheskoy partiy sovetskogo soyuza, Moscow, Politizdat, 1964, p. 385. Net lottery ticket purchases are from CIA, GNP 1970, p. 43. Taxes on land and buildings owned by individuals and cooperatives are from Gosbyudzhet 1972, p. 77. Collective-farm- market fees paid by households are from CIA, GNP 1970, pp. 23- 24. Other state budget revenue from the population is derived as the difference between total state budget revenues from the population (13.844 billion rubles�Gosbyudzhet 1972, p. 12), and the sum of: (I) direct taxes from the population (12.737 billion rubles�lbid), (2) net bond purchases (0.470 billion rubles�Ibid), (3) net lottery ticket purchases (0.254 billion rubles�lbid), (4) collective-farm-market fees paid by households (0.050 billion rubles�above), and (5) taxes on land and buildings owned by individuals and cooperatives (0.211 billion rubles�above). 8. Total outlays. This was derived as the sum of items 6 and 7. 93-892 0 - 82 - 10 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-3 Billion Rubles Soviet Public-Sector Incomes, 1970 I. Net income retained by organizations a. Retained income of collective farms b. Retained profits of state enterprises c. Retained profits of consumer cooperatives d. Retained profits of other organizations 2. Charges to economic enterprises for special funds 34.809 7.186 26.481 0.821 0.321 14.521 a. Social insurance and social security 9.436 b. Education 0.400 c. Research 2.578 d. Social-cultural measures and sports activities 0.162 e. Militarized guards 0.880 f. Support for administration of higher echelons 1.065 3. Taxes and other payments to the budget 132.077 a. Tax on income of collective farms 0.666 b. Tax on income of consumer cooperatives 0.462 c. Tax on income of other organizations 0.107 d. Deductions from profits of state enterprises 53.110 e. Turnover tax 53.346 f. Miscellaneous charges 24.386 4. Allowances for subsidized losses n.e.c. -22.553 5. Consolidated total charges against current 158.854 product, net of depreciation 6. Depreciation 31.827 7. Consolidated total charges against current 190.681 product 8. Transfer receipts a. Net savings of households b. Direct taxes 25.160 9.720 12.737 c. Other payments to the state 2.703 9. Consolidated net income 215.841 Sources to this table: 1.Net income retained by organizations a. Retained income Qf collective farms. See OA, GNP 1970, p. 45. b. Retained profits of state enterprises. See CIA, GNP 1970, p. 45. c. Retained profits of consumer cooperatives. This item (0.821 billion rubles) is the difference between net profits (1.321 billion rubles) and the sum of (1) income taxes (0.462 billion rubles) and (2) premiums paid to employees (0.038 billion rubles). All data are from CIA, GNP 1970, pp. 45-46. d. Retained profits of other organizations. See CIA, GNP 1970, p. 46. 2. Charges to economic enterprises for special funds a. Social insurance and social security. See CIA, GNP 1970, p. 46. b. Education. See CIA, GNP 1970, p. 46. c. Research. See CIA, GNP 1970, p. 46. d. Social-cultural and sports activities. This item (0.162 billion rubles), estimated as 0.15 percent of total wages of khozraschet enterprises, represents funds paid to trade unions for support of social-cultural and sports activities. A proxy for the total wages of khozraschet enterprises is the total state wage bill (table D-1, item 1) less the wages in health, education, government administrative services, and part of science (the latter taken at half the state budget allocation for science, net of investment). The wage bills of these sectors are shown in table D-8, column 7. e. Militarized guards. This item (0.880 billion rubles) is estimated at half of total current outlays on civilian police (table D-4, item 2,d,[3D. It represents charges to enterprise costs that are known to be incurred for the support of the militarized guard. It is thought that a substantial share of such police are used to guard state reserves and prisoners working on contract in ordinary productive enterprises. f. Administrative expenses of higher echelons. This item (1.065 billion rubles) is estimated at 30.8 percent of total current outlays on state administration, the estimated share of employment in economic administration (trusts, offices, and others) in total state administration employment. The share was extrapolated to 1970 on the basis of its growth between 1960 (24.0 percent) and 1967 (28.6 percent-Trud v SSSR, p. 29). This item is intended to represent the charge to costs of khozraschet enterprises for "support of higher echelons," a standard item in enterprise accounts. Outlays on state administration (3.458 billion rubles) are calculated at 90.5 percent of outlays on state administration and social organizations (3.821 billion rubles-table D-4, item 2,c). This share is derived in CIA, GNP 1970, p. 54. 3. Taxes and other payments to the budget a. Tax on income of collective farms. See CIA, GNP 1970, p. 46. b. Tax on income of consumer cooperatives. See CIA, GNP 1970, p. 46. c. Tax on income of other organizations. See CIA, GNP 1970, p. 46. d. Deductions from profits of state enterprises. See CIA, GNP 1970, p. 46. e. Turnover tax. See Gosbyudzhet 1972, p. 17. f. Miscellaneous charges. The estimate of this item is substantially revised from the method described in CIA, GNP 1970, p. 47. In concept, this item still represents the share of unidentified budget- ary income which is received from current production activity plus 134 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 several miscellaneous identified incomes. Gosbyudzhet 1972 gives � total revenues from the socialist sector and identifies several components (pp. 11-12), leaving a large residual: Billion Rubles Total income from the socialist sector 142.8587 Less: Turnover taxes 49.3798 Payments of state enterprises and other economic 54.1568 organizations from profits Income taxes from kolkhozy and social 1.2344 organizations Social insurance charges 8.2034 Forestry income 0.4924 Equals: Residual 29.3919 Several other income items, which can be estimated or identified from other parts of Gosbyudzhet 1972 or from other sources, reduce this residual substantially: Billion Rubles Residual Less: 29.3919 Local fees from enterprises Rental income Income from reduction of administrative expenses 0.4588 0.0626 1.7000 Republic budget surplus Increase in the supply of money Income from foreign trade Parents' fees for kindergartens Parents' fees for nurseries Price markups on radio and television sets Surcharges on spare parts for agricultural machinery 1.2548 2.0000 7.5810 0.7348 0.0835 0.5100 0.7500 Equals: Revised residual 14.2564 The estimates of income from reduction of administrative expenses and the increase in the supply of money are taken from Igor Birman, Secret Incomes of the Soviet State Budget, The Hague, 135 Martinus Nijhoff Publishers, 1981, pp. 82 and 202. The estimate of surcharges on spare parts for agricultural machinery is derived from the estimate for 1972 in Vladimir G. Treml, Agricultural Subsidies in the Soviet Union, p. 28, and the indication that the 1970 and 1972 values were virtually identical (Vladimir G. Treml, Price Indexes for Soviet I8-Sector Input-Output Tables for 1959-1975, Arlington, Va., SRI International, 1978, p. 96). The estimate of income from foreign trade is derived as the sum of the differences in the prices of exports and imports in domestic and foreign trade prices. Estimatts of exports and imports in domestic prices are from Vladimir G. Treml, and Barry L. Kostinsky, The Domestic Value of Soviet Foreign Trade: Exports and Imports in the 1972 Input-Output Table, US Department of Commerce, Bureau of the Census, Foreign Economic Report No. 20, Washington, D. C., forthcoming. Exports and imports in foreign trade prices are in Narkhoz 1972, p. 737. The revised residual may include income from such sources as: custom duties, gross receipts of budget organizations, miscellaneous levies and nontax revenues, unspent budget allocations, fines, deductions for the road economy, and possibly bank loans to the budget equivalent to the increase in savings deposits of the population. In the absence of information on the content of the revised residual, we assume that 90 percent (12.8303 billion rubles) represents income derived from current production of goods and services. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-3 (Continued) Sources to this table (Continued): Total miscellaneous charges are then computed as the unidenti- fied current income just derived plus those items enumerated in the derivation of the residual that represent current income and are not included elsewhere: Billion Rubles 90 percent of revised budget income residual 12.8308 Plus: Price markups on radio and television sets Forestry income Local fees from enterprises Rental income Income from reduction of administrative expenses 0.5100 0.4924 0.4588 0.0626 1.7000 Surcharges on spare parts for agricultural 0.7500 machinery Income from foreign trade 7.5810 Equals: Miscellaneous charges 24.3856 4. Allowance for subsidized losses. There have been several revisions in the estimation of this item. It now consists of the following subsidies: Billion Rubles Total subsidies 22.553 Price differences on the procurement of agricultural products by industry 13.580 Payments from gross turnover taxes 3.966 Payments from the budget to cover price reductions in retail trade 0.400 Processed feeds 0.475 Fertilizer 0.365 Agricultural machinery and equipment 0.432 Housing 2.086 Budget allocations to the press 0.120 Art and radiobroadcasting 0.628 Recreation 0.501 Price differences on the procurement of agricultural products by industry are from CIA, GNP 1970, p. 49, except that a subsidy to milk products of 0.750 billion rubles has been deducted because it is now known to be netted against profits (Izvestiya akademii nauk, seriya ekonomicheskaya, No. 5, 1975, p. 67 and Vladimir G. Treml, Agricultural Subsidies in the Soviet Union, p. 24). Payments from gross turnover taxes are the difference between gross and net turnover taxes (Gosbyudzhet 1972, pp. 11 and 14). The subsidies for processed feeds, fertilizer, and agricultural machinery and equipment are from Vladimir G. Treml, Price Indexes for Soviet I8-Sector Input-Output Tables, 1959-1975, p. 96. All other subsidies are from CIA, GNP 1970, p. 48. Budgetary outlays on physical culture (0.047 billion rubles) were treated as a subsidy in CIA, GNP 1970. They are now classified as a component of public- sector outlays on physical culture. 5.Consolidated total charges against product, net of depreciation. This was derived as the sum of items 1 through 4. 6. Depreciation. See CIA, GNP 1970, p. 49. 7. Consolodated charges against current product. This was derived as the sum of items 5 and 6. 8. Transfer receipts. See Table D-2, item 7. 9. Consolidated net income. This was derived as the sum of items 7 and 8. 136 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-4 Soviet Public-Sector Outlays, 1970 I. Communal services Billion Rubles 21.268 a. Education 12.939 b. Health 8.268 c. Physical culture 0.061 2. Government administrative services 9.030 a. General agricultural programs 1.004 b. Forestry 0.636 c. State administration and the administrative organs of social organizations 3.821 d. Municipal and related services 3.569 (1) Culture 1.180 (2) Municipal services 0.628 (3) Civilian police 1.761 3. Gross investment 122.143 a. Fixed capital 106.989 (1) New fixed investment 87.989 (a) Machinery and equipment 26.053 (b) Construction and other capital outlays 58.164 (c) Net additions to livestock 3.772 (2) Capital repair 19.000 b. Inventories 15.154 4. Research and development 10.343 5. Outlays n.e.c. 28.429 a. Net exports 0.961 b. Defense n.e.c., unidentified out- lays, and statistical discrepancy 27.468 6. Consolidated total value of goods and services, exclusive of sales to households 191.213 7. Transfer outlays 24.628 a. Pensions and allowances 22.300 b. Stipends 1.300 c. Interest payments to households 1.035 d. Net new bank loans to households -0.034 e. Profits distributed to consumer cooperative members 0.027 8. Consolidated total outlays 215.841 Sources to this table: I. Communal services a. Education. Public-sector outlays on education are estimated at 12.939 billion rubles: the sum of wages (9.400 billion rubles), social insurance (0.517 billion rubles), and other current outlays (3.993 billion rubles), less parents' fees for education (0.971 billion rubles). 137 Wages are derived from reported employment (7.246 million- Narkhoz 1978, p. 366) and the average wage rate (108.1 rubles per month-Ibid. p. 373). Social insurance is calculated as 5.5 percent of the wage bill (CIA, GNP 1970, p. 52). The method of estimating other current outlays is complicated and set out in full in the description of the end-use education index (JEC, Consumption). Only a summary is given here. Budgetary education expenditures are divided between general education and higher education (Gosbyudzhet 1971, pp. 27-28). The budget handbooks provide additional details on certain educational subca- tegories of these two expenditure categories (for example, primary and secondary schools-lbid, pp. 84-94) for the republic budgets only. Included are such items as wages, social insurance, stipends, and investment in equipment. For each of these educational subcategories, other (nonlabor) current outlays and total current outlays are computed. Then both items are summed for general and higher education and the percentage of other current outlays in total current outlays is computed. Finally, total budgetary expendi- tures for the USSR for the two categories are multiplied by the percentage of other current outlays and the results summed to arrive at total other current outlays. Parents' fees for education are derived in CIA, GNP 1970, p. 42. b. Health. Outlays for health are estimated at 8.268 billion rubles: the sum of wages (5.004 billion rubles), social insurance (0.275 billion rubles), and other current outlays (3.084 billion rubles), less parents' fees for health (0.095 billion rubles). These components are estimated jointly with expenditures on physical culture (item 1,c below) in the following tabulation: Outlays on Health and Physical Culture Billion Rubles Total Physical Culture Health Wages and social insurance 5.916 0.637 5.279 Wages 5.608 0.604 5.004 Social insurance 0.308 0.033 0.275 Other current outlays from the budget 3.106 0.022 3.084 Other current outlays from other sources 0.350 0.350 Subsidy -0.501 -0.501 Parents' fees -0.542 -0.447 -0.095 Total 8.329 0.061 8.268 Total wages in health and physical culture are derived from reported employment in health, which includes physical culture (5.080 million-Narkhoz 1978, p. 366), and the average wage rate (92.0 rubles per month-lbid, p. 373). Total social insurance is calculated as 5.5 percent of the wage bill (CIA, GNP 1970, p. 53). It Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-4 (Continued) Sources to this table (Continued): was assumed that the shares of other (nonlabor) current outlays in total expenditures were the same in both health and physical culture. The estimate resulting from this assumption is that other current expenditures are 36.9 percent of total expenditures. Total expenditures on physical culture are estimated at 1.009 billion rubles, the sum of public-sector outlays (0.061 billion rubles- item 1,c below), the subsidy for recreation (0.501 billion rubles- table D-3, item 4), and household expenditures for passes to resorts and the like (0.447 billion rubles-CIA, GNP 1970, p. 42). Other current outlays are 36.9 percent, or 0.372 billion rubles of total expenditures. Of this total, 0.022 billion rubles represent budgetary expenditures. Wages and social security payments in physical culture are then determined as total outlays less other current outlays, or 0.637 billion rubles. This in turn determines wages and social insurance in health as 5.279 billion rubles (5.916 billion rubles in health and physical culture less 0.637 billion rubles in physical culture). Finally, other current outlays from the budget are determined as they were for education. Other current outlays are computed as a percentage of total current outlays for identified republic budgetary expenditures and then multiplied by total budgetary health expen- ditures. The result is an estimate of other current outlays in health and physical culture of 3.106 billion rubles. Subtracting the estimated outlays of physical culture of 0.022 billion rubles pro- duces outlays on health alone of 3.084 billion rubles. c. Physical culture. Public-sector outlays on physical culture are 0.061 billion rubles, the sum of budgetary expenditures (0.047 billion rubles-Narkhoz 1970, p. 734) and other expenditures (0.014 billion rubles). V. Cao-Pinna and S. S. Shatalin published a value for 1969 of public-sector outlays of 0.053 billion rubles (Consumption Expenditures in Eastern and Western Europe, New York, Pergamon Press, 1979, p. 116). Budgetary outlays in 1969 were 0.041 billion rubles (Narkhoz 1970, p. 734). Assuming the relationship between budgetary and other expenditures in 1969 is the same in 1970, then total outlays in 1970 are: (0.047) x (0.053/0.041) = 0.061 billion rubles. 2. Government Administrative Services a. General agricultural programs. This item is the sum of wages (0.721 billion rubles), social insurance deductions (0.032 billion rubles), and other current outlays (0.251 billion rubles). Wages are derived from employment (0.586 million) and the average wage rate (102.5 rubles per month). Employment is determined as the differ- ence between total state agricultural employment (9.419 million- Narkhoz 1978, p. 366) and employment in state farms and other state enterprises (8.833 million-Ibid). The wage rate is determined from the difference in the wage rates for total state agriculture (101.0 rubles per month-Ibid. p. 372) and state farms and other state organizations (100.9 rubles per month-Ibid). The following tabulation shows the calculation: Employ- ment (million people) Wage Rate (rubles per month) Monthly Wages (billion rubles) Total state agriculture 9.419 101.0 0.951 State farms and other state enterprises 8.833 100.9 0.891 General agricultural programs 0.586 102.5 0.060 Social insurance deductions are derived as 4.4 percent of wages (CIA, GNP 1970, p. 53). Other current outlays are estimated as one- fourth of current outlays, a reduction from the one-third used in CIA, GNP 1970 (p. 53) for government administrative services. The lower share is based on fragmentary evidence that labor costs comprise the vast bulk of outlays on these government services. The share would be lower than in education (31 percent-item 1,a above) and health (37 percent-item 1,b above), where food costs are large. b. Forestry. Total outlays are estimated as 0.636 billion rubles: the sum of wages (0.457 billion rubles), social insurance deductions (0.020 billion rubles), and other current outlays (0.159 billion rubles). Wages are derived from employment (0.433 million- Narkhoz 1978, p. 366) and the average wage rate (88 rubles per month). The wage rate, not published in the Narkhoz, is from G. I. Vorob'ev et al (Lesnoye khozyaystvo SSSR, Moscow, Lesnaya Promyshlennost', 1977, p. 331). Social insurance deductions are calculated at 4.4 percent of wages (CIA, GNP 1970, p. 53). Other current outlays are estimated to be one-fourth of total current outlays. c. State administration and the administrative organs of social organizations. This item is a combination of two sectors in CIA, GNP 1970: (1) state administration, and (2) the administrative organs of social organizations. The separation of the two sectors in CIA, GNP 1970 was somewhat arbitrary, and we used the same man-hour employment index to measure changes in the activity level of both sectors. It was decided therefore to use one combined sector in this report. Total outlays are estimated at 3.821 billion rubles-the sum of wages (2.717 billion rubles), social insurance deductions (0.149 billion rubles), and other current outlays (0.955 billion rubles). Wages are derived from employment (1.838 million-Narkhoz 1978, p. 366) and the average wage rate (123.2 rubles per month- Ibid. p. 372). Social insurance deductions are calculated at 5.5 percent of the wage bill (CIA, GNP 1970, p. 54). Other current outlays are assumed to be one-fourth of total current outlays. 138 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 d. Municipal and related services. (1)Culture outlays are estimated at 1.180 billion rubles�the sum of wages (0.839 billion rubles), social insurance deductions (0.046 billion rubles), and other current outlays (0.295 billion rubles). The wage bill is derived from employment (0.824 million�Narkhoz 1978, p. 366) and the aver- age wage rate (84.8 rubles per month�Ibid, p. 372). Social insurance deductions are calculated at 5.5 percent of the wage bill (CIA, GNP 1970, p. 52). Other current outlays are assumed to be one-fourth of total current outlays. (2) Municipal services are estimated at 0.628 billion rubles�the sum of wages (0.450 billion rubles), social insurance deductions (0.021 billion rubles), and other current outlays (0.157 billion rubles). The wage bill is derived from employment (0.397 million) and the average wage rate (94.5 rubles per month). Employment is derived as 13 percent of the employment of the housing-communal economy (3.052 million�Narkhoz 1978, p. 366). The wage rate is assumed to be equal to that of the total housing-communal sector (Ibid, p. 373). Social insurance deductions are calculated as 4.7 percent of the wage bill (CIA, GNP 1970, p. 54). Other current outlays are assumed to be one-fourth of total current outlays. (3) Civilian police outlays are estimated as 1.761 billion rubles�the sum of wages (1.235 billion rubles), social insurance deductions (0.086 billion rubles), and other current outlays (0.440 billion rubles). The wage bill is derived from employment (0.675 million) and an estimated wage rate (152.5 rubles per month). Employment is estimated to be 67.6 percent of the Narkhoz employment category "other branches of material production" (0.998 million� Narkhoz 1978, p. 366). The wage rate is assumed to be 25 percent above the average wage rate of all state workers and employees (122.0 rubles per month�Ibid). This assumption results from the calculation of the implicit wage rate for the forestry and other branches of material production sectors, the two sectors for which wage data are not published in the Narkhoz. This type of calcula- tion is subject to rounding errors, but a study of several years shows that the implicit wage rate is consistently higher than the average for all state workers and employees. Social insurance deductions are assumed to be 7.0 percent of the wage bill. Other current outlays are assumed to be one-fourth of total current outlays. 3. Gross Investment a. Fixed capital. (1) Machinery and equipment is estimated at 26.053 billion rubles: the sum of new fixed investment in machinery and equipment (25.300 billion rubles), changes in warehouse stocks of equipment requiring installation (-0.137 billion rubles), and the acquisition of equipment by budget institutions (0.890 billion rubles). New fixed investment is reported in Narkhoz 1972, (p. 474) as the "equipment, instruments, and inventory," component of capital investment. This value is said to be in 1969 estimate prices. 139 How those prices compare to 1970 prices is uncertain. The wholesale price index for the output of the machine-building and metalworking branch of industry shows no change in 1970 com- pared with 1969. Western studies have suggested that there is a persistent upward trend in price, but no precise estimates of yearly changes are available. Here it is assumed that there was no change between 1969 estimate prices and 1970 expenditures. The change in warehouse stocks of equipment requiring installa- tion is from CIA, GNP 1970, p. 55. The acquisition of equipment by budget-supported institutions is not included in Soviet invest- ment data. This value was estimated by increasing the reported value for outlays by union-republic budgets (0.6506 billion rubles� G'osbyudzhet 1972, p. 78) to include outlays from the union budget. In 1970 union-republic budgets financed 73.1 percent of total outlays on education, culture, health, physical culture, science, and administration (Ibid, pp. 33, 34, 60, 69, and 72). It is assumed that this relationship is also true for the acquisition of equipment. (2) Construction and other capital outlays are estimated as the difference between total expenditures on construction and other capital outlays (59.8 billion rubles) and private expenditures on housing construction (1.636 billion rubles�table D-2, item 5,a). Total outlays on construction and other capital outlays are derived as the difference between the gross output of the construction sector (67.6 billion Narkhoz 1978, p. 41) and estimated expenditures on capital repair of structures (7.8 billion rubles�appendix C). (3) Net additions to livestock in the public sector are derived in same manner as in the private sector (table D-1, item 2,c,[2j). The calculation is shown below. Valuation of the Net Additions to Public-Sector Livestock Inventories, 1970 (1) (2) (3) (4) (5) Inventory of Animals Net Additions to (thousand head) Livestock Inventories End End Thousand Rubles Billion 1969 1970 Head Per Rubles Head Cattle 70,173 74,272 4,099 442 1.812 Hogs 42,225 50,921 8,696 173 1.504 Sheep and goats 104,138 110,241 6,103 37 0.226 Poultry 230,213 276,192 45,979 5 0.230 Total 3.772 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-4 (Continued) Sources to this table (Continued): Sources: All data are from CIA, GNP 1970, p. 57, except for poultry. The poultry inventory data are from Selkhoz 1971, p. 273. The poultry price is derived by Margaret Hughes and Barbara Severin in JEC, Agriculture, p. 51. (4) Capita/ repair is derived as the sum of collective-farm outlays (0.918 billion rubles), amortization deductions for capital repair (14.663 billion rubles), and budget expenditures for capital repair (3.419 billion rubles). The collective-farm outlays are from CIA, GNP 1970, p. 55. The amortization deductions are from Narkhoz 1978, p. 532. The budget expenditures reported for union-republic budgets (2.4993 billion rubles�Gosbyudzhet 1971, p. 81) are assumed to represent 73.1 percent of total budget-financed capital repair expenditures, the same share as used in the derivation of the acquisition of equipment by budget-supported institutions in item 3,a,(1) above. b. Inventories. See CIA, GNP 1970, p. 55. 4. Research and development. This item is derived as the sum of wages (5.020 billion rubles), social insurance deductions (0.276 billion rubles), depreciation (0.165 billion rubles), profits (0.094 billion rubles), charges for special funds (0.325 billion rubles), and material expenditures (4.463 billion rubles). The wage bill is derived from employment (2.999 million�Narkhoz 1978, p. 366) and the average wage rate (139.5 rubles per month�Ibid, p. 373). Social insurance deductions are calculated as 5.5 percent of the wage bill (CIA, GNP /970, p. 56). Depreciation, profits, and charges for special funds are estimated in table D-9. Material expenditures are estimated in the same manner, as the corresponding component of the research and development index (appendix B, table B-18). 5. Outlays n.e.c. a. Net exports. This was derived as the difference between total exports and total imports valued in foreign trade prices (Narkhoz 1978, p. 547). b. Defense n.e.c., unidentified outlays, and statistical discrepancy. This was derived as the difference between total outlays (item 8) and the sum of items 1 through 4; 5,a; and 7. 6. Consolidated total value of goods and services exclusive of sales to households. This was derived as the sum of items 1 through 5. 7. Transfer outlays. See table D-1, item 8. 8. Consolidated total outlays. These are equal to total incomes, table D-3, item 9. 140 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-5 Soviet Gross National Product in Established Prices by End Use, 1970 1. Consumption a. Goods Billion Rubles 211.083 . 166.478 (1) Food 107.926 (2) Soft goods 44.294 (3) Durables 14.258 b. Services 44.605 (1) Housing 3.429 (2) Utilities 3.478 (3) Transportation 5.400 (4) Communications 1.200 (5) Repair and personal care 5.497 (6) Recreation 2.608 (7) Education 14.380 (8) Health 8.613 2. Investment 124.374 a. New fixed investment 90.220 (1) Machinery and equipment 26.053 (2) Construction and other capital outlays 59.800 (3) Net additions to livestock 4.367 b. Capital repair C. Inventories 19.000 15.154 3. Other public-sector expenditures 47.802 a. Government administrative services 9.030 (1) General agricultural programs (2) Forestry (3) State administration and the administra- tive organs of social organizations 1.004 0.636 3.821 (4) Municipal and related services (a) Culture (b) Municipal services (c) Civilian police b. Research and development c. Outlays n.e.c. (1) Net exports 3.569 1.180 0.628 1.761 10.343 28.429 0.961 (2) Defense n.e.c., unidentified outlays, and 27.468 statistical discrepancy 4. Gross national product 383.259 141 Sources to this table: I. Consumption a. Goods (1) Food is the sum of items 1,a,(1); 1,b,(1); 3,a,(1); and 3,b,(1) in table D-2. (2) Soft goods is the sum of items 1,a,(2); 1,b,(2); 3,a,(2); and 3,b,(2) of table D-2. (3) Durables. See table D-2, item 1,a,(3). b. Services (1) Housing. See table D-2, item 2,a. (2) Utilities. See table D-2, item 2,b,(1). (3) Transportation. See table D-2, item 2,b,(2). (4) Communications. See table D-2, item 2,b,(3). (5) Repair and personal care. See table D-2, item 2,b,(4). (6) Recreation. See table D-2, item 2,b,(5); and table D-4, item 1,c. (7) Education. See table D-2, item 2,b,(6); and table D-4, item 1,a. (8) Health. See table D-2, item 2,b,(7); and table D-4, item 1,b. 2. Investment a. New fixed investment (1) Machinery and equipment. See table D-4, item 3,a,(1 ),(a). (2) Construction and other capital outlays. See table D-2, item 5,a; and table D-4, item 3,a,(1),(b). (3) Net additions to livestock. See table D-2, item 5,b; and table D- 4, item 3,a,(1),(c). b. Capital repair. See table D-4, item 3,a,(2). c. Inventories. See table D-4, item 3,b. 3. Other public-sector expenditures a Government administrative services. See table D-4, item 2. b. Research and development. See table D-4, item 4. c. Outlays n.e.c. See table D-4, item 5. 4 Gross national product. This is the sum of items 1 through 3. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-6 Billion Rubles Soviet Gross National Product in Established Prices by Type of Income, 1970 1. Wage bill 135.412 a. State wages and salaries 132.032 b. Military pay and allowances 3.380 2. Other and imputed income 62.251 a. Net income of households from agriculture 41.709 b. Military subsistence 3.200 c. Other money income currently earned 10.598 and statistical discrepancy d. Imputed net rent 1.080 e. Imputed value of owner-supplied construction 0.579 services f. Charges to economic enterprises for special 5.085 funds (1) Education (2) Research (3) Social-cultural measures and sports activities 0.400 2.578 0.162 (4) Militarized guards 0.880 (5) Support for administration of higher 1.065 echelons 3. Social insurance 4. Profits a. State enterprises (1) Retained profits of state enterprises (2) Deductions from profits of state enterprises 9.436 89.154 79.591 26.481 53.110 b. Collective farms (1) Retained income of collective farms (2) Tax on income of collective farms c. Consumer cooperatives (1) Retained profits of consumer cooperatives (2) Tax on income of consumer cooperatives d. Other organizations (1) Retained profits of other organizations (2) Tax on income of other organizations 5. Depreciation 6. Turnover and other indirect taxes a. Turnover taxes b. Miscellaneous charges 7.852 7.186 0.666 1.283 0.821 0.462 0.428 0.321 0.107 31.827 77.732 53.346 24.386 7. Allowances for subsidized losses n.e.c. -22.553 8. Gross national product 383.259 Sources to this table: 1. Wage Bill a. State wages and salaries. See table D-1, item 1. b. Military pay and subsistence. See table D-1, item 3,a. 2. Other and Imputed Income a. Net income of households from agriculture. See table D-1, item 2. b. Military subsistence. See table D-1, item 3,b. c. Other money income currently earned and statistical - discrepancy. See table D-1, item 4. d. Imputed net rent. See table D-1, item 5. e. Imputed value of owner-supplied construction services. See table D-1, item 6. f. Charges to economic enterprises for special funds. See table D- 3, items 2,h; 2,c; 2,d; 2,e; and 2,f. 3. Social insurance. See table D-3, item 2,a. 4. Profits a. State enterprises (1) Retained profits of state enterprises. See table D-3, item 1,b. (2) Deductions from profits of state enterprises. See table D-3, item 3,d. b. Collective farms (1) Retained income of collective farms. See table D-3, item 1,a. (2) Tax on income of collective farms. See table D-3, item 3,a. c. Consumer cooperatives (1) Retained profits of consumer cooperatives. See table D-3, item 1,c. (2) Tax on income of consumer cooperatives. See table D-3, item 3,b. d. Other organizations (1) Retained profits of other organizations. See table D-3, item 1,d. (2) Tax on income of other organizations. See table D-3, item 3,c. 5. Depreciation. See table D-3, item 6. 6. Turnover and other indirect taxes a. Turnover taxes. See table D-3, item 3,e. b. Miscellaneous charges. See table D-3, item 3,f. 7. Allowance for subsidized losses. See table D-3, item 4. 8. Gross national product. This was derived as the sum of items 1 through 7. 142 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-7 Soviet Gross National Product in Established Prices by Sector of Origin, 1970 Billion Rubles (8) Total (1) States Wage Bill (2) Other and Imputed Income (3) Social Insurance Deductions (4) (5) Depreciation Profits (6) Turnover and Other Indirect Taxes (7) Subsidies Total 135.412 62.251 9.436 31.827 89.154 77.732 -22.553 383.259 Industry 49.535 5.275 3.571 14.893 52.385 68.861 -18.688 175.832 Ferrous metals 2.539 0.271 0.200 1.430 3.355 -0.363 0 7.432 Nonferrous metals 1.548 0.165 0.122 0.798 2.321 -0.194 0 4.760 Fuels 3.717 0.397 0.328 2.321 3.866 4.467 0 15.096 Electric power 1.065 0.114 0.070 1.602 2.476 0.663 0 5.990 Machinery 19.461 2.070 1.491 3.247 14.186 5.768 -0.432 45.791 Chemicals 2.613 0.279 0.218 1.150 3.927 2.016 -0.365 9.838 Wood, pulp, and paper 4.648 0.495 0.219 1.077 3.127 1.383 0 10.949 Construction materials 3.768 0.401 0.230 0.963 1.601 0.725 0 7.688 Light industry 5.174 0.551 0.351 0.440 6.288 25.857 -5.306 33.355 Food industry 4.185 0.446 0.283 1.291 6.899 27.224 -12.110 28.218 Other industry 0.817 0.086 0.059 0.574 4.339 1.315 -0.475 6.715 Construction 16.889 2.669 1.025 2.147 4.454 1.125 0 28.309 Agriculture 12.033 42.991 1.696 5.531 12.494 3.836 0 78.581 Transportation 10.294 1.096 0.545 5.081 10.081 1.121 0 28.218 Communications 1.545 0.164 0.082 0.383 0.790 0.107 -0.370 2.701 Trade 8.748 0.932 0.395 1.323 6.679 0.726 -0.530 18.273 Services 32.174 5.866 1.772 2.423 2.177 1.786 -2.845 43.353 Housing 1.765 2.011 0.083 1.318 0 0.194 -2.086 3.285 Utilities 0.594 0.043 0.028 0.308 0.724 0.070 0 1.767 Repair and personal care 2.277 0.998 0.146 0.193 0.376 0.165 0 4.155 Recreation 1.176 0.568 0.064 0.284 0.466 0.074 -0.759 1.873 Education 9.400 1.001 0.517 0 0 0.452 0 11.370 Health 5.004 0.533 0.275 0 0 0.241 0 6.053 Science 5.020 0.312 0.276 0.165 0.094 0.243 0 6.110 Credit and insurance 0.519 0.037 0.029 0.155 0.517 0.052 0 1.309 Government admin- istrative services 6.419 0.363 0.354 0 0 0.295 0 7.431 General agricul- tural programs 0.721 0.041 0.032 0 0 0.033 0 0.827 143 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-7 (Continued) Soviet Gross National Product in Established Prices by Sector of Origin, 1970 Billion Rubles (6) Turnover and Other Indirect Taxes (7) Subsidies (8) Total (1) States Wage Bill (2) Other and Imputed Income (3) Social Insurance Deductions (4) (5) Depreciation Profits Forestry 0.457 0.026 0.020 0 0 0.021 0 0.524 State administra- lion and the administrative organs of social organizations 2.717 0.154 0.149 0 0 0.124 0 3.144 Culture 0.839 0.047 0.046 0 0 0.039 0 0.971 Municipal services 0.450 0.025 0.021 0 0 0.021 0 0.517 Civilian police 1.235 0.070 0.086 0 0 0.057 0 1.448 Military personnel 3.380 3.200 0.240 0 0 0 0 6.820 Other branches 0.814 0.058 0.110 0.046 0.094 0.170 -0.120 1.172 Sources for this table: I. State wage bill. See table D-8, column 7. 2. Other and imputed income. See table D-10, column 9. 3. Social insurance. See table D-11, column 7. 4. Depreciation. See table D-13, column 4. 5. Profits. See table D-15, column 7. 6. Turnover and other indirect taxes. See table D-16, column 6. 7. Subsidies. See table D-16, column 5. 8. Gross national product. This was derived as the sum of columns 1 through 7. 144 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-8 Billion Rubles Distribution of the State Wage Bill by Sector of Origin, 1970 (1) Unadjusted State Wage Bill (2) (3) Adjustments for: (4) (5) (6) (7) Adjusted State Wage Bill 135.412 49.535 2.539 Repair and Personal Care Housing- Communal Economy Recreation Civilian Police Transpor- tation Total 135.412 0 0 0 0 0 0.714 Industry 50.549 -1.728 0 0 0 Ferrous metals 2.502 0 0 0 0 0.037 Nonferrous metals 1.526 0 0 0 0 0.022 0.054 1.548 3.717 1.065 Fuels 3.663 0 0 0 0 Electric power 1.050 0 0 0 0 0.015 Machinery 19.378 -0.197 0 0 0 0.280 19.461 2.613 4.648 Chemicals 2.575 0 0 0 0 0.038 Wood, pulp, and paper 4.623 -0.042 0 0 0 0.067 Construction materials 3.714 0 0 0 0 0.054 3.768 5.174 4.185 0.817 16.889 12.033 10.294 1.545 8.748 32.174 1.765 0.594 2.277 1.176 9.400 5.004 Light industry 6.219 -1.120 0 0 0 0.075 0.060 0.012 0.606 Food industry 4.125 0 0 0 0 Other industry 1.174 -0.369 0 0 0 Construction 16.283 0 0 0 0 Agriculture 10.695 0 0 0 0 1.338 -2.805 Transportation 13.099 0 0 0 0 Communications 1.545 0 o o o o Trade 8.601 0 0 0 0 0.147 Services 29.211 1.728 0 0 1.235 0 Housing 3.461 0 -1.696 0 0 0 Utilities 0 0 0.594 0 0 0 Repair and personal care 0 1.728 0.549 0 0 0 Recreation 0.469 0 0.103 0.604 0 0 Education 9.400 0 0 0 0 0 Health 5.608 0 0 -0.604 0 0 Science 5.020 0 0 0 0 0 5.020 0.519 Credit and insurance 0.519 0 0 0 0 0 Government administrative services 4.734 0 0.450 0 1.235 0 6.419 General agricultural programs 0.721 0 0 0 0 0 0.721 0.457 2.717 0.839 0.450 1.235 3.380 0.814 Forestry 0.457 0 0 0 0 0 State administration and the administrative organs of social organizations 2.717 0 0 0 0 0 Culture 0.839 0 0 0 0 0 Municipal services 0 0 0.450 0 0 0 0 0 Civilian police 0 0 0 0 1.235 Military personnel 3.380 0 0 0 0 Other branches 2.049 0 0 0 1.235 0 145 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-8 (Continued) Distribution of the State Wage Bill by Sector of Origin, 1970 Sources to this table: 1. Unadjusted state wage bill. The total state wage bill is derived in table D-6, item 1, as the sum of state wages and salaries (132.032 bil- lion rubles) and military pay and allowances (3.380 billion rubles). The services and government administrative services line items are derived as the sum of their parts. The military personnel line item is from table D-6, item 1,b. All other line items are from table D-9, col- umn 3. The line items in table D-9 are the Soviet employment categories, while those in this table are our GNP sectors. The data from table D-9 are placed in the GNP sectors in this table which con- tain most of the wages. Columns 2-6 reallocate wages from the Soviet categories to conform with the definitions of our GNP sectors. 2. Repair and personal care. The Soviets consider the repair and custom production of consumer goods to be part of the productive sphere and include the employees engaged in these activities with the corresponding branches of industry. In order to estimate the value added in these services, we reallocate the wages from industry to the repair and personal care sector. Employment in these services, given in Vestnik statistiki (no. 8, 1973), p. 95, is assumed to be located in the following industrial branches in the Soviet employment data: Soviet Type of Employment Employment Service (thousands) Category Total 1,299 Machinery Repair of durables 122 Wood, pulp, and paper Furniture repair 26 Light industry Shoe repair 138 Repair and tailoring 709 of clothing Repair of knitwear Other industry Dry cleaning Laundries Photo services Other services 57 37 66 51 93 In the absence of wage data for these services, it is assumed that the average monthly wage in each service is the same as the average monthly wage in its corresponding branch of industry. The wage rates are shown in table D-9, column 2. 3. Housing-communal economy. Employment in the housing- communal economy category of the Soviet employment data belong to the housing, repair and personal care, utilities, recreation, and municipal services sectors of our GNP accounts. The distribution of these employees is estimated to be: Employment (thousands) Housing-communal economy 3,052 Housing 1,557 Municipal services 397 Recreation (hotels) 91 Repair and personal care 484 Utilities 523 Employment in the housing and in municipal services are estimated at 51 and 13 percent, respectively, of total housing- communal employment (CIA, GNP 1970, pp. 54 and 75). Hotel employment is from CIA, GNP 1970, p. 42. Repair and personal care employment is derived as total repair and personal care employment (1,869,000� Vestnik statistiki, No. 8, 1973, p. 95) less employment in industrial repair and personal care services (1,299,000, item 2 above) and less employment in repair and construction of housing (86,000�Ibid). Utilities employment is derived as a residual. It is assumed that the average monthly wage rate for each employment group is 94.5 rubles, the average for the entire housing-communal economy category (table D-9, column 2). 4. Recreation. The Soviet health category in table D-9 includes physical culture employment at resorts and sanatoriums, which are primarily used as vacation spots. Their wages are derived in table D-4, item 1,b. 5. Civilian police. It is thought that employment in the other branches of material production category in table D-9 includes militarized guards and civilian police. Their wages, which are derived in table D-4, item 2,d,(3), are reallocated here to the civilian police sector. 6. Transportation. Employment in transportation in table D-9 includes many employees in trucking organizations that are subordi- nate to enterprises in other sectors of the economy. This activity is equivalent to force-account trucking in the United States, and the employees involved are included in the various nontransportation sectors in US statistics. The primary activities in the Soviet Union are delivery of construction materials, conveying agricultural produce, and short-haul delivery of industrial goods. Using data from the 1966 and 19721-0 tables and various sources on the different transportation modes, it is estimated that 1.666 million employees were engaged in this type of work in 1970. This employment is reallocated to other sectors according to ton- kilometer data for this type of trucking given in Transport i svyaz', Moscow, Statistika, 1972, p. 221, as shown in the following tabulation: Sector Billion Ton- Kilometers Percent Employment (million persons) Total 100.0 1.666 Industry 33.1 25.5 0.424 Construction 28.1 21.6 0.360 Agriculture 62.0 47.7 0.795 Trade 6.8 5.2 0.087 The average monthly wage for these employees is assumed to be 140.3 rubles, the rate given in Narkhoz 1979, p. 395, for the transportation subcategory which includes this type of activity. Within industry, these wages are allocated proportionally to the wage bill of each branch of industry. 7. Adjusted state wage bill. This was derived as the sum of columns 1 through 6. 146 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-9 State Wages and Salaries, 1970 (3) State Wage Bill (billion rubles) . (1) Average Annual Employment (million persons) (2) Average Monthly Wage (rubles) Total 90.186 122.0 132.032 Industry 31.593 133.3 50.549 Ferrous metals 1.359 153.4 2.502 Nonferrous metals 0.663 191.8 1.526 Fuels 1.542 198.0 3.663 Electric power 0.633 138.2 1.050 Machinery 12.017 134.4 19.378 Chemicals 1.568 136.9 2.575 Wood, pulp, and paper 2.848 135.3 4.623 Construction materials 2.258 137.1 3.714 Light industry 5.019 103.3 6.219 Food industry 2.901 118.5 4.125 Other industry 0.785 124.6 1.174 Construction 9.052 149.9 16.283 Agriculture 8.833 100.9 10.695 Transportation 7.985 136.7 13.099 Communications 1.330 96.8 1.545 Trade 7.537 95.1 8.601 Other branches of material production 0.998 171.1 2.049 Housing-communal economy 3.052 94.5 3.461 Art 0.412 94.8 0.469 Education 7.246 108.1 9.400 Health 5.080 92.0 5.608 Science 2.999 139.5 5.020 Credit and insurance 0.388 111.4 0.519 General agricultural programs 0.586 102.5 0.721 Forestry 0.433 88.0 0.457 State administration and the administrative organs of social organizations 1.838 123.2 2.717 Culture 0.824 84.8 0.839 147 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-9 (Continued) Sources to this table: 1. Average annual employment. All employment data are from Narkhoz 1979, pp. 387-388, except for the branches of industry and for general agricultural programs. Employment in the branches of industry are from Vestnik statistiki, No. 11, 1972, p. 93, except for the nonferrous metals and other industry branches. Employ- ment in nonferrous metals is from Steven Rapawy, Civilian Em- ployment in the U.S.S.R., p. 4. Employment in other industry is derived as a residual. Employment in general agricultural programs is derived as the difference between total reported employment in state agriculture and employment in "state farms, interfarm eco- nomic enterprises, subsidiary and other productive agricultural enterprises" (table D-4, item 2,a). 2. Average monthly wage. All average monthly wage rates are from Narkhoz 1979, pp. 394-395, except for the branches of industry, other branches of material production, general agricultural pro- grams, and forestry. The average monthly wage rates in the branches of industry, except for nonferrous metals, and other branches of material production, are determined as the state wage bill in column 3 divided by 12 times the employment in column 1. It is assumed that the average monthly wage in nonferrous metals is 25 percent higher than that in ferrous metals, based on evidence from the 1959 and 1966 1-0 tables. The wage rates for general agricultural programs and forestry are from table D-4, items 2,a and 2,b. 3. State wage bill. The wage bill in total industry and in each branch of industry is from Vestnik statistiki, No. 11, 1972, p. 94, except for the fuels, nonferrous metals, and other industry branches. The wage bill in nonferrous metals is derived as 12 times the product of the employment in column 1 and the average wage rate in column 2. The wage bill in the fuels sector is determined from relationships among the fuel sectors in the 1972 I-0 table. The calculations are shown in the following tabulation: Employment and Wage Data From the 1972 Input-Output Table (1) (2) (3) Employ- Total Average ment Wages Wages per (thousands) (million Employee rubles) (rubles) (4) Column 3 as a Percent of Wages in the Coal Sector (percent) 1970 Employment, Wage, and Social Security Data (5) (6) Average Employ- Wages ment per (thou- Employee sands) (rubles) (7) (8) (9) Total Social Social Wages Insurance Insurance (million Rate Deductions (rubles) (percent) (million rubles) Coal 2,682 1,120 3,004 9.0 270 Oil extrac- 1,749 tion 118 206 8.4 17 Oil refining 1,684 132 222 8.4 19 Gas 1,706 36 61 8.4 5 Other fuels 1,247 136 170 8.4 14 Total 2,375 1,542 3,663 8.9 325 All data in columns 1 and 2 are from the 1972 I-0 table. Column 3 is calculated as column 2 divided by column 1. Column 4 is calculated as column 3 divided by the average annual wage in the coal sector (3,114 rubles-column 3). The average annual wage rate in 1970 in the coal sector (column 5) is calculated as column 7 divided by column 6. All other data in column 5 are calculated as col- umn 4 times the average annual wages in the coal sector in 1970. All data in column 6, except for other fuels, are from Rapawy, Civilian Employment in the U.S.S.R., p. 4. Employment in other fuels is calculated as a residual. All data in column 7, except for coal, are calculated as column 5 times column 6. The coal entry in column 7 is from Vestnik statistiki, No. 11, 1972, p. 94. The social insurance rates in column 8 for coal, oil extraction, oil refining, and gas are from CIA, GNP 1970, p. 72. It is assumed that the rate for other fu- els is 8.4 percent. The data in column 9 are derived as column 7 times column 8. The wage bill in other industry is derived as a residual. The wage bills in all nonindustry sectors are derived as column 1 times column 2 times 12, except for other branches of material production, which is derived as a residual. Coal 1,001.2 3,118.0 3,114 100.0 Oil extraction 94.3 191.4 2,030 65.2 Oil refining 117.2 229.3 1,956 62.8 Gas 21.3 42.2 1,981 63.6 Other fuels 94.1 136.2 1,447 46.5 Peat 74.4 108.1 1,453 46.7 Oil shales 19.7 28.1 1,426 45.8 Total 1,328.1 3,717.1 2,799 89.9 148 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-10 Billion Rubles Distribution of Other and Imputed Income by Sector of Origin, 1970 (4) (5) Administra- Educa- tive Expenses tion of Higher Echelons (6) (7) (8) Research Other Unidentified Identified Money Incomes Income (9) Total 62.251 (1) State Wage Bill (2) Social- Cultural and Sports Activities (3) Milita- rized Guards Total 135.412 0.162 0.880 1.065 0.400 2.578 49.702 7.464 Industry 49.535 0.075 0.440 0.488 0.183 1.289 0 2.800 5.275 Ferrous metals 2.539 0.004 0.023 0.025 0.009 0.066 0 0.144 0.088 0.271 0.165 Nonferrous metals 1.548 0.002 0.014 0.015 0.006 0.040 0 Fuels 3.717 0.006 0.033 0.037 0.014 0.097 0 0.210 0.397 Electric power 1.065 0.002 0.009 0.011 0.004 0.028 0 0.060 1.099 0.114 2.070 Machinery 19.461 0.029 0.174 0.191 0.071 0.506 0 Chemicals 2.613 0.004 0.023 0.026 0.010 0.068 0 0.148 0.263 0.279 0.495 0.401 Wood, pulp, and paper 4.648 0.007 0.041 0.046 0.017 0.121 0 0 Construction materials 3.768 0.006 0.033 0.037 0.014 0.098 0.213 Light industry 5.174 0.008 0.046 0.051 0.019 0.135 0 0.292 0.551 0.446 0.086 2.669 42.991 1.096 0.164 0.932 5.866 2.011 0.043 0.998 0.568 1.001 0.533 0.312 0.037 0.363 0.041 0.026 0.154 0.047 0.025 0.070 3.200 0.058 Food industry 4.185 0.006 0.037 0.041 0.016 0.109 0 0.237 0.046 Other industry 0.817 0.001 0.007 0.008 0.003 0.021 0 Construction 16.889 0.025 0.150 0.167 0.063 0.440 0.869 0.955 0.680 0.582 0.087 0.495 1.819 Agriculture 12.033 0.018 0.107 0.119 0.045 0.313 41.709 0 0 0 Transportation 10.294 0.015 0.091 0.102 0.038 0.268 Communications 1.545 0.002 0.014 0.015 0.006 0.040 Trade 8.748 0.013 0.078 0.086 0.032 0.228 Services 32.174 0.013 0 0.080 0.030 0 3.924 Housing 1.765 0.003 0 0.017 0.007 0 1.884 0 0.836 0.100 0.034 0.129 Utilities 0.594 0.001 0 0.006 0.002 0 Repair and personal care 2.277 0.003 0 0.022 0.008 0 Recreation 1.176 0.002 0 0.012 0.004 0 0.484 0.470 0.250 0 0 0.066 0.531 0.283 0.284 0.029 0.363 0.041 0.026 0.154 0.047 0.025 0.070 0 0.046 Education 9.400 0 0 0 0 0 0 Health 5.004 0 0 0 0 Science 5.020 0.003 0 0.018 0.007 0 Credit and insurance 0.519 0.001 0 0.005 0.002 0 Government administrative services 6.419 0 0 0 0 0 0 General agricultural programs 0.721 0 0 0 0 0 0 Forestry 0.457 0 0 0 0 0 0 State administration and the administrative organs of social organizations 2.717 0 0 0 0 0 0 0 0 Culture 0.839 0 0 0 0 0 Municipal services 0.450 0 0 0 0 0 Civilian police 1.235 0 0 0 0 0 0 3.200 Military personnel 3.380 0 0 0 0 0 Other branches 0.814 0.001 0 0.008 0.003 0 0 149 93-892 - 82 - 11 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-10 (Continued) Sources to this table: I. State wage bill. See table D-8, column 7. 2. Social-cultural and sports activities. The total is derived in table D-3, item 2,d as 0.15 percent of the wage bill of khozraschet enterprises. The values for each sector are also calculated as 0.15 percent of the wage bill, using the same proxy for khozraschet enterprises as in table D-3, item 2,d. The budget allocation for science in 1970, net of investment, was 6.425 billion rubles (Narkhoz 1977, p. 562). Therefore, the estimated wage bill of khozraschet science enterprises is 5.020 billion rubles less 3.212 billion rubles, or 1.808 billion rubles. 3. Militarized guards. The total is derived in table D-3, item 2,e. It is distributed proportionally to the wage bills of the sectors in the productive sphere (industry, construction, agriculture, transporta- tion, communications, and trade)�the sectors most likely to hire guard services. 4. Administrative expenses of higher echelons. The total is derived in table D-3, item 2,f. It is distributed proportionally to the wage bills of khozraschet enterprises as in item 2 above. 5. Education. The total is derived in CIA, GNP 1970, p. 46. It is distributed proportionally to the wage bills of khozraschet enter- prises as in item 2 above. 6. Research. The total is derived in CIA, GNP 1970, p. 46. It is distributed proportionally to the wage bills of the productive sectors as in item 3 above. 7. Other identified incomes. Construction, 0.869 billion rubles, is the sum of private earnings in construction, table D-1, item 4,a,(1), and the imputed value of owner-supplied construction services, table D-1, item 6. Agriculture, 41.709 billion rubles, is the net income of households from agriculture, table D-1, item 2. Housing, 1.884 billion rubles, is the sum of private earnings in housing repair, table D-1, item 4,a,(2),(a), and imputed net rent, table D-1, item 5. Repair and personal care, 0.836 billion rubles, is derived in table D- 1, item 4,a,(2),(b). Recreation, 0.484 billion rubles, is derived in table D-1, item 4,a,(2),(c). Health, 0.470 billion rubles, is derived in table D-1, item 4,a,(2),(d). Education, 0.250 billion rubles, is derived in table D-1, item 4,a,(2),(e). Military personnel, 3.200 billion rubles, is a CIA estimate of subsistence (food and clothing) expenditures. 8. Unidentified money income. The total, 7.464 billion rubles, is derived in table D-1, item 4,b. It is distributed proportionally to the wage bill in column 1. 9. Total. This is derived as the sum of columns 2 through 8. 150 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-11 Distribution of Social Insurance Deductions by Sector of Origin, 1970 (5) (6) (7) Adjusted Social Insurance (1) Unadjusted Social Insurance (2) (3) Adjustments for (4) Repair and Personal Care Housing- Communal Economy Recreation Civilian Police Trans- portation Total 9.436 0 0 0 0 0 9.436 Industry 3.653 -0.120 0 0 0 0.038 3.571 Ferrous metals 0.198 0 0 0 0 0.002 0.200 Nonferrous metals 0.121 o o o o 0.001 0.122 Fuels 0.325 o o o 0 0.003 0.328 Electric power 0.069 0 0 0 0 0.001 0.070 Machinery 1.492 -0.015 0 0 0 0.014 1.491 Chemicals 0.216 0 0 0 0 0.002 0.218 Wood, pulp, and paper 0.217 -0.002 0 0 0 0.004 0.219 Construction materials 0.227 0 0 0 0 0.003 0.230 Light industry 0.423 -0.076 0 0 0 0.004 0.351 Food industry 0.280 0 0 0 0 0.003 0.283 Other industry 0.085 -0.027 0 0 0 0.001 0.059 Construction 0.993 0 0 0 0 0.032 1.025 Agriculture 1.625 0 0 0 0 0.071 1.696 Transportation 0.694 0 0 0 0 -0.149 0.545 Communications 0.082 0 0 0 0 0 0.082 Trade 0.387 0 0 0 0 0.008 0.395 Services 1.566 0.120 0 0 0.086 0 1.772 Housing 0.163 0 -0.080 0 0 0 0.083 Utilities 0 0.028 0 0 0 0.028 Repair and personal care 0 0.120 0.026 0 0 0 0.146 Recreation 0.026 0 0.005 0.033 0 0 0.064 Education 0.517 0 0 0 0 0 0.517 Health 0.308 o o -0.033 0 0 0.275 Science 0.276 0 0 0 0 0 0.276 Credit and insurance 0.029 0 0 0 0 0 0.029 Government administrative services 0.247 0 0.021 0 0.086 0 0.354 General agricultural programs 0.032 0 0 0 0 0 0.032 151 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-11 (Continued) Distribution of Social Insurance Deductions by Sector of Origin, 1970 (1) Unadjusted Social Insurance (2) (3) Adjustments for (4) (5) (6) (7) Adjusted Social Insurance Repair and Personal Care Housing- Communal Economy Recreation Civilian Police Trans- portation Forestry 0.020 0 0 0 0 0 0.020 State administration and the administrative organs of social organizations 0.149 0 0 0 0 0 0.149 Culture 0.046 0 0 0 0 0 0.046 Municipal services 0 0 0.021 0 0 0 0.021 Civilian police 0 0 0 0 0.086 0 0.086 Military personnel 0.240 0 0 0 0 0 0.240 Other branches 0.196 0 0 0 �0.086 0 0.110 Sources to this table: I. Unadjusted social insurance. This is derived from table D-12 except for the values for the total and for agriculture. The agriculture entry is derived as the agriculture value in table D-12 plus: (1) collective farm payments into the All-Union Social Insur- ance Fund for Collective Farmers (0.356 billion rubles�CIA, GNP 1970, p. 46); (2) collective farm payments into the All-Union Social Security Fund for Collective Farmers (0.780 billion rubles�Ibid); and (3) social insurance charges paid on wages of hired agricultural workers (0.018 billion rubles�Ibid, p. 66). The value for the total entry is the sum of the entries in column 1. The line item data from table D-12 are assigned to the same GNP categories as were the wage data in table D-8. 2-6. Adjustments to social insurance deductions. The adjustments made to the social insurance deductions are analogous to the adjustments made to the wage bill in table D-8. 7. Adjusted social insurance. This was derived as the sum of columns 1 through 6. 152 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-12 Social Insurance Deductions, 1970 Total Industry Ferrous metals Nonferrous metals Fuels Electric power Machinery Chemicals Wood, pulp, and paper Construction materials Light industry Food industry Other industry Construction Agriculture Transportation Communications Trade Other branches of material production Housing-communal economy Art Education Health Science Credit and insurance General agricultural programs Forestry State administration and the administrative organs of social organizations Culture Military personnel (I) " State Wage Bill (billion rubles) (2) Social Insurance Rate (percent) (3) Social Insurance Deductions (billion rubles) 135.412 6.1 8.282 50.549 7.2 3.653 2.502 7.9 0.198 1.526 7.9 0.121 3.663 8.9 0.325 1.050 6.6 0.069 19.378 7.7 1.492 2.575 8.4 0.216 4.623 4.7 0.217 3.714 6.1 0.227 6.219 6.8 0.423 4.125 6.8 0.280 1.174 7.2 0.085 16.283 6.1 0.993 10.695 4.4 0.471 �13.099 5.3 0.694 1.545 5.3 0.082 8.601 4.5 0.387 2.049 9.6 0.196 3.461 4.7 0.163 0.469 5.5 0.026 9.400 5.5 0.517 5.608 5.5 0.308 5.020 5.5 0.276 0.519 5.5 0.029 0.721 4.4 0.032 0.457 4.4 0.020 2.717 5.5 0.149 0.046 0.839 5.5 3.380 7.0 0.240 Sources to this table: 1. State wage bill. This was derived from table D-9, column 3, except the total wage bill and military personnel, which are from table D-8, column 1. 2. Social insurance rate. The social insurance rates are from CIA, GNP 1970, p. 72, except for the total, total industry, fuels, other industry, other branches of material production, and military personnel. The rates for the total, fuels, and other branches of material production are derived as column 3, divided by column 1. 153 The rates for other industry and total industry are derived as an average of the other branches of industry as described in CIA, GNP 1970, p. 73. The rate for military personnel is a CIA estimate. 3. Social insurance deductions. Total social insurance deductions are derived in CIA, GNP 1970, p. 46. Deductions in the fuels sector are derived above in the sources for table D-9. All other sectors, except for other branches of material production, are determined as the product of column 1 and column 2. The value for other branches of material production is determined as a residual. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-13 Billion Rubles Except as Noted Depreciation by Sector of Origin, 1970 (1) Employment in Khozraschet Enterprises (million persons) (2) Depreciation (3) Housing Depreciation (4) Depreciation Net of Housing Depreciation Total 69.856 31.827 1.318 31.827 Industry 30.718 15.472 0.579 14.893 Ferrous metals 1.381 1.456 0.026 1.430 Nonferrous metals 0.676 0.811 0.013 0.798 Fuels 1.574 2.351 0.030 2.321 Electric power 0.642 1.614 0.012 1.602 Machinery 12.060 3.475 0.228 3.247 Chemicals 1.591 1.180 0.030 1.150 Wood, pulp, and paper 2.862 1.131 0.054 1.077 Construction materials 2.290 1.006 0.043 0.963 Light industry 4.160 0.518 0.078 0.440 Food industry 2.937 1.346 0.055 1.291 Other industry 0.545 0.584 0.010 0.574 Construction 9.412 2.325 0.178 2.147 Agriculture 9.628 5.713 0.182 5.531 Transportation 6.319 5.200 0.119 5.081 Communications 1.330 0.408 0.025 0.383 Trade 7.624 1.467 0.144 1.323 Services 4.825 1.196 0.091 2.423 Housing 0 0 0 1.318 Utilities 0.524 0.318 0.010 0.308 Repair and personal care 1.783 0.227 0.034 0.193 Recreation 1.050 0.304 0.020 0.284 Education o o o o Health Science 1.080 0.185 0.020 0.165 Credit and insurance 0.388 0.162 0.007 0.155 Government administrative services 0 0 0 0 General agricultural programs Forestry State administration and the administrative organs of social organizations 0 0 0 0 Culture Municipal services Civilian police 0 0 0 0 Military personnel o o o o Other branches 0 0.046 o 0.045 154 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Sources to this table: 1. Employment in khozraschet enterprises. The same proxy for khozraschet enterprises is used here as in table D-3, item 2,d. The total employment data from table D-9 are adjusted in the same manner as the wage data in table D-8, and then employment in the budgetary sectors is deleted. Employment in khozraschet science enterprises is estimated in the same manner as wages in the sources for table D-10, column 2. 2. Depreciation. Total depreciation is from CIA, GNP 1970, p. 49. Depreciation for total industry and each branch of industry is taken from table D-14 with adjustments made for depreciation in produc- tive repair and personal care services, and for urban electric power distribution. Depreciation in the repair and personal care services included in Soviet industrial statistics is calculated by assuming that the capital-labor ratio in these services is one-half of the nonservice component of the same branch of industry and that the depreciation rate is the same. Depreciation in urban electric power is based on a distribution of the capital stock of the communal economy (see services below). Depreciation in construction is the sum of reported deductions in construction (2.313 billion rubles�Narkhoz 1978, p. 532) plus a share of the amortization deductions of consumer cooperatives. Altough consumer cooperatives are primarily engaged in retail trade activity, they do conduct activities belonging to other sectors. According to P. I. Vakhrin (Formirovaniye osnovykh fondov kooperativnoy torgovli, Moscow, Ekonomika, 1974, p. 88), the capital stock of consumer cooperatives on 1 January 1971 was distributed as shown in column 1 of the tabulation below: Sector (1) (2) Capital Depreci- Stock on ation 1 January Rate 1971 (percent) (billion rubles) (3) Calculated Depreci- ation (million rubles) (4) Percent of Column 3 (5) Depreci- ation (million rubles) Trade 5,208 5.8 302 72.4 266 Industry 1,239 7.6 94 22.5 83 Agriculture 118 6.1 7 1.7 6 Construc- tion 94 15.1 14 3.4 12 Total 6,659 6.3 417 100.0 367 The depreciation rates in column 2 are from the 1972 I-0 table. Column 3 is column 1 times column 2 and column 4 shows the percentage distribution of column 3. Column 5 is column 4 times the total, 367 million rubles (Narkhoz 1978, p. 532). 155 Depreciation in agriculture is the sum of reported deductions in agriculture (2.985 billion rubles�Narkhoz 1978, p. 532), a share of the deductions by consumer cooperatives (0.006 billion rubles�see construction above), and deductions made by kolkhozy (2.722 billion rubles�CIA, GNP 1970, p. 49). Depreciation in communications is from Ibid. p. 68. Depreciation in transportation is the total reported for transportation and communications (5.410 billion rubles� Narkhoz 1978, p. 532), less depreciation in communications (above), plus the depreciation on urban transportation recorded with the communal economy (0.198 billion rubles�see services below). Depreciation in trade is the sum of reported deductions in retail trade (0.443 billion rubles�Narkhoz 1978, p. 532), supply and sales (0.530 billion rubles�Ibid), agricultural procurement (0.228 billion rubles�Ibid), and consumer cooperatives (0.266 billion rubles�see construction above). Depreciation in services is the sum of its components. Depreciation in utilities is based on a distribution of the capital stock of the communal economy: Sector (I) Capital Stock on 1 January 1971 (million rubles) (2) Percent of Column 1 (3) Depreciation (million rubles) Total 7,784 100.0 626 Utilities 3,951 50.8 318 Water and sewer 3,010 38.7 242 Gas 941 12.1 76 Transportation 2,458 31.6 198 Subways 1,449 18.6 117 Trams and buses 1,009 13.0 81 Electric power 700 9.0 56 Baths and laundries 204 2.6 16 Hotels 471 6.1 38 Depreciation in repair and personal care is the sum of depreciation in baths and laundries (0.016 billion rubles�above) and the depreciation deducted from industry for repair and personal care services as described above. Depreciation in recreation is the sum of depreciation in hotels (0.038 billion rubles�above) and a part of the depreciation recorded under "other branches" in the Narkhoz data. Other branches is assumed to include parts of the recreation (art, and resorts), science, credit and insurance, and other branches of Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-13 (Continued) Sources to this table (Continued): material production sectors (0.659 billion rubles�Narkhoz p. 532). The other branches depreciation was allocated among these sectors based on some very rough capital stock estimates as follows: Billion Rubles Total 0.659 Recreation 0.266 Science 0.185 Credit and insurance 0.162 Other branches of material production 0.046 3. Housing depreciation. Total housing depreciation is from Yu. V. Peshekhonov, ed., Razvitiye ifmnansirovaniye obshchestvennikh fondov potrebleniya, Moscow, Finansy, 1978, p. 220. Housing depreciation is not separately identified in the Narkhoz data. Instead, it is thought to be combined with the depreciation of the sec- tors that operate the housing. It is assumed here that housing depreciation is distributed proportionally to employment in khozras- chet enterprises (column 1). 4. Depreciation net of housing depreciation. This is column 2 less column 3 except for the total, services, and housing lines. Housing depreciation is the total line item in column 3. The total and service lines are the sum of their parts. 156 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-14 Distribution of Amortization Deductions by Branch of Industry, 1970 (6) Structure of Depreciation (percent) (7) Adjusted Depreciation (billion rubles) Fixed Capital (4) Depreciation Rate (percent) (5) Depreciation (billion rubles) (1) End 1969 (billion rubles) (2) End 1970 (billion rubles) (3) Average [970 (billion rubles) Industry 207.9 227.6 214.795 7.4 15.895 100.000 15.627 Ferrous metals 19.9 21.8 20.565 7.2 1.481 9.317 5.190 1.456 0.811 2.351 1.558 3.493 1.180 1.136 1.006 0.574 Nonferrous metals 10.0 10.9 10.315 8.0 0.825 Fuels 27.0 29.3 27.805 8.6 2.391 15.042 9.972 22.359 7.550 Electric power 28.9 31.8 29.915 5.3 1.585 Machinery 44.2 49.8 46.160 7.7 3.554 Chemicals 16.3 18.7 17.140 7.0 1.200 Wood, pulp, and paper 11.2 12.2 11.550 10.0 1.155 7.266 Construction materials 12.3 13.7 12.790 8.0 1.023 6.436 Light industry 8.4 9.3 8.715 6.7 0.584 3.674 Food industry 17.9 18.9 18.250 7.5 1.369 8.613 1.346 0.716 Other industry 11.8 11.2 11.590 6.3 0.728 4.580 Sources for this table: I. Fixed capital-end 1969. This item represents the fixed capital of industry in 1955 prices on 1 January 1970. All values, except for nonferrous metals and other industry, are from Constance B. Krueger, USSR: Gross Fixed Capital, unpublished, May 1976, table 3. The capital stock of nonferrous metals is assumed to be one-half that of ferrous metals. The capital stock of other industry is derived as a residual. 2. Fixed capital-end 1970. This item is derived in the same manner as column 1. 3. Fixed capital-average 1970. Each entry is computed as column 1 plus 35 percent of the difference between column 2 and column 1. This is the formula used by Gosplan to compute the average value of fixed capital and reflects the fact that more than half of new fixed capital is commissioned in the second half of the year (Ukazaniya, p. 27). 157 4. Depreciation rate.This is derived from Narkhoz 1970, p. 171, except for nonferrous metals and other industry. Nonferrous metals is determined from the ferrous metals rate of 7.2 percent, and the ratio of the nonferrous metals and ferrous metals depreciation rates in the 1966 1-0 table. The other industry rate is determined as column 5 divided by column 3. 5. Depreciation. This is column 3 times column 4 except for other industry, which is derived as a residual. 6. Structure of depreciation. This is column 5 in percentage terms. 7. Adjusted depreciation. Depreciation for total industry is derived as the sum of reported amortization deduction in industry (15.544 billion rubles-Narkhoz 1978, p. 532) and amortization deductions of consumer cooperatives on industrial capital (0.083 billion ru- bles--see the sources to column 2 of table D- 13). Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-15 Distribution of Profits by Sector of Origin, 1970 (1) Reported Profits (billion rubles) (2) Bonuses (billion rubles) (3) "Net" Profits (billion rubles) (4) Adjustment Factor for Industrial Profits (5) Adjusted "Net" Profits (billion rubles) (6) Other Net Income (billion rubles) (7) Total Profits (billion rubles) Total 84.621 5.030 79.591 79.591 9.563 89.154 Industry 55.695 3.310 52.385 1.000 52.385 o 52.385 Ferrous metals 3.999 0.238 3.761 0.892 3.355 0 3.355 Nonferrous metals 2.699 0.160 2.539 0.914 2.321 0 2.321 Fuels 5.229 0.311 4.918 0.786 3.866 0 3.866 Electric power 3.601 0.214 3.387 0.731 2.476 0 2.476 Machinery 13.850 0.823 13.027 1.089 14.186 0 14.186 Chemicals 3.708 0.220 3.488 1.126 3.927 0 3.927 Wood, pulp, and paper 2.579 0.153 2.426 1.289 3.127 0 3.127 Construction materials 1.611 0.096 1.515 1.057 1.601 0 1.601 Light industry 6.685 0.397 6.288 1.000 6.288 0 6.288 Food industry 7.350 0.437 6.913 0.998 6.899 0 6.899 Other industry 4.384 0.261 4.123 1.052 4.339 0 4.339 Construction 4.736 0.282 4.454 4.454 0 4.454 Agriculture 4.935 0.293 4.642 4.642 7.852 12.494 Transportation 10.718 0.637 10.081 10.081 0 10.081 Communications 0.840 0.050 0.790 0.790 0 0.790 Trade 5.737 0.341 5.396 5.396 1.283 6.679 Services 1.860 0.111 1.749 1.749 0.428 2.177 Housing 0 0 0 0 0 0 Utilities 0.770 0.046 0.724 0.724 0 0.724 Repair and personal care 0.400 0.024 0.376 0.376 0 0.376 Recreation 0.040 0.002 0.038 0.038 0.428 0.466 Education 0 0 0 0 0 0 Health 0 0 0 0 0 0 Science 0.100 0.006 0.094 0.094 0 0.094 Credit and insurance 0.550 0.033 0.517 0.517 0 0.517 Government administrative services 0 0 0 0 0 0 General agricultural programs 0 0 0 0 0 0 Forestry 0 0 0 0 0 0 State administration and the administrative organs of social organizations 0 0 Culture Municipal services Civilian police 0 0 0 0 0 0 Military personnel 0 0 0 0 0 0 Other branches 0.100 0.006 0.094 0.094 0 0.094 158 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Sources to this table: 1. Reported prcifits. Total profits are the reported value for all state enterprises (85.668 billion rubles�Narkhoz, p. 541) less net insur- ance premiums (1.047 billion rubles�CIA, VNF 1970, p. 46). The values for each sector are from Narkhoz 1977, pp. 541 and 543 with the following exceptions: � Profits in the nonferrous metals sector are estimated in CIA, GNP 1970, p. 70. � Profits in the electric power sector include the profits of the urban electric power system (0.137 billion rubles). These profits are assumed to be included with the reported profits of the communal economy (0.984 billion rubles�Narkhoz 1977, p. 541) which are allocated based on some data for the RSFSR as follows: Total 0.984 Electric power 0.137 Other utilities 0.770 Repair and personal care 0.002 Recreation 0.040 Urban transportation 0.035 � Profits of the machinery; wood, pulp, and paper; light industry; and other industry sectors are reduced by arbitrary estimates of profits in repair and personal care services. Total repair and personal care profits are arbitrarily estimated at 0.400 billion rubles based on scattered republic data, of which 0.002 are included in the profits of the communal economy (above). The remaining amount is distributed as follows: Total 0.398 Machinery 0.037 Wood, pulp, and paper 0.008 Light industry 0.277 Other industry 0.076 � Profits in the other industry sector are computed as a residual. � Communications profits are from CIA, GNP 1970, p. 67. � Transportation profits are computed as total profits in transporta- tion and communications (11.523 billion rubles�Narkhoz 1977, p. 541), less profits in communications (above), plus profits in urban transportation (above). � Trade profits are the sum of profits in trade, supply and sales, and agricultural procurement. � Utilities profits are estimated as a share of the profits of the communal economy (above). � Profits in the science, credit and insurance, and other branches of material production sectors are assumed to be components of the other branches category in the Narkhoz profit data. The reported profits of this category (1.797 billion rubles�Narkhoz 1977, p. 541) are reduced by net insurance premiums (1.047 billion rubles). 159 The remainder (0.750 billion rubles) is divided arbitrarily as follows: Total 0.750 Science 0.100 Credit and insurance 0.550 Other branches of material production 0.100 2. Bonuses. Total bonuses are from CIA, GNP 1970, p. 45. The to- tal is distributed among the sectors based on the assumption that the ratio of bonuses to reported profits is the same in each sector. 3. Wet"pro/its. This is column 1 less column 2. 4. Adjustment for industrial profits. It is believed that the profit data in the Narkhoz are reported on a ministry basis. The data in this column represent the ratio of profits on a commodity basis to profits on a ministry basis in the branches of industry as estimated in V. D. Belkin (ed.), Model' "dokhod-tovary" i balans narodnogo khozyaystva, Moscow, Nauka, 1978, p. 119. 5. Adjusted "net" profits. This is column 4 times column 3 for the branches of industry, column 3 for all other entries. 6. Other net income. The value for agriculture represents the sum of retained income and income taxes of collective farms (table D-3, items 1,a and 3,a). The values for trade and recreation represent the sum of retained profits and income taxes of consumer cooperatives and other organizations, respectively. 7. Total profits. This is column 5 plus column 6. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table D-16 Billion Rubles Distribution of Turnover and Other Indirect Taxes by Sector of Origin, 1970 (4) Other Miscellaneous Charges (5) Subsidies (6) Total Turnover and Other Indirect Taxes (I) Turnover Taxes (2) Other Identified Indirect Taxes (3) Income From Foreign Trade Total 53.346 1.845 7.581 14.960 -22.553 77.732 Industry 53.346 1.705 6.822 6.988 -18.688 68.861 Ferrous metals 0.059 0 -0.717 0.295 0 -0.363 Nonferrous metals 0 0 -0.383 0.189 0 -0.194 Fuels 4.630 0 -0.763 0.600 0 4.467 0.663 Electric power 0.477 0 -0.052 0.238 0 Machinery 3.200 1.260 -0.512 1.820 -0.432 5.768 Chemicals 0.494 0 1.131 0.391 -0.365 2.016 Wood, pulp, and paper 0.198 0.445 0.305 0.435 0 1.383 Construction materials 0.296 0 0.123 0.306 0 0.725 Light industry 17.795 0 6.736 1.326 -5.306 25.857 Food industry 25.283 0 0.820 1.121 -12.110 27.224 Other industry 0.914 0 0.134 0.267 -0.475 1.315 Construction 0 0 0 1.125 0 1.125 3.836 Agriculture 0 0.030 0.683 3.123 0 Transportation 0 0 0 1.121 0 1.121 Communications 0 0 0 0.107 -0.370 0.107 Trade 0 0 0 0.726 -0.530 0.726 Services 0 0.063 0 1.723 -2.845 1.786 Housing 0 0.063 0 0.131 -2.086 0.194 Utilities 0 0 0 0.070 0 0.070 Repair and personal care 0 0 0 0.165 0 0.165 Recreation 0 0 0 0.074 -0.759 0.074 Education 0 0 0 0.452 0 0.452 Health 0 0 0 0.241 0 0.241 Science 0 0 0 0.243 0 0.243 Credit and insurance 0 0 0 0.052 0 0.052 Government administrative services 0 0 0 0.295 0 0.295 General agricultural programs 0 0 0 0.033 0 0.033 Forestry 0 0 0 0.021 0 0.021 State administration and the admin- istrative organs of social organizations 0 0.124 0 0.124 Culture 0 0 0 0.039 0 0.039 0.021 0.057 Municipal services 0 0 0 0.021 0 Civilian police 0 0 0 0.057 0 Military personnel 0 0 0 0 0 0 0.170 Other branches 0 0.047 0.076 0.047 -0.120 160 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Sources to this table: I. Turnover taxes. Total turnover taxes are from table D-3, item 3,e. Of this amount, 3.966 billion rubles is the difference between gross and net turnover taxes as reported in Gosbyudzhet 1972, p. 14. This difference represents subsidies of various kinds paid from tax receipts, mainly children's clothing. The entire amount is allocated to the light industry sector. The distribution of the net turnover taxes (49.380 billion rubles) is estimated primarily from two sources. Taxes collected in the machinery, light industry, food industry, and the petroleum part of the fuels sector are from P. E. Kuchkin and N. N. Morozov, Chistiy dokhod sotsialisticheskogo obshchestva, Moscow, Finansy, 1974, pp. 155-156. Taxes collected in the ferrous metals; electric power; wood, pulp, and paper; construction materials; and the gas component of the fuels sector are taken or calculated from data in A. Tret'yakova, Nalog s oborota v 1972, unpublished, 1978. Taxes collected in the chemi- cals sector are assumed to be 1 percent of the total, and taxes collected in the other industry sector are calculated as a residual. 2. Other identified indirect taxes. The total, industry, and services line items are the sum of their parts. The machinery line item is the sum of price markups on radio and television sets and surcharges on agricultural machinery (table D-3, item 3,0. The wood, pulp, and paper and other branches line items are stumpage fees paid by these sectors for harvested wood. The fees are recorded as forestry income in the state budget (table D-3, item 3,f). Total forestry income (0.492 billion rubles) is divided between the wood, pulp, and paper and the other branches sectors on the basis of data from the 1972 Soviet 1-0 table which shows these fees as sales of the forestry sector. The agriculture line item is indirect taxes paid by kolkhozy and sovkhozy (CIA, GNP 1970, p. 68). The housing line item is rental payments paid by the trade sector for space in housing units used for retail trade outlets. 3. Income from foreign trade. Income from foreign trade is based on detailed estimates of foreign trade in 1970 valued in foreign trade rubles and the ratio of foreign trade prices to domestic prices by input-output category. First the 1970 foreign trade data in foreign trade prices were allocated to input-output sectors based on the procedures set out in Treml and Kostinsky, The Domestic Value of Foreign Trade: Exports and Imports in the 1972 Input- Output Table. Then the price ratios calculated in that report for each 1-0 sector were used to convert the values in foreign trade prices to domestic prices. The two sets of data were then aggregated from I-0 sectors to GNP sectors. Each entry in this column represents net imports in domestic prices less net imports in foreign trade prices. The total exports and imports in domestic prices calculated in this manner were slightly different from the values published by Treml and Kostinsky. The domestic price data were scaled proportionally to equal their control totals. 4. Other miscellaneous charges. Total other miscellaneous charges are from table D-3, item 3,f. The total is distributed among all sectors on the basis of their shares in total value added less this item. 161 5. Subsidies. Total subsidies and most of the line items are from table D-3, item 4. The subsidy on agricultural machinery is allocated to the machinery sector; the fertilizer subsidy to the chemicals sector; and the processed feeds subsidy to the other industry sector. The subsidy for price differences on the procure- ment of agricultural products by industry is divided between the light industry, food industry, and trade sectors based on the detailed estimates in CIA, GNP 1970, p. 49. The subsidies on wool (0.14 billion rubles), cotton (1.15 billion rubles), and half of the subsidy on sunflower and other oil seeds, hemp, flax, kenaf, and hides (0.05 billion rubles) were allocated to the light industry. The subsidy on fresh vegetables was allocated to the trade sector. The remainder (12.110 billion rubles) was allocated to the food industry. Payments from gross turnover taxes were allocated to light indus- try. The subsidy on art and radiobroadcasting was divided between the communications (0.370 billion rubles) and recreation (0.258 billion rubles) sectors. The subsidy for price reductions in retail trade was allocated to the trade sector. The subsidies on housing, recreation, and the press were allocated to the housing, recreation, and other branches sectors, respectively. 6. Total turnover and other indirect taxes. This is the sum of columns 1 through 4. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix E Conversion of 1970 GNP From Established Prices to Factor-Cost Prices The 1970 GNP data in established prices are convert- ed to factor-cost prices in four steps: (1) arrangement of the established-price data in a format compatible with Soviet input-output (1-0) definitions, (2) conver- sion of the established-price data to producers' prices, (3) estimation of a 1970 1-0 table in producers' prices consistent with the GNP data, and (4) use of the 1-0 table to convert the GNP data in producers' prices to factor-cost prices. This appendix describes all four steps. I-0 tables are used to associate changes in value added by sector of origin with changes in end use expenditures. The conversion from established prices to factor-cost prices involves (1) the elimination of those elements of prices which do not reflect payments for factors of production (land, labor, and capital) or for goods and services used in the production process and (2) the reestimation of payments for capital services (profits and depreciation) to provide an equal rate of return on capital in all sectors. Because both types of changes involve the value-added component of a sector's prices, they directly affect the prices of the goods produced by that sector, whether the goods are delivered directly to final end uses or are pur- chased by other sectors. Changes in value added, therefore, change the prices of all final goods either directly or indirectly. Taking account of the direct and indirect sources of price changes for the elements of GNP by end use requires information on the structure of each sector's purchases of intermediate goods and services. It is this information which is included in an I-0 table and which leads us to estimate a 1970 I-0 table. (For a description of 1-0 tables in general and Soviet 1-0 tables in particular, see Vladimir G. Treml, Dimitri M. Gallik, Barry L. Kostinsky, and Kurt W. Kruger, The Structure of the Soviet Economy: Analysis and Reconstruction of the 1966 Input-Output Table, New York, Praeger Pub- lishers, 1972.) 163 Arranging the GNP Data in an 1-0 Format The first step in the construction of a 1970 I-0 table is to fill in as much of the table as possible with the available information. In this case, the value-added quadrant of the I-0 table can be filled in using sector- of-origin GNP data. Values in the final demand quadrant rely on end-use GNP data. (For a discussion of the relationship between GNP and an 1-0 table, see Philip M. Ritz, "The Input-Output Structure of the U.S. Economy, 1972," Survey of Current Business, February 1981, pp. 34-37.) In addition, gross output data can be estimated from published Soviet data. Putting the GNP data into a Soviet 1-0 table requires two sets of adjustments. First, the definitions of our GNP sectors often differ from the Soviet definitions of the corresponding I-0 sectors, and the data must be adjusted accordingly. Second, a Soviet 1-0 table includes only the so-called productive sectors. We therefore have to rearrange our GNP data for the nonproductive sectors to conform with the Soviet treatment of such data in their 1-0 tables. This section summarizes these two adjustments. In order to conform with the definitions of Soviet 1-0 sectors we have made the following changes to the sector-of-origin GNP data in table D-6: � The value added of the repair and personal care services included in Soviet industrial statistics was transferred to the machinery; wood, pulp, and pa- per; light industry; and other industry sectors. � The value added of the utilities sector connected with water and sewage services was transferred to the other industry sector, and the value added connected with urban gas distribution was trans- ferred to the transportation sector. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 � The output of the forestry sector is redefined. In our GNP accounts, the entire output of the forestry sector is treated as a final expenditure and the stumpage fees paid by the wood, pulp, and paper and other branches sectors are included in the value added of those sectors. Soviet I-0 tables define the stumpage fees as sales of the forestry sector. Sales to final demand by forestry are the difference between the gross output of the sector and first quadrant sales. � The general agricultural programs sector was aggre- gated with the agriculture sector and redefined. It appears that this activity is reflected in an I-0 table in value added as a subsidy rather than as a final demand expenditure. � The subsidy on fresh vegetables, part of the value added of the trade sector in GNP, is transferred to the agriculture sector. � The productive and nonproductive portions of the transportation and communications sectors were estimated and regrouped to form a productive trans- portation and communications sector and a separate nonproductive sector. � The value added in the ferrous and nonferrous metals branches was aggregated to match the ag- gregate metallurgy sector in the 1972 I-0 table. � Income from foreign trade was deleted. The end-use GNP data show total expenditures for various goods and services but do not show which sector of the economy produced them. Thus, the end- use data must be disaggregated in order to fill in the final-demand quadrant. Each column in the con- structed final-demand quadrant shows the expendi- tures for a given end-use category of GNP. Each row shows the sales of an I-0 sector to each end-use category. In many cases, such as transportation, all of the end-use expenditures represent purchases from the sector of the same title. In other cases, such as soft goods, most expenditures were for the output of one sector (light industry in this case). In a few cases, such as inventory change, essentially arbitrary choices had to be made. In disaggregating the expenditure catego- ries, the allocations followed Soviet I-0 definitions, as did the allocations of value-added data. In addition, several modifications were made to the GNP data, and some estimates were made of missing data: � A subsidy was added for private housing compara- ble to that for public housing. Imputed net rent was increased by the same amount, leaving the value added of the housing sector unchanged. � The value added of the food industry was divided into four subsectors to match the end-use expendi- tures on food. � The intermediate sales of services were estimated. The services involved are credit and insurance, repair and personal care, recreation, and nonproduc- tive transportation and communications. � The structure of expenditures for goods and services by the nonproductive service sectors was estimated. In the second adjustment nonproductive service sec- tors were moved out of the interindustry quadrant. This produces additional rows in the value-added quadrant showing the sales of services to other sectors and additional columns in the final-demand quadrant showing the purchases of goods and services by the service sectors. The gross output of each productive sector in purchas- ers' and producers' prices can be estimated from similar data in the 1966 and 1972 I-0 tables and annually published production and price indexes. The gross output of an I-0 sector can be estimated for any year between 1966 and 1972 in current producers' prices by multiplying the 1966 gross output from the I-0 table times the constant-price production index and the price index published for that sector. This was done for each sector for 1972 and the results were compared with the corresponding data from the 1972 I-0 table. The two 1972 gross-output estimates were quite close in all cases. A correction factor was computed which would equalize the two estimates. Then the average annual rate of growth of the correction factor was used in conjunction with the 1970 production and price indexes to estimate 1970 gross output in producers' prices. 164 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The 1970 gross output of each sector in piirchasers' prices was then estimated using the gross output in producers' prices, turnover tax and subsidy data from the GNP accounts, and transportation and trade data from the 1972 1-0 table. The gross output of each sector in both prices is shown in the following tabulation: Sector Gross Output in Gross Output in Producers' Prices Purchasers' Prices (billion rubles) (billion rubles) Metallurgy 37.076 40.542 Fuels 22.442 34.478 Electric Power 11.511 12.011 Machinery 92.800 101.459 Chemicals 22.414 24.700 Wood, pulp, and paper 19.419 23.196 Construction materials 15.990 21.926 Light industry 62.988 78.843 Food industry 90.489 115.735 Animal products 45.961 38.396 Processed foods 12.527 19.539 Basic foods 16.235 18.749 Beverages 15.766 39.051 Other industry 12.621 13.626 Construction 67.522 67.600 Agriculture 103.800 109.295 Forestry 0.623 0.636 Transportation and communications 25.700 25.700 Trade 22.100 21.700 Other branches 3.800 4.300 The gross outputs of the service sectors were derived from the GNP data. The result of all of the adjustments and estimates described above was a 1970 1-0 table with the value- added and final-demand quadrants, the gross outputs, and a few elements of the interindustry quadrant filled in. The remainder of the interindustry quadrant was blank. Converting the GNP Data to Producers' Prices The 1972 Soviet I-0 table was compiled and pub- lished in established or purchasers' prices. The parts of the 1970 table not filled in as described in the 165 previous section are estimated by assuming that the relationships among the various elements of the table in 1970 are similar to the same relationships in 1972. The Soviets published only part of the 1972 I-0 table. Western experts reconstructed the unpublished en- tries and converted the entire table to producers' prices by eliminating turnover taxes and subsidies and by separating the costs of transportation and trade services from the purchase price and showing them as a separate expense. Producers' prices are a more accurate reflection of the structure of production costs in each sector and provide a better basis for estimat- ing the cost structure for 1970. Since the elimination of turnover taxes and subsidies is also part of the conversion to factor-cost prices, it is expedient to convert the data in the partially completed 1970 1-0 table to producers' prices before completing the table. This price change is described here. The 1-0 data are converted from purchasers' prices to producers' prices in four steps: (1) turnover taxes and other fees are deleted, (2) transportation and commu- nications expenses are reallocated, (3) trade and distri- bution expenses are reallocated, and (4) the value added and gross output in each sector are increased by the value of any subsidies given to the sector. Turnover taxes and other fees form part of the purchasers' price of a good as an element of value added and need to be subtracted froni the value added and gross output of each sector. Total turnover taxes and other fees are 54.606 billion rubles, the sum of turnover taxes (53.346 billion rubles-table D-3, item 3,e), price markups on radio and television sets (0.510 billion rubles-table D-3, item 3,1) and surcharges on spare parts for agricultural machinery (0.750 billion rubles-table D-3, item 3,1). The distribution of turn- over taxes by sector is shown in table D-16. The price markups on radio and television sets and the sur- charges on spare parts for agricultural machinery are part of the value added of the machinery sector. The same value of taxes and fees also had to be removed from each sector's sales to preserve the equality between total output and input. In order to subtract the taxes and fees from the rows of the 1-0 table, it is necessary to estimate the distribution of the taxes of each sector as an element of the sales to each sector or to a category of final demand. For this, it was 93-892 0 - 82 - 12 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 assumed that the same distribution of taxes estimated for the 1972 I-0 table is also valid for 1970. The taxes included in final-demand values are then subtracted directly. The taxes paid by each sector when it purchases material inputs are subtracted from each entry in that sector's column of the I-0 table, summed, and placed in a new row in the value-added quadrant. The new row is necessary to preserve the equality between a sector's output and input. The purchase price of any good includes the transpor- tation expenses necessary to deliver the good from the producer to the purchaser. Since this expense is not a real cost of production and can be highly variable depending on the transportation mode and the type and location of the purchaser, a better estimate of the structure of production costs is obtained by subtract- ing this transportation expense. The cost of transpor- tation still exists, but is now shown as a separate purchase in the transportation row. If a complete purchasers' prices table is available, the reallocation of transportation expenses is simple. First the value of each sector's purchases of transportation and communications services is deleted and the value of its gross output is reduced by the same amount. This value represents the amount paid by the produc- ing sector for the delivery of its output to purchasers. Then the same value is removed from that sector's row by assuming that the proportion of transportation and communications expenses in each sector's sales is equal. For example, if a sector's purchases from the transportation sector in purchasers' prices is equal to 5 percent of its gross output, then it is assumed that 5 percent of that sector's sales to each other sector and to final demand represents transportation expenses. The values removed from all of a sector's material purchases are summed and entered as a single pur- chase of transportation and communications services. This value represents the amount paid by the produc- ing sector for the delivery of its material inputs. In this case, a complete purchasers' prices table is not available. Therefore, it was assumed that the propor- tion of each sector's sales that represented transporta- tion and communications services in 1970 was the same as it was in 1972. The transportation purchases by each sector were then summed and compared with the gross output of the transportation and communi- cations sector. The calculated amount, 27.1 billion rubles, was 5 percent higher than the published gross output, (25.7 billion�Narkhoz 1978, p. 41). All of the 1972 transportation rates were lowered by 5 percent to remove the discrepancy, and the calculations were repeated. The trade and distribution expenses were reallocated using the same procedure as for transportation. This operation is slightly more complicated because there are sharply different markups for wholesale trade, retail trade, and agricultural procurement services. Again the rates used for the 1972 I-0 table were assumed to be valid for 1970, and the gross output of the trade sector was calculated. Again, the resulting total was 5 percent greater than the gross output of the trade sector. The same proportional reduction of the 1972 trade and distribution rates was used to remove the discrepancy. Subsidies were removed in an analogous manner to turnover taxes and other fees. The subsidies row in the value-added quadrant was deleted, and the gross output of each sector was increased by the same amount. The same amount was then allocated among purchasing sectors and final demand, using the distri- bution of the corresponding subsidies in the 1972 I-0 table. Finally, the estimated subsidies received by each sector on its material purchases were summed and entered as a new row in the value-added quadrant. Estimating a 1970 Input-Output Table The computation described in the previous two sec- tions produced a partial 1970 I-0 table in producers' prices. The remaining parts of the table were estimat- ed based on the assumption that all production rela- tionships should be as similar as possible to what they were in 1972 and yet be consistent with the data already filled in. 166 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Mathematically, the unknown parts of the table are estimated by minimizing the sum of squared differ- ences between the corresponding entries of the 1972 and 1970 I-0 tables. If x(i,j) is the value of the sales of sector i to sector j in 1970 and y(i,j) is the same sales in 1972, then the following is minimized: n n S = Z(x(ii)�YON/Y(ii), i=1 j=1 subject to the constraints that: (1) Ex(i,j)=C(j), and i=1 (2) Ix(i,j)=R(i), where j=1 CO) is the column sum of sector j (gross output less value added and other estimated purchases) and R(i) is the row sum of sector i (gross output less final demand and other estimated sales). The minimum value of S is determined by the equations: (3) x(i,j)=y(i,jX1-1-X(i)+�(j)), where X(i) and �(j) are Lagrangian multipliers. Substituting each equation (3) into equations (1) and (2) produces a system of 2n-1 linear equations in 2n-1 unknowns (the Lagrangian multipliers), where n is the number of sectors in the I-0 table (19 in this case). The values of the Lagrangian multipliers can then be substituted back into each equation (3) to determine the actual value of each cell in the 1970 1-0 table. For a detailed description of this and other methods of estimating 1-0 tables see John Pitzer, An Analysis of Technical Change in the Soviet Economy: An Application of Soviet Input-Output Tables (Ph.D. dissertation, American University, 1980). 167 Estimating GNP in Factor-Cost Prices The preceding sections have described the estimation of GNP in producers' prices and a complete 1970 Soviet I-0 table. In order to complete the conversion to factor-cost prices, it is necessary to eliminate the remaining elements of value added which do not represent a payment to a factor of production, esti- mate the capital stock of each sector, and replace Soviet profits with a capital charge which provides an equal rate of return in each sector. All of these changes directly affect value added. The 1-0 table is needed to compute the direct and indirect impact of the value-added changes on end-use GNP. In any 1-0 table, the sum of a sector's material purchases and value added equal its gross output, or: (4) X(j)= /x(i,j)-F w(j)-Fd(j)+Z(j), where i=1 X(j) is the gross output of sector j, w(j) is the labor income earned in sector j, d(j) is the depreciation in sector j, and Z(j) is all other value added in sector j. As in previous estimates of Soviet GNP in factor-cost prices, it is assumed that w(j) and d(j) adequately represent their respective variables. It is desired to compute a uniform rate of return on each sector's capital stock, r, and to reprice the output of all sectors to accommodate this uniform return. Equation (4) now becomes (5) p(j)X(j)= /p(i)x(i,j)+ w(j) d(j) -f- rK(j), i=1 where p(i) is the price change required in sector i, and KO) is the capital stock of sector j. We make two further refinements. First, the capital stock of each sector is disaggregated to show how much was produced by the machinery, construction, Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 and agriculture (livestock) sectors, and each portion of the capital stock is revalued according to the price variable, p(i), of the sector producing the capital. Second, the constraint is added that factor-cost GNP must equal established-price GNP. These refinements produce the system of equations: (6) p(j)X(j) = Zp(i)x(i,j)+ w(j)+d(j)-f-rEp(i)K(i,j), i=1 i=1 (7) w(j)+d(j)+r Ep(i)K(i,j)=GNP (established prices), i=1 where K(i,j) is the amount of capital produced by sector i and owned by sector j. There are n equations of type (6) and one equation (7), for a total of n +1. There are n unknown price variables, p(i), and one unknown interest variable, r, for a total of n +1. Equation (6) is nonlinear, however, and the system must be solved by iteration. The capital data were derived principally from the estimates by Constance B. Krueger of capital stock by major sector in 1955 prices (USSR: Gross Fixed Capital, unpublished, 1976). Capital stock of the various services were estimated primarily from data in Rutgayzer, Resursy razvitiya neproizvodstvennoy Very, and other monographs on the service sector. Imputed depreciation was also added for capital stock for which the Soviets do not compute amortization deductions (primarily the capital used by budget organizations). In order to make our accounts more comparable to those of OECD countries, a compromise between the theoretical standard of an equal rate of return on capital in all sectors and the OECD practice of not imputing any return on government capital was adopted. In the version used here, the capital stock of the housing sector and of the government sectors (state administration and the administrative organs of social organizations, culture, health, education, forest- ry, municipal services, general agricultural programs, and civilian police) was given a rate of return one-half that of the other sectors. With equations (6) and (7) solved, and the entire 1-0 table repriced in factor-cost prices, the only step remaining was to rearrange the data in accord with our definitions of GNP sectors. In effect, the adjust- ments described in the first section of this appendix were made in reverse order. The result is a Western- style 1970 I-0 table with GNP by end use and by sector of origin in factor-cost prices as two of its components. 168 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part II. AN INDEX OF INDUSTRIAL PRODUCTION IN THE USSR By Ray Converse 169 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Contents Page Summary Introduction The Revised Methodology Taxonomy of the Industrial Index The Product Sample Sectors, Branches, and Groups Construction of the Standard Indexes Alternative Approaches Derivation of the Branch Indexes The Machinery Index The Index of Total Industrial Output Soviet Industrial Growth, 1950-80 Revised SPIOER Indexes Major Trends in Industrial Production Industrial Materials Machinery Consumer Nondurables 175 179 179 179 180 183 184 184 187 188 190 190 190 192 197 197 198 Evaluation of the New Indexes 198 Consistency Tests 198 Consistency With the Official Indexes 198 Plausible Elimination of Inflated Growth 200 Consistency of Growth Trends 200 Consistency With Investment Series 203 Sample Representativeness 207 Sample Coverage 207 A Rough Measure of Sample Representativeness 208 Biases in the Basic Data 210 Changes in the Material Intensity of Production 210 Biases in the Quantity and Value Data 212 The Importance of Disguised Inflation 215 Appendixes A. The SPIOER Sample and Sector Indexes 219 B. Computation of the Machinery Index 241 171 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Tables 1. Share of Branch Value Added in 1972 Accounted for by Different 184 Statistical Series SPIOER Industrial Groupings 185 Industry: 1970 Value Added at Factor Cost by Branch 190 4. Soviet Industrial Production Indexes 191 5. Soviet Industrial Production: Annual Rates of Growth 193 6. Soviet Industrial Production: Average Annual Rates of Growth 195 7. Rankings of Industrial Branches by Growth Rates 8. Comparisons of Average Annual Growth in SPIOER and Official Series 199 201 9. Difference Between Official and SPIOER Average Annual Growth 202 Rates for Industry and Branches of Industry Difference Between Official and SPIOER Growth Rates 203 for Industry 11. 1 SPIOER and Official Industrial Indexes: Comparisons of Secular 205 Growth Patterns SPIOER and Official Industrial Indexes: Directional Changes in 206 Growth 13. Estimated Sample Coverage of SPIOER Indexes in 1972 14. SPIOER and I-0 GVO: Comparisons of Average Annual Growth Rates 209 210 15. Gross Output and Value Added in Input-Output Tables at Constant 211 Prices 16. Comparison of Growth of Output in Two Sectors Using Fixed and 213 Variable price Weights 17. Comparison of Growth of Quantity and Value Series Within 216 Branches of Industry 18. Growth of Machinery Samples Estimated From Official GVO Data 217 19. Growth of Soviet Industry Under Different Assumptions of Bias 218 in the SPIOER Producer Durables Sample A-1. The SPIOER Sample: Products, Units, and Key Sources 219 A-2. Gross Sector Output Indexes 230 B-1. Allocation of Value Added in the Machinery Branch to Producer 242 Durables and Consumer Durables 172 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figures 1. Growth of Industrial Production, 1950-80 176 2. A Capsule View of How the Index Is Constructed 180 3. Branch Shares of 1972 Industrial Gross Output and Value Added 187 4. Structure of the Machinery Branch 189 5. Growth of Soviet Industrial Production 196 6. SPIOER and Official Series: Comparison of Annual Growth Rates for Industry 204 Comparison of Production of Producer Durables and Adjusted 207 Investment 173 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 An Index of Industrial Production in the USSR Summary Measures of industrial production are needed to gauge the pace of Soviet economic development and to calculate more general measures of economic activity such as Gross National Product. Because the official index is believed to have an upward bias, synthetic indexes of industrial production (SPIOER) have been constructed by the CIA to avoid the pitfalls of the of- ficial indexes. The indexes provide an empirical picture of Soviet industrial development since 1950 (figure 1). Industry recorded impressive growth in the fifties as the Soviet economy rebuilt from World War II by rapidly boosting output in the machinery and construction materials branches. Beginning in 1960 the growth rate of industrial production declined precipitously, stabilizing at a slower rate before a new period of declining growth rates began in the mid-1970s. Average Growth of Industrial Production Average Annual Percent SPIOER Official 1951-59 1960-75 1976-80 9.4 6.3 3.4 12.0 8.2 4.4 SPIOER indexes are based on a sample of three types of Soviet reporting: physical output series, constant value series, and official indexes of gross output.' Physical output series, when available, are preferred because they avoid the distortions of disguised inflation. The products included in the index sample are classified by input-output sector and aggregated using 1 July 1967 price weights. ' Gross output is the value of production of an economic unit, such as an enterprise, ministry, branch, or all industry. In general, gross output represents shipments from the enterprise adjusted by inventory changes. 175 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 1 Growth of Industrial Production,1950-80 Percent 12 10 8 6 �� � �� � ��� � �� � � �� �� ��� � � � ��� ��� � ��� � �� � � ���� � � � � � ��� � � ��� � � � ���� � � �� ��� � � ���� � � � � � ����� � � � � ��� � � ��� � ���� � ���� � � � ����� � � � � � � � � � � � � � � 4 � � � � � � � � � � . � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � . � � � � � � � � � � � � � � � � � � � � � � � � � � ������� � � � � � � � � � � � � � � ����� ��� � � ��� � � C... ' � � � � I ?..1- � L � 01. -11-1- 61- .1.-.�-r�-�.-1.-.4.�:1:4:�:�.-.1:��-1:�-r.�1�.1:��.r�.�J.:�Z�:' � � 4.. �F � � l� � �1.�1 0 1950 55 60 65 70 75 80 2 ���� ���� .... � � �������������������������� �������������� � � � � � ���������������������������� �������������������������� � � � � � � � � � � � � Postwar boom Stable, slowly declining 11:.1 Slowdown To combine sector indexes into indexes for the branches of industry, we use a 1972 input-output table for the USSR to derive value-added weights within the branch.2 The branch indexes are further aggregated into indexes for industrial materials, machinery, consumer nondurables, and total industry. The amounts of value added in each branch in 1970 (at factor cost) serve as the weights.' Machinery production is treated differently because of the need for indexes for machinery components. Samples are created for nearly every machin- ery sector in the input-output table, and estimates of the total value added for each sector are allocated between producer and consumer durables An input-output table is a data matrix that records for a given year the technological rela- tionships between the various sectors of an economy. Along the columns, it gives the structure of inputs of materials, labor, and capital necessary to produce a given volume of output. Along the rows, it shows how the output of a given sector is distributed among the various industries and final consumption. Value added is gross output less intermediate inputs consumed. More specifically, value added includes profits, wages, depreciation, and other payments to the factors of production plus indirect business taxes and subsidies (as a negative income). 176 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 production. The two sets of value-added weights for each machinery sector are applied to the various sector output indexes to compute separate output series for the two types of durables. These series are then combined with estimated military durable production to arrive at an index for total machinery output. Several tests have been performed on the synthetic indexes for reasonable- ness in terms of consistency with collateral information, the representative- ness of the sample, and biases in the basic data. Although, as expected, the synthetic indicator of industrial progress shows slower growth than the Soviet official index, the configurations of trends are similar in both indexes. The consistency is best for the most recent period, where gross dis- tortions in official data seem less than in the past. Trends in the most im- portant segment of industrial output�producer durables�can be com- pared to the key end-use component of investment in machinery and equipment. When this comparison is made, the two series match closely. The data are inadequate to test directly for the representativeness of the sample�a crucial factor in establishing the legitimacy of any index. The high share of the total production covered by the sample in 1972�the year of the most recent input-output table, which provides information on the total volume of production�suggests that it is representative. The samples for six of the 10 branches of industry represent more than 60 percent of to- tal branch output in 1972. Coverage is poorest in nonferrous metals and chemicals and petrochemicals. In another test of the SPIOER's accuracy, the industrial growth implied by the 1959, 1966, and 1972 input-output tables was compared with the growth registered by SPIOER indexes over the same periods. The SPIOER samples generally grow more slowly. This could suggest some downward bias in the synthetic indexes, but the discrepancy could also result from us- ing the spurious official price indexes to deflate the input-output tables to constant prices to arrive at "comparable" growth rates with the synthetic indexes. SPIOER's reliance on gross output rather than value-added indexes could be an important source of bias but does not seem to be. We in effect are as- suming at the sector level that the ratio of value added to gross output has remained constant. Analysis of the gross output and value-added compo- nents of the input-output tables for 1959, 1966, and 1972 suggests that the error resulting from this assumption is not serious. The performance of SPIOER is least satisfactory in controlling the biases in the basic data. Series that measure output in quantity terms almost certainly understate the true growth rate because they fail to account for 177 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 improvements in quality and changes in product mix. While this conceptu- al problem applies to nearly all the quantity series, it undoubtedly is most serious in the machinery branch. Similarly, disguised inflation that enters the value series, usually under the guise of new-product pricing, leads to an overstatement of growth. This occurs when enterprise managers make minor modifications to an existing product to justify a price higher than would be warranted by the marginal improvement. This problem is most acute in the machinery branch, especially in producer durables where the value series have a large weight and grow much faster than the physical output series. On one hand, evidence suggests that the quantity series may bias the growth rate for selected machinery products downward by as much as 1 percentage point per year; the bias in quantity series for other branches probably is smaller. On the other hand, indications exist that disguised inflation in the value series in our machinery sample may display growth trends that are biased upward by as much as 3 percentage points per year. (The value series are not a significant problem in other branches because of their infrequent use and small weight.) As for the net effect of these biases, if all the difference in growth rates be- tween the value and physical series in the producer durables sector, where the problems of bias are the worst, were actually attributable to inflation, the SPIOER index would overstate machinery growth by a maximum of 1.2 percentage points per year and overall industrial growth by 0.3 percentage point. But the machinery inflation bias is probably much less because the quantity series, by understating growth, partially offset the upward biases of the value series. 178 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 An Index of Industrial Production in the USSR Introduction Any attempt to assess Soviet economic development and to measure aggregate economic activity requires a reliable measure of industrial production. The official measures prepared by Soviet statistical agencies are unreliable by Western standards, so independent esti- mates are necessary.4 The CIA's Office of Economic Research Indexes of Soviet Industrial Production (SPIOER) circumvent weaknesses inherent in official statistics. These indexes, first published in 1963, have been revised over the years to improve the methodolo- gy and adjust to data availability.' The current revisions, like their predecessors, adopt as a model the Federal Reserve Board's industrial pro- duction index for the United States. The revised methodology enhances SPIOER's compatibility with the structure of Soviet input-output tables and makes the SPIOER branch indexes more comparable in scope with official time series. Frequent changes in reporting procedures�a persistent problem with Sovi- et data�make earlier versions of the indexes less representative with time and force an inappropriate reliance on obsolete data. Therefore, this revision of SPIOER tries to conform to current Soviet reporting practices. ' The problems of the official Soviet measures are discussed in CIA, Comparing Planned and Actual Growth of Industrial Output in Centrally Planned Economies, ER 80-10461 (August 1980). Descriptions of the changing methodology behind these indexes have been published over the years. For example, the writings of the late Rush V. Greenslade are especially prolific on this topic. In particular, see "Industrial Production Statistics in the USSR," in Vladimir G. Treml and John P. Hardt, eds., Soviet Economic Statistics, (Durham: Duke University Press, 1972), pp. 155-194; with Wade Robertson, "Industrial Production in the USSR," Soviet Economic Prospects for the Seventies, US Congress, Joint Economic Committee (Washington, D.C.: Government Printing Office, June 27, 1973), pp. 270-282; and "The Real Gross National Product of the USSR, 1950-75," Soviet Economy in a New Perspective, US Congress, Joint Economic Committee (Washing- ton, D.C.: Government Printing Office, October 14, 1976), pp. 269- 300. See also F. Douglas Whitehouse and Ray Converse, "Soviet Industry: Recent Performance and Future Prospects," Soviet Econ- omy in a Time of Change, vol. 1, US Congress, Joint Economic Committee (Washington, D.C.: Government Printing Office, Octo- ber 10, 1979), pp. 402-422. This paper first describes the updated SPIOER proce- dures. The revised methodology is described in terms of the taxonomy of the individual indexes, the stand- ard approach, the special case of machinery, and the computation of the total industry index. The next section presents the indexes and discusses the pattern of industrial growth from 1950 to 1980. In the last section both the indexes and the samples are subjected to several tests to determine their reasonableness. The Revised Methodology Taxonomy of the Industrial Index The revised industrial production index uses a five- tier stratification of industry: � Individual products, for example, iron ore. � Input-output sectors, for example, ferrous ores. � Branches of industry, for example, ferrous metals. � Major industry groups, for example, industrial materials. � Total industry. The process of going from product samples to an index of total industrial production is summarized in figure 2. Product data are aggregated into sector indexes using 1 July 1967 prices as weights. That is, output of a given product in physical units is multi- plied by its July 1967 price, and the value is summed together with like values for other products of the sector to obtain a value from which a sector index can be calculated. Branch indexes are calculated from sector indexes using value added derived from the 1972 input-output table in producer prices to elimi- nate the double-counting inherent in adding the value of output of earlier stages of production to values at later stages�for example, adding the value of iron ore to the value of steel. The aggregations from branches to industry groups and finally to total 179 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 2 A Capsule View of How the Index Is Constructed Products Products aggregated with I July 1967 prices Sectors Sectors aggregated with value-added weights derived from 1972 input-output table For example: Iron ore Manganese ore (Each item is a production series from 1950 to the present) IFerrous ores Ferrous metals Coke products Refractory materials 'Branches Branches aggregated with 1970 value-added weights IFerrous metals Nonferrous metals Fuel Electricity Chemicals Wood, pulp, paper Construction materials opIndustry group Groups aggregated with 1970 value-added weights Total industry Ilndustrial materials I Machinery wTotal industry Consumer nondurables industry are accomplished with independently derived 1970 value-added weights based on factor cost rather than established prices.6 The advantages of classifying machinery production by end-use designation require some departures from this basic procedure. Individual machinery products are divided into producer durables and consumer durables. In addition, estimates of output for the 6 Established prices are the actual prices existing in the Soviet Union for transactions. We believe that these prices are seriously distorted because of indirect taxes and subsidies, and because supply and demand forces do not play a role in price formation. Therefore, we adjust the established prices to a factor cost basis so that the prices will better represent the cost of the resources used in production. This adjustment is done by eliminating subsidies, indirect taxes, and profits and imputing a capital charge based on each sector's stock of fixed and working capital. For a full discussion of this procedure, see JEC, GNP, 1950-80. defense sector must be included. This then leads to machinery subsectors and subbranches based on the two classifications of durables produced. At the major industry group level, no distinction is made and all products are combined under a single machinery group. The Product Sample. The major building blocks of this index are the 312 products that form the sample of industrially produced goods. These products are measured in one of three ways: physical quantities, values, or indexes. 180 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The most common description is a statistical produc- tion series expressed in physical terms: tons, square meters, units of production, or some other convention- al measure. Examples of this type of data are tons of coal, square meters of tile, or number of subway cars. The product series are then multiplied by actual or estimated 1967 enterprise wholesale prices to derive constant price series. In some cases the raw product data are adjusted by indexes of quality change in the average or standard product over time. For example, not only has Portland cement production increased over time, but the output mix has steadily shifted in favor of higher "marks" (greater strength) of cement. Raw figures for Portland cement production are therefore weighted by both the 1967 wholesale price and an index of average mark to account for the improved quality of the product over time. Official ruble value series reported by the Central Statistical Administration of the USSR (CSA) are also used as sample elements. A few examples are the value of production of agricultural machinery, metal- cutting machine tools, and forge presses. Until recent- ly these series were reported in official 1967 wholesale prices, although earlier years were reported in 1955 wholesale prices. In 1976 the Soviets began to publish these value series in prices of 1 January 1975. The official statistics have overlap in the different prices for a given year to permit an approximate linkage between the earlier and later periods, so that a common price basis can be maintained. Since the physical output samples are weighted by 1 July 1967 prices, the new value indexes were linked backward to estimate them in 1967 prices to conform with the remainder of the sample. These rubles series, however, must be used with caution because many of them contain a large degree of concealed inflation. The products in this category are usually machinery items subject to the problems of new-product pricing. Some share of the reported growth arises from the use of first temporary prices and then permanent prices that are substantially higher than increased performance would justify.' In addition, since these series include both intermediate and final goods, they contain a substantial amount of double-counting. To the extent that the magnitude of double-counting has fluctuated over time, these series could be biased up or down. The third kind of production measure consists of gross value of output (GVO) indexes prepared by the Soviets for various product groups such as mineral chemicals, repair of machinery, and metal structurals. They are supposed to represent the aggregation of all output in a given branch�sometimes including work in process and major repairs. These indexes are subject to even greater limitations than the CSA value series.' Therefore, they are used only to fill out the sample in some crucial areas where better indica- tors are lacking. Although each line item in the SPIOER sample ostensibly consists of a production entry for every year since 1950, the quality of coverage is not uniform. Some gaps in coverage exist for the earlier years, especially during the 1950s. These gaps fit three categories: missing intervening observations at irregu- lar intervals, series that begin several years after 1950 despite production during earlier years, and items not produced in earlier years. The extent of the resulting problems and procedures to circumvent them vary by type of gap. ' See the section "Biases in the Basic Data" for a fuller treatment of the new-product pricing phenomenon. It has been widely discussed in the literature. In particular, see Abraham S. Becker, Ruble Price Levels and Dollar-Ruble Ratios of Soviet Machinery in the 1960s, Report R-1063-DDRE (Santa Monica, California, The Rand Cor- poration, 1973); Joseph S. Berliner, The Innovation Decision in Soviet Industry (Cambridge, The MIT Press, 1976); Padma Desai, "On Reconstructing Price, Output and Value-Added Indexes in Postwar Soviet Industry and Its Branches," Oxford Bulletin of Economics and Statistics (February 1978): pp. 55-77; Central Intelligence Agency, An Analysis of the Behavior of Soviet Ma- chinery Prices, 1960-73, ER 79-10631 (December 1979); and James E. Steiner, Inflation in Soviet Industry and Machine Building and Metalworking (MBMW), 1960-1975, SRM 78-1042 (Working pa- per, July 1978). ' As an index, the output data are express only as a proportion of another year. The publication of indexes with tfcrent base years and in extremely rounded form limits accuracy. In addition, an index cannot be scaled to compare its relative importance with activity elsewhere in the economy. 181 93-892 0 - 82 - 13 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Missing intervening years are the most common type of gaps in the SPIOER data. A typical series is fairly complete except for a few years when the relevant production data fail to appear in either an edition of the Narodnoye khozyaystvo or in one of the two editions of the statistical compendium Promyshlen- non'. In general several benchmark observations are available for these series�most often for 1950, 1953, 1955, 1958, and 1960�although the precise configu- ration of benchmarks varies from series to series. This problem affects around 50 of the statistical series or about 15 percent of the sample. Almost all of these cases are concentrated in three branches of industry: ferrous metals, processed food, and machinery. In all instances of this kind, years between benchmarks are interpolated by assuming that the average annual rate of growth between benchmarks is constant. Since we have little interest in year-to-year comparisons during the 1950s, this procedure should not introduce a significant distortion. The second type of gap occurs when Soviet statistical authorities fail to extend a newly published series back in time. This is potentially a more serious problem because extrapolation of a data series to complete it involves more uncertainty than interpola- tion. However, this problem is limited to less than 20 series or about 5 percent of the sample. About three- fourths of these occur in the machinery branch. Several different approaches are used to adjust the series depending on the availability of other informa- tion. For example, production data on three different types of boilers are published in different units for earlier years only. A year in common is used to splice the series together, and then extend the desired series backward. The index series for printing machinery and equipment does not extend back to 1950, so quantity production series available in the earlier years for two types of printing equipment are used to extend the full series. For some ruble series and index series in the sample, statistical correlations between GVO branch indexes and product series are used to extend the product series back in time. Metalwares, metal structurals, light industry and processed food industry machinery and equipment, and mineral chemicals are examples where this procedure is used. In a few instances�furniture, logging and paper machinery, machinery repair, and carpeting�the series are merely extrapolated backward assuming a constant average annual rate of growth equal to the rate for the first five years for which data were published. The assimilation of new products into SPIOER poses a different statistical problem whose treatment de- pends on the type of data series used for the new product. In most cases the line items in the sample are so aggregated that a new product merely falls within the rubric of an existing broader classification. Phys- ical product series often cannot be adequately disag- gregated to account for the effect of new products and a changing product mix. This can be a serious handi- cap because the entire output of a given commodity or commodity class�bulldozers in construction machin- ery, for example�has to be given a single average or representative unit price for the entire period. Other examples of quantity series in SPIOER where new products are included in output statistics, but where the average price may not fully reflect them are synthetic plastics and resins, synthetic knits and fi- bers, and scrapers. In those instances where the SPIOER disaggregation accounts specifically for new products�such as trac- tors, automobiles, and trucks�another procedure is used. If the product is considered essentially new, it is added into the sample at its 1967 price or its first permanent price for models introduced after 1967. If the product is considered a modification of an earlier model, production is added to the output of the similar model at the earlier model's price. The problem of accounting for new products does not apply to the value and index series. Because these series presumably cover all products in a given cate- gory, they include new products and reflect changes over time in the product mix. However, value series also include the value of output of intermediate products as well as the disguised inflation mentioned earlier. All of these problems associated with the treatment of new products are discussed in detail later in the paper. 182 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 In addition to gaps in coverage for the earlier years, there are numerous problems with the more recent data, which are both difficult to quantify and poten- tially more serious. During the past decade, Soviet statistical authorities have continuously reduced the amount of information reported from one year to the next. The "Industry" section in the latest Narkhoz, for example, contains only 80 pages in contrast to the 142 pages in the 1970 edition. At least 10 percent of the SPIOER series published directly in the Narkhoz in 1970 no longer appear there. Thus, greater reliance must be placed on estimates based on other sources. The information on which to base these estimates also has become more fragmentary, so that the estimates are more subject to error. Since the Soviets are more likely to delete publication of a series when its growth trend becomes unfavorable, SPIOER estimates may suffer from an upward bias. Fortunately, the series deleted from standard publication so far have not had a major impact on the SPIOER sample, but the trend is potentially troublesome. In terms of the absolute number of sample items, the physical output series dominate�they account for 292 (94 percent) of the 312 statistical series in the index. (See appendix A-1 for a listing of the sample.) The CSA value series account for another 4 percent and the GVO indexes comprise the remaining 2 percent of the sample. Comparisons of the absolute number of statistical series are deceptive, however, because some series have significantly greater impact on the aggregate indexes than other series. The approximate share of each type of statistical series in the industry portion of the 1972 Soviet input-output table weighted by value added is: Type of Series Percent Including Unrepresented Products Excluding Unrepresented Products Quantity CSA rubles CSA gross value of output index 73.3 10.7 8.0 79.7 11.6 8.7 Unrepresented 8.0 a Unrepresented products are those items lacking any SPIOER counterpart. Some examples of this are cable products, tools and dies, and construction materials machinery and equipment. The relative importance of value and index series based on the share of industrial output they represent is three times more than their importance based strictly upon a count of the number of series used. Nonetheless, quantity series still have much the larg- est weight in the calculation of SPIOER indexes. Sectors, Branches, and Groups. The next step-up in the taxonomy of the industrial production index is the input-output sector. This level is based on the 88- sector version of the 1972 input-output table in pro- ducer prices, of which only the first 81 sectors consti- tute Soviet industry.' The remaining sectors consist of nonindustrial activity such as agriculture, transporta- tion, communications, and retail trade. Adapting SPIOER indexes to the input-output framework per- mits us to (1) compare our indexes with the 1959, 1966, and 1972 input-output tables, (2) determine changes in the production mix over time, (3) judge the representativeness of our sample, and (4) most impor- tantly, employ value-added weights at a fairly disag- gregated level. SPIOER product series currently rep- resent all but 12 of the 84 industrial sectors. Of the 72 sectors covered, 58 sector indexes are determined at least partially by quantity samples, 11 are partly value series, and five are based solely on the CSA gross value of output indexes. The level immediately above the input-output sector is the Soviet branch (otrasl j, which is formed by com- bining selected input-output sectors. Branch-level in- dexes have three advantages: (1) the 10 major branches are much more manageable for analysis than the numerous input-output sectors; (2) the branch structure matches published Soviet data and, therefore, facilitates comparisons and tests of the SPIOER indexes; and (3) value added at factor cost can be calculated from Soviet data only at the branch level or above in 1970�the base year for CIA's GNP accounts.' The metal-producing sectors are an exception. The 1972 recon- structed input-output table combines ferrous metals, ferrous ores, nonferrous metals, and nonferrous ores into one sector. This is inadequate disaggregation for our purposes. Thus, we use relation- ships among these four sectors from the 1966 table in 1970 producer prices to estimate value added in the four sectors in 1972. For our purposes, therefore, the input-output table has 84 industrial sectors. See JEC, GNP, 1950-80. 183 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 1 Percent Share of Branch Value Added in 1972 Accounted for by Different Statistical Series Branch Type of Series Quantity CSA Value CSA GVO Unrepresented a All industry 73.3 10.7 8.0 8.0 Ferrous metals 94.8 5.2 Nonferrous metals 62.7 37.3 Fuel 100.00 Electric power 100.00 Machinery 53.3 18.5 23.9 4.3 Chemicals 77.4 4.1 18.7 Wood, pulp, and paper products 78.4 16.7 4.9 Construction materials 100.00 Light industry 63.9 36.1 Processed food 100.00 a This category consists of industrial activity lacking any representa- tion in SPIOER, such as nonferrous ores, cable products, and tools and dies. As indicated above, the impact of the less desirable CSA value and index series on all industrial indexes is confined to less than one-fifth of the weight. Ideally, the relative importance of each type of series would be about the same in the various branches of industry as in the total, so that no branch index would suffer more from the biased sector indexes than any other. Unfor- tunately, this is not the case. Only about one-half of the machinery index is accounted for by quantity series, nearly one-fifth by value series, and approxi- mately one-fourth by the least desirable GVO series. Other than machinery, the impact of the value and GVO series on branch estimates is quite limited (table 1). Only in light industry do value series represent more than one-third of total value." The highest level of subaggregation is the major industry group, which resembles the major compo- nents of the Federal Reserve Board's index of US ""Light industry" as used in this paper differs from the standard light- industry versus heavy-industry dichotomy used in the West. An appropriate synonym for light industry in the present context is soft goods consisting of articles such as textiles, clothing, and footwear. industrial production (table 2). SPIOER has three major groups: industrial materials, total machinery, and consumer nondurables. Construction of the Standard Indexes Alternative Approaches. Measurement of output be- comes a problem when the output of several diverse products must be combined into one series. One approach, and the basic method employed in the USSR, sums the values of the individual products to yield the gross value of output (GVO). This index usually appears in one of two variants. The first, the gross turnover of output (valovoy oborot), includes intraplant consumption of a plant's own products calculated by summing the value of output of individ- ual workshops within the plant. Most Soviet produc- tion statistics that are published in physical quantities include intraplant consumption. A second variant, the gross product (valovaya produktsiya), removes mate- rials and intermediate products fabricated by work- shops that are consumed within the plant. In general, 184 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 2 SPIOER Industrial Groupings Total industry Industrial materials Ferrous metals Nonferrous metals Fuel Electric power Chemicals and petrochemicals Wood, pulp, and paper products Construction materials Machinery Civilian machinery Producer durables Consumer durables Military machinery Consumer nondurables Light industry Processed food production series reported in value terms are computed on this basis. 22 The gross-output method of aggregation is mislead- ing, however, because the values include some inter- mediate product already counted elsewhere. For ex- ample, this procedure counts the value of coking coal used in manufacturing steel both in the output of the coal industry and in that of the steel industry. If the steel is used elsewhere in industry, the coking coal will be counted again. If the amount of double-counting of production is constant and the industrial structure is stable, then the bias in the computed growth rate is minimal since the growth rate of value added and gross output of each enterprise will be nearly identical. A small bias 12 For a discussion of the two types of gross output measures, see M. R. Eydel'man, Mezhnotraslevoy balans obshchestvennogo pro- dukta, (Moscow: Statistika, 1966) pp. 200-203, A. I. Yezhov, Statistika promyshlennosti, (Moscow: Statistika, 1977), pp. 57-61, and Vladimir G. Treml, Dimitri M. Gallik, Barry L. Kostinsky, and Kurt W. Kruger, The Structure of the Soviet Economy: Analysis and Reconstruction of the 1966 Input-Output Table, (New York: Praeger Publishers, 1972), pp. 45-46. arises because the output of the separate enterprises will be combined by gross-output weights rather than value-added weights.' The principal bias from double-counting arises, how- ever, from increasing vertical specialization in the production of a given commodity. This causes the gross output of an enterprise to rise faster than value added. The bias caused by this type of double- counting is particularly severe over time, where the economic structure is rapidly changing. By any stand- ard, Soviet industry has grown rapidly over the last three decades and the degree of specialization has increased somewhat. Soviet industry is notorious for its autarky. Because of the vagaries of its distribution system, enterprise and ministry managers want to control as much as possi- ble the production and distribution of the material inputs needed by their enterprises. Enterprises and ministries frequently produce goods that clearly are not their specialty. Soviet planners and academics have long realized that this excessive vertical integra- tion hampers efficiency, and there have been numer- ous campaigns over the years to encourage specializa- tion. To the extent these campaigns have been efficacious, this would increase double-counting and the upward bias of gross output as a measure of the growth of industrial production. The construction materials industry is a prime exam- ple of how a changing industrial structure causes double-counting to increase. At one time, most ce- ment was shipped directly to the construction indus- try. Soviet leaders decided, however, to "industrialize construction" by fabricating as many construction elements�such as walls, bathroom units, and railroad tracks�as possible in a plant instead of on site by the construction industry. This means that much of the cement is now converted into precast concrete pro- ducts by other plants within the construction materi- als industry, and a larger share of cement output is now double-counted than formerly. ' For a discussion of the biases of gross-output measures and double-counting, see Rush V. Greenslade, "Industrial Production Statistics in the USSR," pp. 155-194. 185 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Finally, industries with a high ratio of material inputs to gross output are more susceptible to biases imposed by double-counting. This means we would expect a greater danger of significant bias in the measurement of machinery, chemicals, and construction materials output and a smaller bias in the remaining branches. The preferred measure for most purposes is the sum of value added by industrial sector, where value added equals gross value of output of a sector less purchases of goods and services from other sectors of the economy. Value added measures the net contribution of a particular industry to national product. It is the sum of profits, wages, depreciation, other payments to the factors of production, and indirect business taxes less subsidies. To construct a value-added index, however, requires accurate data on production (quan- tities and prices) and purchases of inputs from other sectors (quantities and prices). Two approaches have been used to derive indexes of value added in constant prices. One approach�re- ferred to in the economic literature as double-defla- tion�measures both outputs and intermediate inputs in constant prices, where value added is the difference between the two. This can be accomplished in one of two ways; either constant price measures for output and intermediate inputs can be used or current price measures for each individual component can be de- flated with price indexes. The information require- ments of this approach are extremely rigorous because both outputs and purchases from other sectors of the economy must be tracked over time. While reported Soviet production data are deficient in quantity and quality, statistics on material inputs are even scarcer. For this reason, double-deflation is not practical in compiling SPIOER. An alternative approach (used in the Federal Reserve Board's index of US industrial production) is a hybrid procedure that combines gross output indexes with value-added weights for a base year. This approach, known as a single indicator method, is as good as double-deflation only if gross output and purchases from other sectors move over time at the same rate. Since this is a rough approximation at best, the hybrid FRB-type indexes only approximate a true value- added series. They do remove most of the double- counting inherent in pure GVO measures of industrial production (completely in the base year, less than completely in other years). While double-deflation is closer than the single indi- cator approach in theory to the notion of value added, both the output and input indexes used by double- deflation must be accurate. T. P. Hill has argued convincingly that under fairly weak assumptions er- rors in the output and input indexes will compound measured bias rather than offset each other and that using a single indicator will produce a more accurate result. Moreover, Hill's study of growth in several OECD countries suggests that on average the growth rate is not much different whether double-deflation or a single indicator is used. Although the method used undoubtedly affects the measured growth of some components of industrial activity, these differences tend to cancel out." Depending on whether gross output or value added is used, one may receive an entirely different impression of both industrial structure and growth. In figure 3 the share of industrial production by branch of indus- try in 1972 is displayed both for gross output and value-added weights. The gross-output scheme tends to give a higher weight to sectors that either produce mainly for final consumption or are highly material intensive and a lesser weight to sectors that either produce mainly for further industrial processing or are highly labor and capital intensive. Thus, to the extent that industries with the most double-counting are growing relatively slowly, the gross- output index is biased downward and vice versa. In the Soviet case, both light industry and processed foods have lagged behind other branches whereas machinery has grown the fastest. With gross-output weights, light industry and processed food gain in importance and machinery loses. Other things being equal, therefore, Soviet gross output of industry tends to increase more slowly than value added. ' For an extensive discussion of the properties and relative merits of the two methods, see T. P. Hill, The Measurement of Real Product: A Theoretical and Empirical Analysis of the Growth Rates for Different Industries and Countries, (Organization for Economic Co-operation and Development, 1971), pp. 11-37, 111-112, 118- 119. 186 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 3 Branch Share of 1972 Industrial Gross Output and Value Added Percent Ferrous metals Nonferrous metals Fuels Electric power Machinery Chemicals and petro- chemicals Wood, pulp, and paper products Construction materials Light industry Processed food Industry, nec -� lb � lc � 1 � � � � � � � � 5 10 15 20 25 30 35 1:1 Gross output El Value added Derivation of the Branch Indexes. For reasons enu- merated above, the SPIOER indexes use the single indicator technique to measure industrial production. Computing the branch indexes involves: creating the sector indexes, deriving the sector value added, and aggregating the sectors into branches. The indicator used is based on gross output. The method for esti- mating the indexes described below applies to every branch except for machinery, where the methodology is slightly more complicated. To construct the 72 sector indexes, the sample of industrial products is classified by input-output sec- tors to develop a series of subsamples. Each individual line item is multiplied by its 1 July 1967 enterprise wholesale price to convert all sample items into value terms. Then for each sector in every year all of the line items in a subsample are summed to yield a value series for sample output in that sector. Finally, these sector series are indexed to the base year of 1970. Next value added in each sector is derived for 1972 from the reconstructed input-output table in producer prices.' Total purchases by each sector are subtracted from its gross outlays (or gross output.) 16 For other " A somewhat more aggregated form of this input-output table appears in the article by Dimitri M. Gallik, Gene D. Guill, Barry L. Kostinsky, and Vladimir G. Treml, "The 1972 Input-Output Table and the Changing Structure of the Soviet Economy," Soviet Economy in a Time of Change, vol. I, pp. 423-471. This particular version of the 1972 table allocates the taxes and subsidies on the purchases of every sector to the interindustry quadrant. This avoids the problem of a negative value added that would arise in many of the sectors in the processed food branch. Since food prices are held down artificially by the government, many of these sectors must receive substantial subsidies. 187 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 years value added in each sector is computed by finding the ratio of the value for the sector index in each year to its value in 1972 and then multiplying this ratio by value added in 1972 as derived from the input-output table. Finally, to obtain the branch indexes, every sector is first allocated to one of the 10 industrial branches. Then for each year the estimated value added for all of the sectors belonging to that branch are totaled. After totals for each branch are converted to indexes with base 1970=100, these branch indexes are equiv- alent to an aggregation of production indexes using value-added weights. This procedure entails at least four possible sources of error: � The samples for each sector may be unrepresenta- tive of actual gross output over time. � Value added may not move in the same way as gross output because the material intensiveness of produc- tion may have changed. � Value-added estimates for the sectors may be wrong because in the reconstruction of the 1972 input- output table they were derived as a residual, and thus are subject to all of the uncertainties that plague any residual. � The price bases of the input-output table (1972 prices) and the product sample (1967 prices) are both different from the 1970 prices that should be used. These possible sources of error are discussed in detail below in the section, "Evaluation of the New Indexes." The Machinery Index The machinery index has undergone substantial revi- sion since the methodology was last described in 1976. Revisions have focused on five areas: � More machinery sectors are represented in the producer durables indexes. � Passenger automobiles for private purchases and other consumer-oriented automotive products have been shifted from the producer durables to the consumer durables component of the machinery index. � Some sectors producing both consumer durables and producer durables have separate indexes to represent each component. � The Tovary series adjusted to deduct furniture production is no longer used as the sole measure of consumer durables.'' � Finally, new weights for producer and consumer durables have been derived with the help of the 1972 input-output table. The machinery branch is handled differently because we want to disaggregate branch output according to how the machinery is used (figure 4). Since the use of value-added weights implies a production orientation and the different components of the machinery index are based on end use, the disaggregation is not easy. The first useful end-use distinction within machinery is between civilian machinery and military machinery. Here, military machinery excludes common-use dura- bles�products with both civilian and military appli- cations, such as trucks or bulldozers�because they are already reflected in production reported by the CSA. Since the USSR publishes no statistics on uniquely military machinery production, we rely on CIA estimates. A second useful distinction within the machinery branch is between producer durables and consumer durables, reflected only infrequently in Soviet statis- tics. Consumer durables output appears indirectly in the official Tovary time series. Although SPIOER formerly used this series as a proxy for consumer durables, it neither consists exclusively of consumer durables nor does it contain all consumer durables. For example, the Tovary series includes nondurables such as household chemicals, and may exclude the production of passenger cars destined for private purchase. Because reliable official data are not at hand to separate consumer durables from producer durables, we must use an alternative method. The full title of this series is "production of commodities of cultural-everyday significance and household articles" (proiz- vodstvo tovarov kurturno-bytovogo naznacheniya i khozyaystvennogo obikhoda). Hereafter this series is referred to as Tovary. 188 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 4 Structure of the Machinery Branch To achieve the desired disaggregation of machinery production according to end use, we rely on the categories of final demand included in the recon- structed Soviet input-output tables. These tables allo- cate final demand among three categories: private consumption, public consumption, and other final demand. We assume that the machinery-producing sectors allocate consumer durables output to private consumption. Public consumption contains "consump- tion of material product by state organizations and agencies servicing the population, i.e., health, educa- tional, entertainment, and other such agencies." In addition, public consumption includes: consumption by public housing, utilities, personal transportation, communications, and the state. Other final demand consists of net accumulation of fixed capital, working capital, inventories, and state reserves; replacement of depreciated fixed capital and capital losses and capital repair; other expenditures and net exports." We as- sume that both deliveries to public consumption and to other final demand are preponderantly producer durables. (This is an oversimplification because this definition of producer durables undoubtedly captures machinery that is uniquely military and any consumer durables that are exported.) We then are able to generate a set of value-added weights in each machin- ery sector for producer durables and consumer dura- bles. The details of this procedure are described further in appendix B. " Treml, Gallik, Kostinsky, and Kruger, Structure, pp. 48-49. Also see Vladimir G. Treml, Dimtri M. Gallik, and Barry L. Kostinsky, "1966 Ex Post Input-Output Tables for the USSR: A Survey," Vladimir G. Treml, ed., Studies in Soviet Input-Output Analysis, (New York: Praeger Publishers, 1977), P. 9. 189 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 3 Industry: 1970 Value Added at Factor Cost by Branch 1970 Value Added by Branch at Factor Cost (billion rubles) a Share of Industry Group (percent) b Share of Industry (percent) c Industrial Materials 59.113 100.0 49.7 Ferrous metals 8.793 14.9 7.4 Nonferrous metals 4.810 8.1 4.0 Fuel 12.070 20.4 10.1 Electric power 8.308 14.1 7.0 Chemicals 7.756 13.1 6.5 Wood, pulp, and paper 9.388 15.9 7.9 Construction materials 7.988 13.5 6.7 Machinery 38.528 100.0 32.4 Consumer nondurables 21.404 100.0 18.0 Light industry 9.761 45.6 8.2 Processed food 11.643 54.4 9.8 Subtotal 119.045 Other industry 3.564 Total industry 122.609 a JEC, GNP, 1950-80. See table E-4. The groups-industrial materials and consumer nondurables-are sums of the branches directly below them. b Each value added in column 2 divided by the appropriate group total. c Value added in each branch and group divided by the subtotal for all industry. The effect of dividing by the subtotal is to allocate other industry proportionally among all of the branches. The Index of Total Industrial Output The calculation of indexes for the three major indus- try groups and for total industry can be summarized briefly. Since these indexes are used in estimating Soviet GNP within the framework of the GNP ac- counts maintained by the Office of Economic Re- search, we use the branch value added at factor cost in 1970 as weights instead of weights derived from input-output tables. The purpose of using factor cost instead of established prices for measuring value added is to count the true resource costs of produc- tion. The chief differences from an established price valuation are that factor cost subtracts taxes, adds subsidies, and imputes the costs of productive factors not appropriately accounted for by Soviet procedures, such as charges on fixed capital and working capital.'9 " See CIA, USSR: Gross National Product Accounts, 1970, pp. 1, 20, 85. Table 3 shows these weights and the relative impor- tance of each branch. The group and aggregate indexes are obtained by converting each branch index to a value-added basis and then summing the ele- ments within each group and all industry. Soviet Industrial Growth, 1950-80 Having described the methodology of the production index, we present the indexes and review some of the key developments in Soviet industry since 1950. Revised SPIOER Indexes The revised SPIOER indexes for the period 1950-80 are given in table 4 and the annual rates of growth in table 5. The average annual rates of growth for various quinquenniums are further summarized in table 6. The indexes for the individual input-output 190 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 4 Soviet Industrial Production Indexes 1970=100 1959 1950 1951 1952 1953 1954 1955 1956 1957 1958 Industrial materials 21.61 24.24 26.37 28.66 31.81 35.53 38.52 42.07 46.43 50.89 Ferrous metals 22.63 25.57 29.08 31.91 34.79 38.32 41.21 43.66 46.61 50.67 Nonferrous metals 19.00 21.54 24.24 27.03 29.58 34.72 36.81 38.88 41.04 44.38 Fuels 24.03 26.25 28.05 29.99 33.07 37.63 41.77 46.57 50.87 54.45 Electric power 12.48 14.20 16.25 18.33 20.49 23.10 26.03 28.51 32.00 35.97 Chemicals and petrochemicals 13.03 14.31 15.61 17.22 19.59 22.52 25.26 27.65 31.02 33.72 Wood, pulp, and paper 40.37 45.80 47.60 49.63 54.66 57.65 59.70 63.91 69.87 76.29 Construction materials 14.18 16.13 18.19 21.22 24.73 29.37 32.61 37.88 45.19 52.00 Total machinery 21.61 23.73 25.78 28.07 30.60 34.20 36.67 39.16 42.10 45.89 Including: Producer durables 14.29 15.31 16.96 19.63 22.01 24.94 28.45 33.40 37.97 41.81 Consumer durables 9.97 11.00 12.60 15.23 18.27 22.54 24.86 27.12 29.53 33.33 Consumer nondurables 24.79 28.79 31.00 34.17 37.42 40.47 44.24 46.71 50.33 54.88 Light industry 27.79 32.66 34.75 38.06 42.55 45.59 48.28 50.51 54.53 58.70 Processed food 22.27 25.55 27.85 30.91 33.12 36.18 40.86 43.54 46.82 51.68 Total industry 22.18 24.90 27.01 29.46 32.42 35.99 38.95 41.96 45.73 49.99 1969 1960 1961 1962 1963 1964 1965 1966 1967 1968 Industrial materials 54.38 57.71 61.56 65.82 70.59 75.47 80.16 85.51 89.80 93.60 Ferrous metals 55.15 59.83 64.42 68.43 73.42 78.11 82.94 87.63 91.62 94.82 Nonferrous metals 48.37 52.42 57.07 61.53 65.21 69.88 76.69 83.50 90.17 94.66 Fuels 57.73 60.56 64.06 69.44 73.95 78.31 83.33 87.69 90.77 94.76 Electric power 39.65 44.46 50.16 55.80 62.03 68.26 73.48 79.13 86.09 92.90 Chemicals and petrochemicals 37.13 40.82 45.12 49.98 56.85 65.32 71.85 79.02 84.67 89.82 Wood, pulp, and paper 76.40 76.29 78.09 81.38 85.07 86.77 87.17 91.52 93.71 95.37 Construction materials 58.27 62.57 65.77 67.60 70.88 75.76 81.22 86.97 90.36 92.16 Total machinery 50.07 54.30 59.84 63.67 67.75 71.48 74.72 79.72 86.90 92.88 Including: Producer durables 44.82 48.26 54.55 58.67 63.72 68.53 72.50 78.52 86.34 92.17 Consumer durables 37.00 41.10 45.61 49.74 54.01 58.52 64.90 72.96 81.99 90.73 Consumer nondurables 57.75 60.92 63.89 65.72 68.51 73.17 77.40 83.44 88.99 94.34 Light industry 62.07 64.34 66.56 67.47 69.47 70.70 75.96 82.26 88.75 94.40 Processed food 54.12 58.06 61.66 64.26 67.70 75.25 78.61 84.42 89.18 94.30 Total industry 53.59 57.18 61.42 65.11 69.30 73.77 77.90 83.26 88.72 93.50 191 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 4 (continued) Soviet Industrial Production Indexes 1970=100 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 Industrial materials 100.00 105.66 110.76 116.88 123.12 130.19 134.88 138.77 142.62 144.11 147.77 Ferrous metals 100.00 103.79 107.25 111.57 116.30 121.45 124.70 125.60 128.38 128.45 128.02 Nonferrous metals 100.00 107.02 112.72 119.56 126.92 132.89 137.08 141.26 145.90 150.22 151.43 Fuels 100.00 104.81 109.78 115.11 120.73 127.83 132.54 138.12 142.47 146.70 150.14 Electric power 100.00 108.12 115.80 123.62 131.88 140.58 150.29 155.65 162.90 167.68 175.26 Chemicals and petrochemicals 100.00 108.06 115.28 125.71 137.67 151.03 158.26 166.55 172.49 172.88 181.90 Wood, pulp, and paper 100.00 102.80 104.83 107.66 109.59 113.59 113.45 113.98 113.44 110.16 113.22 Construction materials 100.00 106.67 112.27 119.01 124.61 130.24 134.76 137.37 140.73 141.19 142.59 Total machinery 100.00 108.12 115.61 125.25 135.96 146.38 154.50 163.21 172.39 182.04 189.96 Including: Producer durables 100.00 110.05 117.97 128.34 139.60 151.03 160.70 171.22 182.05 193.00 200.39 Consumer durables 100.00 112.62 128.14 144.86 159.91 173.85 184.68 197.98 214.65 224.14 232.72 Consumer non- durables 100.00 103.43 105.60 107.40 113.32 117.99 119.42 123.40 124.11 127.29 127.47 Light industry 100.00 104.48 105.26 108.24 111.11 114.30 119.05 122.06 125.21 127.41 129.96 Processed food 100.00 102.55 105.89 106.69 115.17 121.09 119.73 124.52 123.19 127.18 125.38 Total industry 100.00 106.06 111.40 117.88 125.51 133.24 138.45 143.92 148.93 153.36 157.77 sectors used for computing output for the branches and total industry appear in appendix table A-2. Major Trends in Industrial Production The postwar period of Soviet industrial growth falls naturally into three phases: an immediate postwar boom, a period of stable-but slowly declining- overall growth, and then a prolonged slowdown. These three phases are clear and pronounced for total industry and for industrial materials (figure 5). Ma- chinery conforms to this pattern except in the middle phase. Its growth slows initially in the 1960s, as do the other groups, but growth then improves in the mid- 1960s where it remains on a plateau until the third phase begins. Consumer nondurables also do not exhibit a stable middle phase, showing instead large growth fluctuations around a steadily declining trend. The postwar industrial boom lasted through the 1950s with annual industrial growth ranging between 8 and 12 percent per year. As the Soviet economy rebuilt from the massive destruction of World War II, expan- sion focused on those industries most vital to the nation's investment programs-construction materials and machinery. Production of consumer nondurables generally grew more slowly even though production was at a low absolute level. The early 1960s marked the beginning of a new phase in Soviet industrial development as growth slowed sharply in practically every branch. For the next decade and a half, the growth of total industrial 192 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 5 Soviet Industrial Production: Annual Rates of Growth Percent 1959 1951 1952 1953 1954 1955 1956 1957 1958 Industrial materials 12.2 8.8 8.7 11.0 11.7 8.4 9.2 10.4 9.6 Ferrous metals 13.0 13.7 9.7 9.0 10.1 7.6 5.9 6.8 8.7 Nonferrous metals 13.3 12.5 11.5 9.4 17.4 6.0 5.6 5.6 8.1 Fuels 9.2 6.9 6.9 10.3 13.8 11.0 11.5 9.2 7.0 Electric power 13.8 14.4 12.8 11.8 12.7 12.7 9.5 12.3 12.4 Chemicals and petrochemicals 9.8 9.1 10.3 13.8 14.9 12.2 9.5 12.2 8.7 Wood, pulp, and paper 13.4 3.9 4.3 10.1 5.5 3.6 7.0 9.3 9.2 Construction materials 13.7 12.8 16.7 16.5 18.8 11.0 16.2 19.3 15.1 Total machinery 9.8 8.6 8.9 9.0 11.8 7.2 6.8 7.5 9.0 Including: Producer durables 7.1 10.8 15.7 12.1 13.3 14.1 17.4 13.7 10.1 Consumer durables 10.3 14.6 20.9 20.0 23.3 10.3 9.1 8.9 12.9 Consumer nondurables 16.1 7.7 10.2 9.5 8.2 9.3 5.6 7.7 9.0 Light industry 17.5 6.4 9.5 11.8 7.1 5.9 4.6 8.0 7.6 Processed food 14.7 9.0 11.0 7.2 9.3 12.9 6.6 7.5 10.4 Total industry 12.2 8.5 9.1 10.1 11.0 8.2 7.7 9.0 9.3 1969 1960 1961 1962 1963 1964 1965 1966 1967 1968 Industrial materials 6.9 6.1 6.7 6.9 7.2 6.9 6.2 6.7 5.0 4.2 Ferrous metals 8.8 8.5 7.7 6.2 7.3 6.4 6.2 5.7 4.6 3.5 Nonferrous metals 9.0 8.4 8.9 7.8 6.0 7.2 9.7 8.9 8.0 5.0 Fuels 6.0 4.9 5.8 8.4 6.5 5.9 6.4 5.2 3.5 4.4 Electric power 10.2 12.1 12.8 11.2 11.2 10.0 7.6 7.7 8.8 7.9 Chemicals and 10.1 petrochemicals 9.9 10.5 10.8 13.7 14.9 10.0 10.0 7.2 6.1 Wood, pulp, and paper 0.1 -0.1 2.4 4.2 4.5 2.0 0.5 5.0 2.4 1.8 Construction materials 12.1 7.4 5.1 2.8 4.8 6.9 7.2 7.1 3.9 2.0 Total machinery 9.1 8.5 10.2 6.4 6.4 5.5 4.5 6.7 9.0 6.9 Including: Producer durables 7.2 7.7 13.0 7.5 8.6 7.5 5.8 8.3 10.0 6.8 Consumer durables 11.0 11.1 11.0 9.1 8.6 8.4 10.9 12.4 12.4 10.7 Consumer nondurables 5.2 5.5 4.9 2.9 4.2 6.8 5.8 7.8 6.7 6.0 Light industry 5.7 3.6 3.5 1.4 3.0 1.8 7.4 8.3 7.9 6.4 Processed food 4.7 7.3 6.2 4.2 5.3 11.2 4.5 7.4 5.6 5.7 Total industry 7.2 6.7 7.4 6.0 6.4 6.5 5.6 6.9 6.5 5.4 193 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 5 (continued) Soviet Industrial Production: Annual Rates of Growth Percent 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 Industrial materials 6.8 5.7 4.8 5.5 5.3 5.7 3.6 2.9 2.8 1.0 2.5 Ferrous metals 5.5 3.8 3.3 4.0 4.2 4.4 2.7 0.7 2.2 0 -.3 Nonferrous metals 5.6 7.0 5.3 6.1 6.2 4.7 3.1 3.1 3.3 3.0 0.8 Fuels 5.5 4.8 4.7 4.9 4.9 5.9 3.7 4.2 3.1 3.0 2.3 Electric power 7.6 8.1 7.1 6.8 6.7 6.6 6.9 3.6 4.7 2.9 4.5 Chemicals and petrochemicals 11.3 8.1 6.7 9.0 9.5 9.7 4.8 5.2 3.6 0.2 5.2 Wood, pulp, and paper 4.9 2.8 2.0 2.7 1.8 3.6 -0.1 0.5 -0.5 -2.9 2.8 Construction materials 8.5 6.7 5.2 6.0 4.7 4.5 3.5 1.9 2.4 0.3 1.0 Total machinery 7.7 8.1 6.9 8.3 8.5 7.7 5.5 5.6 5.6 5.6 4.4 Including: Producer durables 8.5 10.1 7.2 8.8 8.8 8.2 6.4 6.5 6.3 6.0 3.8 Consumer durables 10.2 12.6 13.8 13.0 10.4 8.7 6.2 7.2 8.4 4.4 3.8 Consumer non- durables 6.0 3.4 2.1 1.7 5.5 4.1 1.2 3.3 0.6 2.6 0.1 Light industry 5.9 4.5 0.7 2.8 2.7 2.9 4.2 2.5 2.6 1.8 2.0 Processed food 6.0 2.6 3.3 0.8 7.9 5.1 -1.1 4.0 -1.1 3.2 -1.4 Total industry 7.0 6.1 5.0 5.8 6.5 6.2 3.9 4.0 3.5 3.0 2.9 production remained fairly stable at around 6 percent, although it trended slightly downward. During this period of apparent industrial consolidation, machinery production continued to drive overall industrial growth. Growth in industrial materials and consumer nondurables was generally slower and showed a stron- ger downward slide. While all signs suggest that the growth of industrial production slowed considerably after the 1950s, the extent and suddenness of the decline in the indexes may be deceptive. One likely cause of the sudden slowdown is the decline in the workweek from 46 to 41 hours by 1960. Thus, even with a 4.4-percent increase in industrial employment in 1960, labor inputs increased only 0.5 percent.2� Considering that 21) Steven Rapawy, Estimates and Projections of the Labor Force and Civilian Employment in the U.S.S.R. 1950 to 1990, Foreign Economic Report Number 10, (Washington: U.S. Department of Commerce, September 1976), p. 43. The data presented were revised and updated in February 1980. the Soviets historically have achieved growth by the infusion of new inputs, it is not surprising that growth slowed. A lesser possibility, is that statistical reporting practices may have tightened after the 1950s to reduce the inflation of reported output in later report- ing periods!' The current phase of industrial slowdown began in the mid-1970s when growth of machinery production started to falter and machinery production could no longer offset the gradual slowdown in the growth of materials and nondurables. This slowdown reflects the slowing growth in the industrial labor force, a con- tinuing failure to assimilate new production capacity 2 For a discussion of the padding of Soviet output statistics, see Gregory Grossman, Soviet Statistics of Physical Output of Indus- trial Commodities, (Princeton: Princeton University Press, 1960), and Alec Nove, "A Note on the Availability and Reliability of Soviet Statistics," in Morris Bornstein and Daniel R. Fusfeld, ed., The Soviet Economy: A Book of Readings (fourth edition; Homewood, Illinois: Richard D. Irwin, Inc., 1974), pp. 237-245. 194 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 6 Soviet Industrial Production: Average Annual Rates of Growth Percent 1976-80 1951-55 1956-60 1961-65 1966-70 1971-75 Industrial materials 10.5 8.9 6.8 5.8 5.4 2.6 Ferrous metals 11.1 7.6 7.2 5.1 4.0 1.1 Nonferrous metals 12.8 6.9 7.6 7.4 5.9 2.6 Fuels 9.4 8.9 6.3 5.0 5.0 3.3 Electric power 13.1 11.4 11.5 7.9 7.0 4.5 Chemicals and petrochemicals 11.6 10.5 12.0 8.9 8.6 3.8 Wood, pulp, and paper 7.4 5.8 2.6 2.9 2.6 -0.1 Construction materials 15.7 14.7 5.4 5.7 5.4 1.8 Total machinery 9.6 7.9 7.4 6.9 7.9 5.4 Including: Producer durables 11.8 12.4 8.9 7.8 8.6 5.8 Consumer durables 17.7 10.4 9.6 11.3 11.7 6.0 Consumer nondurables 10.3 7.4 4.8 6.4 3.4 1.6 Light industry 10.4 6.4 2.6 7.2 2.7 2.6 Processed food 10.2 8.4 6.8 5.9 3.9 0.7 Total industry 10.2 8.3 6.6 6.3 5.9 3.4 on time, declining capital productivity, and little success in boosting worker productivity. The result has been the low rates of industrial growth in recent years. The decline in growth is continuing. The USSR faces severe strains because of deceleration in the growth of available inputs-especially fuels, minerals, and la- bor.22 The lack of success in boosting productivity during the 10th Five-Year Plan suggests that the Soviets will be hard pressed to offset tightening input bottlenecks. " See CIA, Soviet Economic Problems and Prospects, ER 77- 10536 U (July 1977). Since 1950 some evolution of the industrial structure has occurred: Estimated Share of Industrial Percent Value Added, 1967 Prices 1950 1980 Industrial materials 48.4 46.5 Total machinery 31.5 39.0 Consumer nondurables 20.1 14.5 195 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 5 Growth of Soviet Industrial Production Three-year moving average Percent Total industry 10 8 6 Industrial materials 10 8 6 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �������������.. � � � � � � � � � � � � � � � � � � � � ..40.6%....e.e.0. � 4. � � � � � � � � � � � � � � . � . � � � � � � � 4 ............................... � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � ............................... � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � ����� oo.e.o.s.������� � � � � � � � � � � � � � � � � ��� 1 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 0...0.0.0.0.6.46.41.6 � � � � � 6 2 �� � � � � � . � � � � � � � � � � � w � � � � � � � � � � 2 � � � � � � . . . � � � � � � � . . .�.�.�.� . .� . . . . ....... . � � � � � � �.�.�.*.�.�.'.�.'.'.�.�.�.*.�.�.� � � � � � � . . . . . 0 � � � � � � � � � � � � � � � � � � � � � � � � � � � � � ��� � � � � � � � � � � � � � . . . . I 1..1.164 7.1.P ����:..1.../:.;�Fr.....r.;4�1.1..16./.� � � i � i 1 � � � � � � � � � � 0 1950 55 60 65 70 75 80 0 1950 55 60 65 70 75 80 � � 1 � � � � � � � 1 � � � � � � � � � � � 0 � � � � � � � � 41 � � � 1 � � � � � � � � � � � � . � � II � � � � � � � � � � � � � . � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 41k..*.*.*.�.*.�.�.'.�.*.%�������� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � Total machinery 10 8 6 4 � II. � � � � � � 11 � � � � � � � � � � ..� � � � � � � � � � � � � � � � � � � � . � � � � � � � � � � � � � � � � � � � � � � � � � � � ��� � � � � � � � � � � � � � 0.0.6.4..e.e.o.e.e.e.e.e.......b.e. � � � � � � 40 � � do � � � � � or � � � � � � 0. IP � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � O � � � � � � 0 � � � � � � e.. � e.10..0.�.�... � � � � � � 000.������������� � � � � O � � � � � � � � � � � � � � � � � � � � 4%80 2 � � � � � � . � � � � � � � . � � � � � � � � � � � � � � � � � � � � � � .0 � � � � � � � � � : : :1 0 1950 55 60 65 70 75 80 dr.. � � � � � � � � � AD ��� � � � ��� ��� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 0'....... ��������������� � � � � � � � 0 � � � � � � � � � � ID � � � � � 4,........ �.�������������� 1 � � � � � � � � � � � �...e.�...�.�...� � � � � � � le � � � � .'.'.'.. . . . 4 � I P 101�41 S67.1� 1.15 Consumer nondurables 10 8 6 4 2 � 0 � � 0 � � � � � � � � � � 0 � � � � � � � 0 � � � � � � � � � � � � � � � � � 0.0.0.0.0.0.0 � � � � � � 0 � � � � � � � � � � � � 0 � � � � � � � � � � � � � � � � � � � � � � � � 0 � � � � � � � � � � � � � � � � � � � � � � � � � 0 � � � � � � � � � � 0 � 0 � � � � � � � � � � � � � � � � � � � � � � � � 0 1950 55 Postwar boom Stable, slowly declining Slowdown 60 65 70 75 80 196 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 In 30 years, the share of industrial materials has dropped by only 2 percentage points. Machinery's share of the industrial pie has expanded by 8 percent- age points until now where it represents nearly two- fifths of industrial production. It comes as no surprise, however, that this growing share comes mostly at the expense of consumer nondurables. Industrial Materials. During the overall decline in the growth of the production of industrial materials (from 10.5 percent per year in 1951-55 to 2.6 percent per year in 1976-80) the relative growth positions of the branches in the group changed markedly. At first, construction materials, electric power, and nonferrous metals were the fastest growing branches in the industrial materials group as well as in all of industry. The dramatic growth of: these three branches stemmed from the needs of postwar reconstruction and the rapid arms buildup during the Cold War. Chemicals and ferrous metals were also leading sec- tors in the early 1950s; fuels and wood, pulp, and paper products were at the bottom. In the last half of the decade, construction materials and electric power maintained their strong growth positions and were joined by chemicals. Meanwhile, both metals branches slipped into the slow growth group. Since the early 1960s, the chemicals branch has become the fastest growing branch in all industry, followed by electric power and a resurgent nonferrous metals branch. Meanwhile, construction materials, fuels, ferrous metals, and wood, pulp, and paper branches have continued to grow below the average for the industrial materials groups as a whole. The years 1976-80 were particularly disastrous for industrial materials. Growth in every branch of mate- rials fell to record lows. Chemicals lost its position as growth leader to the machinery branch. As an exam- ple of the widespread slowdown, electric power be- came the fastest growing component of industrial materials even though its growth was only two-thirds of the rate achieved from 1971 to 1975. Machinery. The machinery branch has been the fastest growing component of industrial production for most of the 1960-80 period and has been perhaps the most dynamic element in the entire economy. Machinery experienced a sharp decline in growth in the early 1960s along with the rest of industry. It rebounded during the rest of the decade and into the 1970s, when it too began to share in the current decline. During much of the postwar era, the growth of consumer durables output has outpaced producer durables�partly because it started from an extremely low base. The changing composition of consumer durables production has also helped to generate strong growth rates." In the 1950s consumer durables pro- duction was so primitive that products such as kitchen utensils and small electrical appliances accounted for the bulk of the growth. In the 1960s larger appli- ances�televisions, refrigerators, and washing ma- chines�began to drive consumer durables output. Early in the 1970s output of automobiles sold to consumers also began to grow rapidly. In the past few years, however, the growth of automotive production has tailed off, and consumer durables growth has approached that of producer durables. Some of this deceleration may reflect strained supplies of ferrous metals, which also support investment and the produc- tion of military hardware. Production of producer durables grew rapidly during the postwar boom�even accelerating for a long time�as capital stock throughout the economy was replenished and expanded. Practically every machin- ery component except that destined for consumer- related industries shared in the revival. Toward the end of the 1950s, growth of producer durables output dropped sharply across the board, except for agricul- tural machinery whose output expanded in the early 1960s. From the late 1960s until the beginning of the current period of slowdown, growth picked up slightly as investment expanded. During this period somewhat " For an early discussion of the different phases of consumer durables output when the product composition changed significant- ly, see Marshall I. Goldman, "The Reluctant Consumer and Economic Fluctuations in the Soviet Union," Journal of Political Economy, (August 1965), pp. 366-380. 197 33-892 0 - 82 - 14 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 more resources were devoted to machinery for con- sumer industries, precision instruments, motor vehi- cles, and agricultural machinery. In the 1970s, pro- ducer durables growth has slowed with the rest of industry, especially the production of motor vehicles, freight cars, agricultural machinery, instruments, and equipment for consumer industries. Consumer Nonduraples. Light industry and processed food generally have been the slowest growing branches of industry. Production of consumer goods traditionally has not had the highest priority, and production of consumer nondurables by its very na- ture reflects performance in the trouble-plagued agri- cultural sector. Although both processed food and light industry fared well during the early boom period, output was still at extremely low levels. Both branches experienced a sharp decline in growth during the early 1960s, with the burden felt most severely by light industry. This decline reflected both a diversion of investment re- sources away from the consumer branches and rela- tively poor agricultural performance during 1961-64. By the middle of the decade, the growth of nondura- bles accelerated somewhat as crops improved and the increased production of machinery for consumer in- dustries began to have an impact on output. Light industry especially profited from this shift that tempo- rarily allowed consumer nondurables to grow faster than the industrial average. After the peak growth of nondurables output recorded in 1967, growth again trended sharply downward. Light industry fell back to its usual low growth patterns after the initial surge of new capital stock had worked its way through the system. The poor agricultural performance of the 1970s hampered pro- cessed food production: after the 1975 crop failure, processed food production declined absolutely in 1976, for the first time in the post-Stalin era. In addition, output in this branch declined twice more during the 10th Five-Year Plan. Evaluation of the New Indexes Since SPIOER was developed because the official industrial production indexes released by the CSA are unreliable, we need to judge the degree of improve- ment that SPIOER represents. We examine the syn- thetic indexes from several perspectives. One criterion is for consistency with the official data. Although the official indexes are unreliable growth measures, the SPIOER and official indexes should at least agree on the configuration of trends, and the indexes should at least roughly correspond regarding the relative growth among sectors. In addition, these indexes should satisfactorily remove the growth distortions; we would expect that generally the SPIOER growth rate should fall below the official rates. A second criterion is for the product sample to be representative of total industrial output. Although the inclusion in the sample of a large share of industrial product should help satisfy this standard, this does not guaran- tee that the sample will move as total industrial output especially if the material intensity of produc- tion has changed over time. According to a third citerion, any biases in the basic data should be minimal or at least partially offsetting. In this section of the paper, the SPIOER indexes are subjected to a series of tests to determine how well they satisfy the criteria of consistency, representativeness, and mini- mal bias. Consistency Tests Consistency With the Official Indexes. Consistency first implies that both sets of indexes�synthetic and official�should show roughly similar relative rates of growth among the branches of industry. Where differ- ences arise in the fastest or slowest growth sectors, there should be a plausible explanation. To test this property, average annual rates of growth were computed for six periods for every branch of industry for both SPIOER and the official indexes." For each five-year period the branches were ranked " The nonferrous metals branch was excluded from this and other tests because the CSA does not publish an appropriate index for that branch. 198 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 7 Rankings of Industrial Branches by Growth Rates 1951-55 1956-60 1961-65 1966-70 1971-75 1976-80 Ferrous metals SPIOER Official 4 6 7 5 4 5 7 7 6 8 7 7 Fuels SPIOER Official 8 7 4 6 6 7 8 7 5 5 4 Electric power SPIOER Official 2 4 2 3 2 3 2 3 3 4 2 3 Chemicals and petrochemicals SPIOER Official 3 2 3 4 1 1 1 1 1 2 3 2 Wood, pulp, and paper SPIOER Official 9 9 9 8 9 8 9 9 9 7 9 9 Construction materials a SPIOER Official 1 1 1 1 7 4 6 4 4 3 6 6 Machinery SPIOER Official 7 3 6 2 3 2 4 2 2 1 Light industry SPIOER Official 5 5 8 9 8 9 3 5 5 4 Processed food SPIOER Official 6 8 5 7 5 6 5 6 7 6 8 8 Spearman's Rank Correlation Coefficient b Sum of Squared Differences c 0.75 30 0.73 32 0.87 16 0.88 16 0.88 14 0.97 4 a For the official series, the construction materials branch is a combination of the published construction materials and glass and porcelain indexes. b Freund, Modern Elementary Statistics, pp. 364-366. c The sum of squared differences derived in the Spearman Rank Order Correlation test is significant at 99-percent level of confidence if the value is less than 20. For a discussion of the significance test, see James V. Bradley, Distribution-Free Statistical Tests, (Engle- wood Cliffs, New Jersey: Prentice-Hall, Inc., 1968), pp. 93-95, 314. 199 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 by growth rates. A statistical test was then performed using Spearman's rank correlation coefficient to de- termine the degree of agreement in branch growth rankings between the SPIOER and official indexes." The results are summarized in table 7. The sum of squared differences indicate that the rank correlation coefficients for the 1960s and 1970s are significant at the 99-percent confidence level�strong statistical evi- dence that both SPIOER and official branch indexes exhibit similar relative growth. The 1950s are a different matter, however, as the correlation is not significant at this level of confidence. The source of this insignificance is the wide disagreement over the machinery rankings. Both quinquenniums in the 1950s give machinery a rank four places higher in the official indexes than in the SPIOER versions. Perhaps disguised inflation operated at higher rates then than in the later periods. In every five-year period except 1971-75, both indexes agree on the most rapidly growing branch; in the one exception, the fastest growing branch in the SPIOER series is ranked second in the Soviet data. Moreover, in nearly every case the slowest growing branch in one set of indexes matches either the slowest or next slowest in the other. The largest divergence in rankings occurs during the 1950s, the smallest deviation during the most recent quinquennium. Since the beginning of the 1960s, the major incongru- ities have involved construction materials and machin- ery. The official series generally ascribe a higher rank to these two branches. In the case of construction materials, double-counting seems to have increased over the years, causing the growth of gross value of construction materials measured by the official data to be more rapid than our estimated growth of output. The increase in double-counting results partly from a conscious drive to "industrialize" construction. (See earlier discussion.) The machinery anomaly occurs because machinery is probably the branch most susceptible to the problems of new-product pricing. The official machinery index becomes an uncertain amalgamation of constant prices and current prices�the latter tending to rise " See John E. Freund, Modern Elementary Statistics, (3rd Edition; Englewood Cliffs, N. J.: Prentice-Hall, Inc., 1967), pp. 364-366. over time. The official machinery index inflated by so- called new product prices grows more rapidly than the SPIOER output indexes, so machinery tends to rank higher in the official series. Plausible Elimination of Inflated Growth. The offi- cial indexes are unacceptable because of the twin biases of new-product pricing and double-counting that exaggerate growth according to most Western observers and even some Soviet ones. If the SPIOER indexes are to be plausible measures of industrial growth, the difference between the SPIOER and official rates should be largest for those branches of industry most susceptible to upward bias�machinery, chemicals, and construction materials. The average annual rates of growth for both the official and SPIOER series are shown in table 8 for each quin- quennial period since 1950. The SPIOER growth rate is less than the official rate in each comparison period for total industry and for the individual branches with the exception of fuels (1956-60 and 1976-80) and processed food (1951-55 and 1956-60). The largest reductions in growth occur in those industries with the most severe new product pricing and double-counting problems: machinery, chemicals, and construction materials (table 9). All of these tests of SPIOER's consistency with the official index have considered only multiyear periods. A year-by-year comparison for total industry (table 10 and figure 6) shows that the SPIOER growth rate is less than the official rate for every year. Thus, to the extent that the SPIOER methodology is designed to avoid the growth distortions in the official series, it seems to do so. In most cases the rate of growth measured by SPIOER falls below the rate claimed in the official Soviet measures. Moreover, SPIOER reduces the rate of growth most in those branches�machinery, chemicals, and construction materials�most afflicted by new-product pricing and increased double-counting. Consistency of Growth Trends. A third consistency test compares the aggregate and branch growth trends measured by the SPIOER and official indexes. The SPIOER indexes should agree in general with the 200 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 8 Percent Comparisons of Average Annual Growth in SPIOER and Official Series 1971-75 1976-80 1951-55 1956-60 1961-65 1966-70 Total industry SPIOER Official 10.2 13.1 8.3 10.4 6.6 8.6 6.3 8.4 5.9 7.5 3.4 4.4 Ferrous metals SPIOER Official 11.1 12.1 7.6 8.8 7.2 8.0 5.1 5.7 4.0 5.0 1.1 1.9 Fuels SPIOER Official 9.4 10.1 8.9 8.5 6.3 6.5 5.0 5.7 5.0 5.1 3.3 2.9 Electric power SPIOER Official 13.1 14.4 1L4 13.1 11.5 12.3 7.9 9.0 7.0 7.1 4.5 5.0 Chemicals and petrochemicals SPIOER Official 11.6 17.3 10.5 12.0 12.0 14.4 8.9 12.2 8.6 10.6 3.8 5.7 Wood, pulp, and paper SPIOER Official 7.4 8.3 5.8 7.8 2.6 5.0 2.9 5.5 2.6 5.2 -0.1 1.5 Construction materials SPIOER Official 15.7 17.6 14.7 17.6 5.4 9.1 5.7 8.6 5.4 7.5 1.8 2.5 Machinery SPIOER Official 9.6 16.7 7.9 14.2 7.4 12.4 6.9 11.7 7.9 11.6 5.4 8.2 Light industry SPIOER Official 10.4 12.3 6.4 6.9 2.6 2.6 7.2 8.6 2.7 4.6 2.6 3.4 Processed food SPIOER Official 10.2 10.0 8.4 7.9 6.8 7.2 5.9 5.9 3.9 5.4 0.7 1.5 trends of the official indexes with respect to relative growth in different periods unless official series give totally distorted view of the pattern of growth over time. For example, a test for secular consistency might compare growth in the fifties with that in the seven- ties. A radical divergence between the SPIOER and the official indexes with respect to the pattern of Soviet development would throw considerable doubt on the synthetic indexes. We expect that even though a the official indexes are biased, they nonetheless reflect actual growth trends. To perform this test, we first compute the average annual rate of growth for 1951-80 and then several multiyear periods within that span for both SPIOER and the official series. These period growth rates are indexed relative to the historical average for that branch to then test both series for similar long-term 201 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 9 Percentage Points Difference Between Official and SPIOER Average Annual Growth Rates for Industry and Branches of Industry a 1951-55 1956-60 1961-65 1966-70 1971-75 1976-80 Total industry 2.9 2.1 2.0 2.1 1.6 1.0 Ferrous metals 1.0 1.2 0.8 0.6 1.0 0.8 Fuels 0.7 -0.4 0.2 0.7 0.1 -0.4 Electric power 1.3 1.7 0.8 1.1 0.1 0.5 Chemicals and petrochemicals 5.7 1.5 2.4 3.3 2.0 1.9 Wood, pulp, and paper 0.9 2.0 2.4 2.6 2.6 1.6 Construction materials 1.9 2.9 3.7 2.9 2.1 0.7 Machinery 7.1 6.3 5.0 4.8 3.7 2.8 Light industry 1.9 0.5 0.0 1.4 1.9 0.8 Processed food -0.2 -0.5 0.4 0.0 1.5 0.8 a These numbers represent the average annual percentage rate of growth for the official series less the SPIOER rates. Thus, a positive value indicates that SPIOER has a lower growth rate, while a negative one implies the opposite. movements. Interpretation of the test results is com- plicated because growth consistency can be assessed on at least four different planes, none of which is necessarily preferred. Maximum consistency between SPIOER and the official indexes is not necessarily optimal, since a trade-off exists between the accuracy of the SPIOER indexes and their consistency with the official indexes. As the degree of SPIOER's consisten- cy with the official indexes increases, eventually a point is reached where greater consistency implies mere replication of the growth distortions in the official indexes. A minimal interpretation of growth consistency re- quires simply that the SPIOER and official growth indexes agree on the above- or below-average years. Another interpretation of consistency is that the SPIOER and official indexes agree regarding the extremes, the periods of highest and lowest growth. A level of consistency even more difficult to achieve is that the growth rates of the SPIOER indexes and the official series move in the same direction from one period to the next. However, seeking consistency here risks forcing the inaccuracies of the official series onto the synthetic indexes. The highest degree of consisten- cy (in some cases undesirable) requires that the values of the indexed growth rates be nearly equal for a given period. Failure to ensure this highly rigid form of consistency is not critical, unless we assert that the amount of distortion in the official indexes remains unchanged from year to year. When the test results are interpreted from the stand- point of the agreement on above- and below-average years-whether the growth indexes are above or below 100-the SPIOER indexes do quite well (table 11). In only two out of 60 possible instances do the SPIOER and official indexes clearly disagree in assigning above- or below-average performance to a given period. In the two exceptions-chemicals and petrochemicals in 1966-70 and machinery in 1971- 75-only marginal changes in the index would remove the inconsistency. The consistency of SPIOER and official indexes with respect to the identification of the periods of hiphest and lowest growth is quite good. SPIOER estimates agree with the official indexes on the high growth 202 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 10 Difference Between Official and SPIOER Growth Rates for Industry Official a (percent) SPIOER (percent) Difference b (percentage point) 1951 16.4 12.2 4.2 1952 11.6 8.5 3.1 1953 12.0 9.1 2.9 1954 13.3 10.1 2.2 1955 12.5 11.0 1.5 1956 10.6 8.2 2.4 1957 10.0 7.7 2.3 1958 10.3 9.0 1.3 1959 11.4 9.3 2.1 1960 9.5 7.2 2.3 1961 9.1 6.7 2.4 1962 9.7 7.4 2.3 1963 8.1 6.0 2.1 1964 7.3 6.4 0.9 1965 8.7 6.5 2.2 1966 8.7 5.6 3.1 1967 10.0 6.9 3.1 1968 8.3 6.5 1.8 1969 7.1 5.4 1.7 1970 8.5 7.0 1.5 1971 7.7 6.1 1.6 1972 6.5 5.0 1.5 1973 7.5 5.8 1.7 1974 8.0 6.5 1.5 1975 7.5 6.2 1.3 1976 4.8 3.9 0.9 1977 5.7 4.0 1.7 1978 4.8 3.5 1.3 1979 3.4 3.0 0.4 1980 c 3.6 2.9 0.7 a Central Statistical Agency, Narkhoz 78, 79, and 80, (Moscow: Statistika, 1979, 80, and 81) p. 38. b This is the annual growth rate of the official series less the SPIOER rates. Thus, a positive value indicates that SPIOER has reduced the growth rate while a negative one implies the opposite. c Preliminary. period for total industry and eight out of nine branches and on the low growth period for all indexes. Only a minor shift would lead to perfect consistency at this level. A change in average growth rate of only 0.4 percentage point would bring the series for chemi- cals into conformity on the best growth periods. The secular consistency of SPIOER with respect to comparable period-to-period growth trends is surpris- ingly good. Table 12 summarizes the directional structure of the two growth index series. A negative sign indicates that growth has slowed while a positive one signifies an acceleration. When both signs match during a given period, the two indexes agree that growth has accelerated or decelerated. Of the 50 possible comparisons between the two sets of indexes, they agree on directional trend 45 times." Three of the five inconsistencies occur in the two branches of industry-construction materials and machinery- with the least reliable official output indexes. Consistent agreement on relative deviations of sub- period growth rates from the 1950-80 average is hard to interpret in terms of the reasonableness of the synthetic series because relative bias in either the official indexes or SPIOER may change. In any case the performance of SPIOER is mixed in this sort of comparison. In some cases-such as total industry, electric power, ferrous metals, and fuels-agreement is good on the pattern of growth. In others-like wood, pulp, and paper and construction materials- the magnitudes of growth shifts are very different in the two series. Therefore, SPIOER gives a somewhat different picture of the pattern of development in these latter branches. Consistency With Investment Series. Another way to test the representativeness of the producer durables sample is to compare this index with the official series 26 The test treats a result of no trend in one series versus some trend in the other as no match. 203 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 6 SPIOER and Official Series: Comparison of Annual Growth Rates for Industry Percent 18 16 14 12 10 8 6 4 2 \ 0 1950 55 60 65 70 aNarkhoz bThis is the annual growth rate of the official series less the SPIOER rates. 000- w 75 80 - Officiala - SPIOER difference Difference b for the machinery and equipment component of in- vestment since investment goods make up the major portion of producer durables. The official series for investment in machinery should be comprehensive with each individual product valued at its own price (unlike SPIOER's index for producer durables pro- duction, which is based on a sample). Before performing the comparison the investment series must be adjusted to a production basis. Machin- ery does not appear in the investment data as soon as it is produced. In addition, some allowance must be made for foreign trade. Domestically produced ma- chinery that is exported never appears in the invest- ment data. Likewise, imported machinery appears in the investment data, but is never reflected in the production data. Given the frequent delays in the construction indus- try, we assume that on average production or imports of machinery are reflected in investment after a year's lag. Implied Production t = Investment t+I � Net Imports t The investment series so adjusted is compared with the SPIOER producer durables series in figure 7." " Foreign trade in machinery and equipment is reported in Vneshnyaya torgovlya SSSR in current foreign trade rubles; in contrast the investment series is reported in constant estimate prices of 1969. The foreign trade data are adjusted in the following way. First, net imports of machinery and equipment are computed in current foreign trade rubles. Second, a price index for imports is derived by comparing the relative growth of two series for total imports�one in comparable prices and the other in current prices. This implicit price index is used to deflate machinery imports, even though it is bascd on all imports, including non-machinery pro- ducts. Hence some possible error is introduced by this procedure unless machinery prices have moved in the same pattern as all import prices. Finally, net imports of machinery and equipment in constant prices are adjusted to domestic prices by using a coeffi- cient of 0.978 estimated by Vladimir Treml for 1972. Although the assumptions used to make the foreign trade data comparable with the investment data may be tenuous, machinery imports are a small share of investment. 204 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 11 SPIOER and Official Industrial Indexes: Comparisons of Secular Growth Patterns a 1951-55 1956-60 1961-65 1966-70 1971-75 1976-80 Ferrous metals SPIOER Official 188 175 129 128 122 116 86 83 68 74 19 28 Fuels SPIOER Official 149 153 141 129 l 00 98 79 86 79 89 52 44 Electric power SPIOER Official 142 143 124 130 125 122 86 89 76 70 49 50 Chemicals and petrochemicals SPIOER Official 126 144 114 100 130 120 97 102 93 88 41 48 Wood, pulp, and paper SPIOER Official 211 151 166 142 74 91 83 100 74 95 �3 27 Construction materials SPIOER Official 196 169 184 169 68 88 71 83 68 72 22 24 Machinery SPIOER Official 128 135 105 115 99 100 92 94 105 94 72 66 Light industry SPIOER Official 196 192 121 108 49 41 136 134 51 72 49 53 Processed food SPIOER Official 173 159 142 125 115 114 100 94 66 86 12 28 Total industry SPIOER Official 150 151 122 120 97 99 93 97 87 86 50 51 a Each value is the ratio of the period average to the postwar average. 205 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 12 SPIOER and Official Industrial Indexes: Directional Changes in Growth From (1951-55) to (1956-60) From (1956-60) to (1961-65) From (1961-65) to (1966-70) From (1966-70) to (1971-75) From (1971-75) to (1976-80) Ferrous metals SPIOER Official - - - - - - - - - - Fuels SPIOER Official � � _ � � _ 0 + - - Electric power SPIOER Official - - + - - - - - - Chemicals and petrochemicals SPIOER Official � � + + - - - - - Wood, pulp, and paper SPIOER Official - - - - + + - - - - Construction materials SPIOER Official - + - - + - - - - Machinery SPIOER Official - - - - - - + - - Light industry SPIOER Official - - - - + + - - - - Processed food SPIOER Official - - - - - - - - - - Total industry SPIOER Official - - - - - - - - - - 206 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Figure 7 Comparison of Production of Producer Durables and Adjusted Investment Index: 1970=100 180 160 140 120 100 80 60 40 20 I 0 1950 55 I I 60 I I 1 I 65 I I ii 70 I Ii 75 ii 80 - Machinery investment - Producer durables The close correspondence between the two series over the postwar period suggests that the producer dura- bles sample is representative of the total output of this type of machinery. When examining growth rates instead of indexes, as shown in the tabulation below, the relationship between the two series does not appear quite as close: Average Annual Growth of Adjusted Machinery Investment and Producer Durables Percent Adjusted Machinery Investment SPIDER Producer Durables 1951-55 14.6 11.8 1956-60 10.0 12.4 1961-65 9.6 8.9 1966-70 7.7 7.8 1971-75 9.1 8.6 1976-79 5.2 6.3 1951-79 9.5 9.4 In some periods the two series diverge substantially in terms of average annual rates of growth. Both series grew at about the same rate from 1950 to 1979. The machinery investment series may also be susceptible to the effects of new-product pricing and hence disguised inflation. Thus, the close relationship could mean that the producer durables index has not successfully removed all traces of disguised inflation and has some upward bias. Sample Representativeness Sample Coverage. A statistical sample should at least include enough items to ensure that the characteris- tics of the sample approach those of the total. In 207 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 general, the larger the sample's share of the total, the greater the likelihood that its characteristics are similar to those of the full population.' Using the 1972 input-output table as a point of reference enables us to measure the sample coverage and to identify those areas of industry where a relatively small sample threatens the accuracy of the indexes. If we sum the value of all the products within each sector's sample for 1972 and compare this wit4 the reported GVO in the input-output table, we get a rough notion of the percentage of industrial output covered by SPIOER, at least for that year. The measure is rough because differences in accounting practices and pricing make the industrial sample and the input-output table incompatible in some respects. For example, the production of commodities pub- lished in physical units includes intraplant turnover, but the value of production as reported in the input- output table presumably removes intraplant turnover in measuring gross output." Production data ex- pressed as a CSA index and perhaps as a value series are also usually reported on an establishment basis, and the input-output data are compiled on a commod- ity basis. A commodity-based classification scheme rebases the secondary production of an enterprise to the industry to which it ostensibly should belong, but establishment-based classification makes no attempt at such a correction." Another important difference is the SPIOER sample's use of 1 July 1967 prices and the input-output table's use of 1972 prices. To the extent that there has been inflation�concealed or otherwise�our estimated sample coverage may be understated. 2' A large share�but less than 100 percent�does not ensure that the sample represents the total if the products included are atypical. For example, Soviet production data may be upward biased because the CSA publishes only data that reflect favorably on Soviet accomplishments. On the other hand, some published data under- state growth because the Soviets generally measure output in natural units, like the number of bulldozers. Such treatment fails to capture changes in product assortment and quality. Therefore, because of the peculiarities of Soviet data, a large sample share does not guarantee the representativeness of the sample. Narodnoye khozyaystvo v 1978 g, p. 580 and Treml, Gallik, Kostinsky, and Kruger, Structure, pp. 46-47. Also see the earlier discussion of gross output measures in this paper. Treml, Gallik, Kostinsky, and Kruger, Structure, pp. 123-146. In SPIOER's coverage of industrial production, 87 percent of the industrial sectors reported in the recon- structed 1972 input-output table have some form of representation in the sample (table 13). The machin- ery branch has the most sectors and also the most gaps in coverage, although the missing sectors are relatively unimportant. Of the represented sectors the median coverage is 71 percent with the degree of coverage ranging from 8 percent in one machinery sector to more than 100 percent in certain sectors in the construction materials, light industry, and proc- essed food branches.3' Coverage in four of 10 branches is more than 70 percent, and all but two have at least 50-percent coverage. The most restricted samples are found in nonferrous metals (29 percent) and chemicals (42 percent); statistics on production of nonferrous metals and many chemicals are considered classified by Soviet authorities and hence are not reported. Machinery coverage would have been low�about one-half�except that we added our estimates of military machinery to the value of the sample. Overall in this benchmark year the SPIOER sample ac- counted for about 60 percent of Soviet industrial production. A Rough Measure of Sample Representativeness. The fact that SPIOER product samples represent substan- tial shares of total output in 1972 does not guarantee that the samples are representative in terms of their growth. The best available benchmarks of representa- tiveness are the various input-output tables. One rough measure can be performed computing gross value of output in current rubles from the 1959, 1966, and 1972 input-output tables for 10 branches of 3' The sectors where this occurs are: logging (115 percent), cement (106 percent), concrete (106 percent), asbestos cement (118 percent), linen (159 percent), hosiery and knitwear (125 percent), flour and cereal (142 percent), and fruit and vegetables (155 percent). There are several possible explanations for the seeming anomaly. First the average wholesale prices used by SPIOER could be too high. Second, in some cases prices may have been reduced between 1967 and 1972. Third, different definitions of output and differences arising from the conflict between commodity versus establishment classifications also play a role. 208 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 13 Estimated Sample Coverage of SPIOER Indexes in 1972 Number of Sectors in Branch Number of Sectors With a Sample Minimum Sector Coverage (percent) Maximum Sector Coverage (percent) Branch Coverage a (percent) Ferrous metals b 5 4 70.5 98.0 78.6 Nonferrous metals 2 1 37.8 37.8 29.1 Fuels c 6 6 23.4 86.6 71.8 Electric power 1 1 89.3 89.3 89.3 Machinery 27 21 8.3 100.0 67.4 Chemicals and petrochemicals 10 9 34.8 100.0 42.2 Wood, pulp, and paper 6 5 47.2 114.9 70.4 Construction materials 8 8 14.3 118.5 65.7 Light industry 8 7 16.2 159.1 56.4 Processed food 10 10 17.0 155.1 55.1 Total industry 83 72 8.3 159.1 59.9 a Branch coverage is the sum of the value of sector samples expressed as a percent of the branch GVO. In estimating SPIOER's coverage we have relied on two decision rules to compute shares. First, if the sector is represented within the SPIOER sample by an official GVO index, we assume that is equivalent to 100-percent coverage, since the official production indexes presumably are based on full coverage. See Abraham S. Becker, Ruble Price Levels. Second, if the sample coverage computes to more than the sector GVO, we assumed sector coverage is 100 percent for estimating branch and industry coverage. b The coke products sectors of the ferrous metals branch is described by a proxy linked to the index for extraction of coking coal. In this tabulation the sample share for this sector is treated as zero. If the share were treated as complete coverage, branch coverage would increase from 78.6 percent to 88.6 percent. Two sector samples in the fuels branch-those for peat and oil shale-use an average unit value rather than a true unit price. In this tabulation the sample share is taken as zero, an obvious understate- ment. If the share were treated as 100 percent, the fuels branch sample share would only increase from 71.8 percent to 74.0 percent. industry (ferrous and nonferrous metallurgy are com- bined). These GVOs are then "deflated" to constant 1972 rubles by the published Soviet indexes of enter- prise wholesale prices. We realize that these indexes are not an adequate gauge of price movements. Nonetheless, analysis of their construction suggests they are most deficient in the machinery branch and less so elsewhere. Then revised branch indexes are constructed from the SPIOER data by using gross output weights in 1972 for the sectors, rather than value-added weights, to build synthetic branch GVO indexes in constant prices. Next, average annual rates of growth for the periods 1960-66 and 1967-72 are computed for both the deflated GVO branch indexes from the input-output table and the SPIOER indexes adjusted to a gross output basis. 209 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 14 Percent SPIOER and 1-0 GVO: Comparisons of Average Annual Growth Rates 1960-66 1967-72 Deflated 1-0 Values Revised SPIOER Deflated 1-0 Values Revised SPIOER Metallurgy 7.4 7.5 5.2 5.1 Fuels 4.2 5.9 7.2 4.8 Electric power 11.6 10.7 8.5 7.9 Machinery 17.0 7.0 10.5 7.4 Chemicals and petrochemicals 12.0 10.9 11.2 8.0 Wood, pulp, and paper 3.8 2.3 5.8 3.3 Construction materials 7.7 7.3 6.8 5.7 Light industry 5.9 3.6 7.2 5.2 Processed food 5.4 5.4 5.7 5.2 In 15 of the 18 comparisons in table 14, the SPIOER growth rate is less than the growth of deflated GVO from the input-output tables; in one case the rates are equal and in only two instances are SPIOER rates greater. The lower SPIOER rate is consistent with our under- standing of Soviet price indexes. Because official price indexes do not capture all of the real price inflation, deflation of GVOs in the input-output tables by the official price series does not remove all of the price inflation from measured real growth. We would there- fore expect SPIOER growth rates to be below those derived from input-output GV0s, as they generally are. While this does not prove that the sample is representative of all industrial output, it does suggest that any sampling errors are likely to produce a lower growth rate rather than a higher one. This is comfort- ing because the greatest threats to measurement errors are likely in the opposite direction. (See the following discussion in "Biases in the Quantity and Value Data.") Biases in the Basic Data Changes in the Material Intensity of Production. Only the 1972 input-output table is used in the SPIOER computations to estimate the output indexes for the branches of industry. This practice implicitly assumes that the ratio of value added to gross output for each sector remains approximately constant over the period. If this assumption is wildly unrealistic, the SPIOER indexes would fail to move in a manner representative of the movement of national industrial output. To avoid this strong assumption, one would need a highly disaggregated input-output table for every year, although only three-for 1959, 1966, and 1972-have been compiled thus far. Even these three tables cannot be easily used together because SPIOER is a constant price index and the input- output tables are in current rubles. Fortunately this work already has been partly done on a limited basis for 18 sectors in two companion studies by Vladimir Treml and Gene Gui11.32 By using these constant price tables for the three benchmark years- 1959, 1966, and 1972-it becomes possible to com- pare movements in gross output and value added. The "See Vladimir G. Treml, Price Indexes for Soviet I8-Sector Input- Output Tables for 1959-1975, Technical Note SSC-TN-5943-1, (Arlington, Virginia: SRI International, June 1978), for a deriva- tion of the price indexes. Also see Gene D. Guill, Deflation of the 18 Sector Soviet Input-Output Tables, Technical Note SSC-TN- 5943-4, (Arlington, Virginia: SRI International, August 1978), for the derivation of input-output tables for several years in 1970 producer prices. 210 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 15 Gross Output and Value Added in Input-Output Tables at Constant Prices (Average Annual Percentage Rate of Growth) Sector 1960-66 1967-72 Gross Output (percent) Value Added a (percent) Difference (percentage point) Gross Output (percent) Value Added a (percent) Difference (percentage point) Metallurgy 7.4 8.3 -0.9 5.7 3.3 2.4 Coal 0.8 -1.4 2.2 2.0 -1.0 3.0 Oil 8.6 9.8 -1.2 12.7 13.1 -0.4 Gas 17.8 17.8 0 5.6 4.9 0.7 Electric power 11.6 14.0 -2.4 8.3 9.1 -0.8 Machinery s13.1 12.0 1.1 10.2 12.3 -2.1 Chemicals and petrochemicals 11.8 12.5 -0.7 9.4 9.6 -0.2 Wood products 3.8 3.2 0.6 5.3 5.0 0.3 Paper 4.3 5.2 -0.9 11.7 10.9 0.8 Construction materials 7.7 9.2 -1.5 7.8 7.8 0 Light industry 5.7 6.0 -0.3 7.1 8.1 -1.0 Processed food b 4.8 NMF NMF 5.2 NMF NMF Industry without processed food 7.8 7.3 0.5 8.2 8.5 -0.3 NMF means no meaningful figure. a Including amortization deductions. b A comparison for processed food is not possible because of the negative value added in this sector owing to heavy state subsidies. results of this comparison (table 15) suggest that gross output does change, for the most part, in line with value added. In over two-thirds of the comparisons the differences in growth rates between gross output and value added are less than 1 percentage point. The cases with the largest divergence in growth rates are coal in both periods, electric power in 1960-66, and metallurgy and machinery in 1967-72. In general, value added tended to grow slightly slower than gross output in the early period and faster in the later period. These results indicate that the assumption of a con- stant ratio of value added to gross output should not bias the SPIOER indexes much as measures of value added. Moreover, in those instances of wide disagree- ment between the gross output and value-added growth in table 15, the explanation may lie in the unreliability of the price deflators used for machinery output (and input) and changes in product mix within input-output sectors. If subsectors within any of the 18 sectors have widely disparate gross output to value- added ratios, the growth of gross output for the full sector need not match that of value added. SPIOER partially circumvents the product mix problem by disaggregating industrial production to a more de- tailed level than represented in the 18-sector input- output tables used by Treml and Guill. The greater level of detail in SPIOER allows variations in the ratio of value added to gross output at the 18-sector level and freezes the ratio only at a more detailed sectoral breakdown. On balance, the effect on the SPIOER indexes of the inability to construct true indexes of value added-a problem that exists in the production indexes of many 211 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Western countries�remains unresolved. Much de- pends on the direction and degree of technological change. If materials use or intensity has generally declined over time, SPIOER's growth would be exces- sively slow. Increases in materials intensity would cause errors in the opposite direction. Biases in the Quantity and Value Data. While the SPIOER sample covers a large portion of Soviet industrial production in 1972, other sample properties could bias the synthetic indexes. The quantity series employed in samples of sector production on balance may understate growth. For example, a bulldozer in a given model category produced in 1950 is counted the same as a bulldozer produced in, for example, 1962 despite any model improvements that may have been introduced. Ideally, the SPIOER methodology should account for changes in average product quality, but this would require engineering studies of every product. Quantity series also do not measure changes in product mix, which could reduce the reliability of these series as measures of production. Returning to the earlier example, the capacity of the average bulldozer has fluctuated over time as the product mix has changed. As a result, the fixed price weight used for the sample becomes unrepresentative. If the Soviet Union is gradually moving toward higher capacity equipment, the sample price becomes lower than the true average in later years, higher in earlier years, and growth is understated. Similar biases could occur in other sectors as well. The magnitude of this quantity series bias depends on the nature of the product involved. Products that are less complex, more homogeneous, and less vulnerable to innovation, such as many industrial materials and basic consumer goods, probably are less vulnerable to this bias. Bias should be greatest in technically com- plex, heterogeneous products such as machinery. Some notion of the possible extent of the bias that might arise in the machinery branch from using fixed price weights can be obtained by drawing on a recent CIA study." This study has collected for several types " CIA, An Analysis of the Behavior of Soviet Machinery Prices, 1960-73, ER 79-10631, December 1979. of machinery produced during 1960-73 a sample of model numbers, prices, and physical specifications. The purpose of this study was to determine what price changes have occurred that cannot be explained by changes in product quality or mix." A result of this research was the derivation of price indexes for two types of machinery represented by quantity series in SPIOER�construction machinery and hoist-trans- port equipment (cranes). By using these price series to deflate the final demand component for these two sectors in the 1959, 1966, and 1972 input-output tables to 1972 producer prices, we derive series simi- lar conceptually to two quantity indexes in SPIOER, except that average unit prices are allowed to vary due to changes in product mix. Comparison of the growth rates of the series over the periods covered by the input-output table should give a rough indication in at least two quantity series of the scale of the bias that results from using fixed price weights. The results of this test shown in table 16 suggest that the SPIOER quantity series do tend to understate growth. Although the fixed price series grow more rapidly in the 1960-66 period than the variable price series, the downward bias becomes evident when examining 1967-72 and both periods combined. Over- all, the series with fixed price weights grow 1.1 and 0.4 percent less rapidly than the series with variable price weights for hoist-transport machinery and con- struction machinery, respectively. We have attempted to limit the effect of this bias on the machinery index by disaggregating the product sample as much as possible. Trucks, cars, and buses are disaggregated by model numbers, for example. By increasing the level of product detail in this way, the sample implicitly adjusts for changes in product as- sortment and partly for quality improvements. This approach cannot be followed for most sectors, howev- er, because the necessary production and price data are not available. 34 The cited study estimates regressions for each type of machinery covered. By regressing prices on physical parameters and time, it is possible to discover how prices have increased because of changes in product specifications and inflation. 212 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 16 Average Annual Percent Comparison of Growth of Output in Two Sectors Using Fixed and Variable Price Weights 1960-66 1967-72 1960-72 Hoist transport machinery Variable price weights a 8.4 9.5 8.9 Fixed price weights b 8.7 6.9 7.8 Construction machinery Variable price weights a 8.9 8.8 8.8 Fixed price weights b 10.3 6.2 8.4 a These series are derived from the deflated final demand of the respective sector from the input-output tables of 1959, 1966, and 1972. Because the CIA study has no price samples for 1966, the 1966 table in 1970 prices is used and then deflated to 1972 prices with the derived indexes. Deliveries to final demand in current prices are found in the following sources: 1959�Dimitri M. Gallik, Barry L. Kostinsky, and Vladimir G. Treml, Conversion of Soviet Input-Output Tables to Producers' Prices: The 1959 Reconstructed Table, FER-No. 6 (Washington, D.C.: US Department of Commerce, February 1975). 1966�Treml and Guilt, in Treml, Studies, pp. 197-281. 1972�Gallik, Guill, Kostinsky, and Treml, "The 1972 Input- Output Table," pp. 423-471. Prices: The price deflators are taken from CIA, An Analysis of the Behavior of Soviet Machinery Prices, 1960-73. b These series are derived from the SPIOER quantity series for these two sectors. Much more has been written about the distortions afflicting both types of value series�official ruble value series and GVO index series�the double-count- ing and disguised price inflation alluded to earlier. The effect of changes in double-counting is relatively easy to understand; the inflationary bias perhaps requires more discussion. Enterprise managers find it advantageous to boost prices to meet their performance targets. But it is difficult for managers to raise prices on standardized products since prices are controlled by the govern- ment. An exception is made, however, if the item can be considered a new product." Then an enterprise can charge a new-product price, which is deliberately set higher than the price of the old product to recapture research and development costs of the new product. Later the temporary new-product price gives way for " The new-product pricing phenomenon has been widely discussed in the literature. In particular see Abraham S. Becker, Ruble Price Levels; Joseph S. Berliner, The Innovation Decision in Soviet Industry; Padma Desai, "On Reconstructing Price, Output and Value-Added Indexes in Postwar Soviet Industry and Its Branches," pp. 55-77; Gregory Grossman, "Price Control, Incen- tives and Innovation in the Soviet Economy," Alan Abouchar, ed., The Socialist Price Mechanism (Durham, N. C.: Duke University Press, 1977); and CIA, An Analysis of the Behavior of Soviet Machinery Prices, 1960-73. 213 93-892 0 - 82 - 15 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 a permanent price. Because innovation is risky given the incentives confronting the Soviet manager, specifi- cations of old products often change only slightly. This is enough, however, to allow him to charge a substantially higher price for this "new" product and to lead him to halt production of the older and cheaper model. Purchasers have little choice but to accept the more expensive item. As a consequence, value of production has increased more than could be justified by the degree of product change. An inflationary bias is also introduced into the value series by the way constant or, in Soviet terminology, comparable prices (sopostavimye tseni) are set. For items in production before the base year for the comparable prices, the prices in effect in the base year are used in the series. For products introduced subse- quently, the first permanent price is the comparable price. The output series therefore reflects a mixture of constant and current prices; the presence of price inflation will then bias the output index upward. New-product pricing represents the serious measure- ment problem in industries where products are hetero- geneous, where value measures would provide the only meaningful measure of output, and where many op- portunities for innovation exist and product complex- ity makes it difficult to distinguish between real and cosmetic improvements. Although these features exist to some degree in all industrial branches, they are most characteristic of machinery and chemicals. The study already referred to (An Analysis of the Behavior of Soviet Machinery Prices, 1960-73), can be used to gain some notion of the possible impact of disguised inflation on the value series. One type of machinery analyzed in that study is machine tools, for which SPIOER relies on the official value series in the Narkhoz. According to the value series, machine tool output in 1970 was 2.33 times the 1960 level�an average annual increase of 8.8 percent. The machin- ery price study concludes, however, that machine tool prices in 1970 were 28.7 percent above the 1960 level after allowance for changes in product characteristics. Deflating the value series by this price increase suggests that output in 1970 was only 181 percent above 1960 or that machine tool output increased at an average rate of only 6.1 percent per year, 2.7 percentage points per year less than the value series used by SPIOER. If the wholesale price index derived in that paper based on a sample of several types of machinery is representative of all of the value series incorporated in SPIOER, the hidden price changes incorporated in the value series and hence wrongly counted as real growth, would be significant: Implied Price Inflation Average Annual Percent in Machinery 1961-66 1967-70 1971-73 2.7 5.7 �1.6 This would suggest that in the 1960s the value series are upward biased and that at least in the early 1970s the value series are downward biased. Over the entire 13-year period, the implicit rate of inflation in the value series would average 2.6 percent per year. Not all value series are subject to a large upward bias arising from price inflation. In some of the rapidly developing industries like precision instruments and electronics, prices have been reduced repeatedly to prevent the excessive accumulation of profits. Because those industries are in a relatively early phase of development, expansion of output generates substan- tial economies of scale and cost savings. In such cases the amount of disguised inflation would be much smaller than in more developed branches that are also represented by value series. The relative importance of this kind of sample bias in the branch indexes can be determined from the composition of the sample in each branch. Six of the branch indexes are completely based upon quantity series. Distortions in the value series reported by the CSA could carry over to the synthetic indexes for the wood, pulp, and paper industry, light industry, chemi- cals, and machinery. The tabulation below indicates 214 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 that machinery is the branch most affected by the value series. The value series are used to measure changes in only about one-fifth of industrial production. Because quantity series and value series are not evenly distributed among the branches, indexes dominated by value series suffer most from the distortion caused by disguised inflation. Shares in 1970 of Value Added Percent Branch Quantity Value Series Series Chemicals and petrochemicals 95 Wood, pulp, and paper 85 Light industry 65 5 15 35 Machinery Producer durables 41 59 Consumer durables 27 73 The Importance of Disguised Inflation. Considerable attention has been devoted to the possibility of hidden inflation in the value series included in the SPIOER samples. The major industrial branches in which value series are used to measure production are listed in table 17. The branch samples are divided into quantity or official value series, and two separate indexes are calculated for each branch�one for prod- ucts reported in physical units and one for products reported by value. (Value-added weights are used to aggregate individual series.) The table compares the growth rates for these components of the branch indexes in which value series are important. The value series generally grow substantially faster than the physical series. This does not necessarily mean that the differences are caused by disguised inflation of the value series. For example, in the wood, pulp, and paper industry the rapidly growing value series is furniture. While new-product pricing un- doubtedly is a problem in the furniture industry, furniture output has been a stellar performer in a branch that otherwise is nearly stagnant. Similarly, it is not surprising that sewn goods�measured in rubles�is one of the fastest growing components of light industry; in later phases of development the processing of fabrics becomes more important than the manufacture of the fabrics themselves. The results for consumer durables are surprising. Value series comprise a larger share of the sample than in any other part of SPIOER; ironically, the value series increase more rapidly than the quantity series only in three of the six periods. During the entire 29-year period, the value series increased only 0.9 percentage points per year faster. The Producer durables comparison is more troublesome. Between 1950 and 1979 the value series in the producer durables sample increased on average nearly 4 per- centage points faster than the quantity subsample� suggesting a substantial upward bias in the official value series. Not all of the discrepancy in the machinery series can be attributed to index distortions, however. The quan- tity series do include machinery sectors that are actually growing more slowly than sectors represented by value series. For example, transport machinery�a quantity series�traditionally grows slowly once a nation's transportation infrastructure is in place, and instruments and computers�a value series�has been a fast growing sector since 1960. We can test this hypothesis in a rough way. The Soviets publish GVO indexes for subgroups of machinery at a level of detail that is unavailable in most of the other industrial branches. The official GVO machinery branch indexes for the years 1960, 1965, 1970, 1975, and 1980 were used to estimate subsample growth based strictly on official GVO data. These component in- dexes were then classified according to whether they were predominantly represented by quantity or value series in the SPIOER machinery sample. According to the rates of growth shown in table 18, the branch subsample represented by quantity series is growing about 2 percentage points less rapidly than the sub- sample described by value series. We conclude, there- fore, that the machinery represented by quantity data are less dynamic machinery sectors. 215 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 17 Comparison of Growth of Quantity and Value Series Within Branches of Industry Average Annual Percent 1951-55 1956-60 1961-65 1966-70 1971-75 1976-79 Wood, pulp, and paper Quantity series 7.0 5.0 1.8 1.9 1.3 -2.6 Official value series 18.1 17.8 10.4 9.1 8.8 4.3 Chemicals and petrochemicals Quantity series 11.4 10.2 11.8 8.9 8.4 3.3 Official value series 20.8 19.4 16.1 9.7 11.7 6.0 Light industry Quantity series 9.3 5.9 3.2 4.9 2.3 1.7 Official value series 13.4 7.6 1.2 12.2 3.5 4.5 Consumer durables Quantity series 17.7 11.5 9.4 7.6 14.8 2.1 Official value series 17.7 9.9 9.7 12.9 10.5 8.4 Producer durables Quantity series 10.8 12.2 6.8 5.5 5.1 2.2 Official value series 12.9 12.5 10.9 10.0 11.0 8.4 Whatever the reason, a wide disparity in growth rates clearly exists between the two types of subsamples in the producer durables index. How the underlying biases might affect the overall machinery index and the industrial index can only be judged by some fairly arbitrary sensitivity testing (table 19). Six different assumptions regarding the bias in the producer durables sample are tested. In each case, we assume that the SPIOER growth rates are biased for specific reasons and reestimate growth taking into account the assumed adjustments. The cases tested allow for the downward biases of the quantity series, the upward biases of the value series, and combina- tions of both. The alternative assumptions are: I. Real growth of the value series is the same as that of the quantity sample. 2. Real growth of the value series is 2 percentage points higher than that of the quantity series. 3. Real growth of the quantity series is 1 percentage point higher than the measured rate and equals the real growth of the value series. 4. Inflation in the value series is 3 percent per year. 5. The downward bias in the quantity series is 1 percentage point per year, and the upward bias in value series is 3 percentage points per year. 6. The downward bias in the quantity series is 1 percentage point per year, and real growth in the value series is 2 percentage points per year higher than the adjusted growth in the quantity series. The impact of possible biases in the producer durables sample weakens considerably at higher levels of ag- gregation. The largest discrepancy between SPIOER growth and growth of hybrid indexes (1951-79) is 2.2 percentage points for producer durables, 1.2 percent- age points for machinery, and just 0.3 percentage point for total industry. Moreover, in this case ma- chinery growth is unrealistically low compared with that in other industrial sectors. Assumptions that give a more realistic machinery growth suggest that the error introduced into SPIOER indexes by any bias in the machinery index is no larger than half that in the worst case. 216 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 18 Growth of Machinery Samples Estimated From Official GVO Data Average Annual Percent 1976-80 1961-65 1966-70 1971-75 Quantity series subsample a 11.3 9.1 8.3 5.0 Electrotechnical industry 10.1 8.4 6.7 5.6 Energy machinebuilding 13.7 9.7 8.4 4.5 Metallurgical, mining, and other machinery 9.5 6.8 7.1 3.2 Hoist transport machinery 15.1 8.4 7.4 4.1 Construction machinery 13.1 11.3 9.0 4.4 4.1 7.7 Railroad machinery 8.7 7.3 6.0 Automotive machinery 11.1 12.5 13.0 Value series subsample a 11.4 '1.4 10.8 7.8 Machine tools 12.9 9.7 10.0 8.1 Instruments 16.2 17.8 18.5 14.0 6.8 7.3 5.1 Chemical machinery 16.1 10.3 9.2 Logging, pulp, and paper machinery 11.6 15.2 10.8 Light industry and food machinery 10.2 8.6 8.9 Metallic items 8.2 11.6 8.9 5.0 5.5 6.1 Metallic structurals 7.6 10.7 9.9 Machinery repair 11.4 9.3 8.7 Mixed quantity and value subsample Tractors and Agricultural machinery 13.3 8.7 11.2 6.1 a Because of difficulties in deriving weights, a simple average of the indexes is used to aggregate the subbranch elements. The average annual rates of growth are computed from the average indexes. 217 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 19 Average Annual Percent Growth of Soviet Industry Under Different Assumptions of Bias in the SPIDER Producer Durables Sample SPIOER Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Producer durables 1951-55 11.8 10.8 11.8 11.8 10.3 10.6 13.1 1956-60 12.4 12.2 13.3 13.2 10.7 11.0 14.3 1961-65 8.9 6.8 7.9 7.8 7.4 7.9 9.0 1966-70 7.8 5.5 6.6 6.5 6.3 6.8 7.7 1971-75 8.6 5.1 6.3 6.1 6.8 7.2 7.4 1976-79 6.3 2.2 3.4 3.2 3.3 4.6 4.4 1951-79 9.4 7.2 8.3 8.2 7.7 8.1 9.4 Total machinery 1951-55 9.6 9.4 9.7 9.7 9.1 9.2 10.1 1956-60 7.9 8.3 8.6 8.6 7.3 7.4 8.8 1961-65 7.4 6.2 6.8 6.8 6.6 6.8 7.5 1966-70 6.9 5.4 6.2 6.1 6.0 6.3 6.9 1971-75 7.9 5.6 6.1 6.2 6.7 7.0 7.1 1976-79 5.6 2.8 3.6 3.5 4.1 4.4 4.3 1951-79 7.6 6.4 7.0 6.9 6.7 6.9 7.5 Total industry 1951-55 10.2 10.1 10.3 10.3 10.0 10.1 10.4 1956-60 8.3 8.9 8.8 8.8 8.3 8.3 10.5 1961-65 6.6 6.6 6.9 6.8 6.8 6.9 5.5 1966-70 6.3 5.9 6.1 6.1 6.0 6.1 6.3 1971-75 5.9 5.7 6.0 6.0 6.1 6.2 6.3 1976-79 3.6 2.8 3.1 3.1 3.4 3.5 3.4 1951-79 6.9 6.7 7.0 6.9 6.9 6.9 7.2 218 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix A Table A-1 The SPIOER Sample: Products, Units, and Key Sources Ferrous metals branch Ferrous ores sector Manganese ore Tons Narkhoz Iron ore Tons Narkhoz Ferrous metals sector Cast iron Tons Narkhoz Rails and rail accessories Tons Narkhoz Wire rod Tons Narkhoz Plain wire Tons Narkhoz Seamless pipe and tube Tons Narkhoz Welded pipe and tube Tons Narkhoz Heavy section pipe and tube Tons Narkhoz Light section pipe and tube Tons Narkhoz Steel plate Tons Narkhoz Hot rolled sheet Tons Narkhoz Cold rolled sheet Electrical sheet Tons Tons Narkhoz Narkhoz Tinplate Tons Narkhoz Galvanized sheet Tons Narkhoz Products for reprocessing Tons Narkhoz Coke products sector Coke products (coking coal used as proxy) Tons Narkhoz Refractory materials sector Fire clay Dinas Tons Narkhoz, Estimate Tons Narkhoz, Estimate Magnesite and chrome magnesite items Tons Narkhoz, Estimate Magnesite powder/metallurgical Tons Narkhoz, Estimate Nonferrous metals branch Nonferrous metals sector Copper Tons Estimate Lead Tons Estimate Zinc Tons Estimate Tin Tons Estimate Aluminum Tons Estimate Magnesium Tons Estimate Titanium Tons Estimate Nickel Tons Estimate Antimony Tons Estimate 219 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) The SPIOER Sample: Products, Units, and Key Sources Mercury Ton Estimate Cadmium Tons Estimate Tungsten (60%w03) Tons Estimate Molybdenum Tons Estimate Fuels branch Coal sector Coking coal Tons Narkhoz Lignite Tons Narkhoz Noncoking hard coal Tons Narkhoz Oil extraction sector Oil (including gas condensate) Tons Narkhoz Oil refining sector Refined products Tons Estimate Gas sector Natural gas from wells Cubic meter Narkhoz, Journals, Estimate Asociated natural gas Cubic meter Narkhoz, Journals, Estimate Peat sector Peat Tons of standard fuel Narkhoz Oil shales sector Oil shale Tons of standard fuel Narkhoz Electric power branch Electric power sector Electric power distributed from busbars Kilowatt-hours Narkhoz Machinery branch Energy and power machinery sector Steam boilers (high capacity) Steam boilers (medium capacity) Steam boilers (low capacity) Tons/hours Narkhoz, Estimate Tons/hours Narkhoz, Estimate Tons/hours Estimate Steam and gas turbines Kilowatt Narkhoz, Estimate Hydraulic turbines Kilowatt Narkhoz, Estimate Electrotechnical machinery and equipment sector Generators (steam and gas turbines) Kilowatt Narkhoz, Estimate Generators hydraulic turbines Kilowatt Narkhoz, Estimate Electric motors over 100 kilowatt Kilowatt Narkhoz Power transformers Kilowatt-amps Electric bulbs Units Narkhoz Machine tools sector Metal cutting machine tools Rubles Narkhoz Forge presses sector Forge press machine tools Rubles Narkhoz 220 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) Precision instruments sector Instruments of time Rubles Narkhoz Other instruments and computers Rubles Narkhoz Metallurgical and mining machinery and equipment sector Metallurgy machinery and equipment except rolling mills Rolling mill equipment Coal combines Tons Narkhoz Tons Narkhoz Units Narkhoz Coal cutting machines Units Narkhoz Mine loading machines Units Narkhoz Electric mine locomotives Units Narkhoz Petroleum equipment/refinery Tons Narkhoz, Estimate Deep-well pumps Units Narkhoz Turbodrills Units Narkhoz Pumps and compressors sector Refrigerators Units Narkhoz Chemical equipment Rubles Narkhoz Log and paper machinery and equipment sector Log and paper machinery and equipment Light-industry machinery and equipment sector Light-industry machinery and equipment Food-industry machinery and equipment sector Index Narkhoz Rubles Narkhoz Food-industry machinery and equipment Rubles Narkhoz Printing machinery and equipment sector Printing-industry machinery and equipment Rubles Narkhoz Hoist-transport equipment sector Railroad cranes Units Narkhoz Truck cranes Units Narkhoz Tower cranes. Units Narkhoz Pneumatic tire cranes Units Narkhoz Electric bridge cranes Units Narkhoz Elevators Units Narkhoz Construction machinery and equipment sector Excavators/multibucket 0.15- to 0.20-cubic-meter single-bucket excavators Units Narkhoz, Estimate Units Narkhoz, Estimate 0.25- to 0.30-cubic-meter single-bucket excavators 0.35- to 0.80-cubic-meter single-bucket excavators Units Units Narkhoz, Estimate Narkhoz, Estimate 1- to I.25-cubic-meter single-bucket excavators Units Narkhoz, Estimate 1.4- to 2.5-cubic-meter single-bucket excavators Units Narkhoz, Estimate 3- to 8-cubic-meter single-bucket excavators 10 and more single-bucket excavators Units Units Narkhoz, Estimate Narkhoz, Estimate Bulldozers Units Narkhoz Scrapers Units Narkhoz Motor graders Units Narkhoz 221 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) The SPIOER Sample: Products, Units, and Key Sources Transportation, machinery and equipment sector Reefers, mainline freight Box cars, mainline freight Units Units Estimate Estimate Flat cars, mainline freight Gondola cars, mainline freight Tank cars, mainline freight Cement cars, mainline freight Units Units Units Units Estimate Estimate Narkhoz Estimate TE-1 diesel locomotives TE-2 diesel locomotives Units Units Estimate Estimate TE-3, -7, -10, -30 electric diesel TE-4 diesel locomotives Units Units Estimate Estimate TE-50,TEP-60, 1E-40 electric diesel Units Estimate TGP-50,TG-102, I E-106 diesel hydraulic G-1 /GT-101/ gas turbines VL-22m, direct current Units Units Units Estimate Estimate Estimate VL-8, -10, T-8 direct current Units Estimate VL-23 electric locomotives Units Estimate N-0 electric locomotives Units Estimate N-8 electric locomotives Units Estimate N-60 electric locomotives VL alternating current Units Units Estimate Estimate L steam locomotives Units Estimate Sum steam locomotives Units Estimate SO steam locomotives Units Estimate LV steam locomotives Units Estimate P 36 steam locomotives Units Estimate Railroad passenger cars Units Narkhoz Trolley cars Units Narkhoz Subway cars Units Narkhoz Civilian shipbuilding Units Estimate by type Civilian aircraft Units Estimate by type Automobiles sector Motorcycles Units Narkhoz, Estimate Moped Units Narkhoz, Estimate Bicycles Units Narkhoz, Estimate Motor scooters Units Narkhoz, Estimate Consumer autos Units Estimate Consumer auto prices Index Estimate Cars Moslcvich-400 sedan Units Moslcvich cabriolet model Moslcvich station wagon Units Units Estimate Estimate Moslcvich 2136, 2138, 2140, IZH-2125 Units Estimate 222 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) Moskvich 423 and 424 Units Estimate Zil limousine Units Estimate Zim sedan Units Estimate Gaz-67 jeep Units Estimate Uaz-469 jeeps Units Estimate Pobeda Units Estimate Gaz-21, 24/volga Units Estimate Zaz-965, 966, 968, 968a Gaz-13,14/chayka Units Estimate Units Estimate Vaz-2103, 2102, 2106, NIVA-2121 Trucks Units Estimate Vaz-21011 Units Estimate Gaz-51 Units Estimate Gaz-63 Units Estimate Gaz-53f, 53a, 66, 52 Units Gaz-93 Units Estimate Estimate Zit-157,157k Units Estimate Zit-164,164a Units Estimate Zi1-150 Units Estimate Zit-151 Units Estimate Zi1-585 Units Estimate Ural zis-335, 355m, 356, 358, 375, 37 Units Estimate Zi1-130, 131 Units Estimate Yaaz-200, 210, 214, 219, 221, 22 Kraz-214, 219, 221, 222, 255, 257 Units Units Estimate Estimate Maz-200, 205 Maz-500-504a, 509, 514, 516 Units Estimate Units Estimate Maz-525 Units Estimate Belaz-528, 529, 530, 531, 540, 548, 54 Moaz-542, 546, 522 Units Units Estimate Estimate Trucks (continued) Kaz-120 Units Estimate Kaz-585 and B, 585 and V Units Estimate Kaz-602, 606, 608, 608B Units Estimate Kaz-600 and A, 600B and V Gaz-AA Units Units Estimate Estimate Ural-Zi1-5/353, 355M and 356 Moskvich-430, 432 Units Units Estimate Estimate Uaz-450, 451, 452 Kamaz-5320, 5410 Units Units Estimate Estimate Abz-50 and miscellaneous Units Estimate Kaz-120 Units Estimate Kaz-585 and B, 585 and V Units Estimate 223 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) The SPIOER Sample: Products, Units, and Key Sources Kaz-602, 606, 608, 608B Units Estimate Kaz-600 and A, 600B and V Gaz-AA Units Units Estimate Estimate Ural-Zil-5/353, 355M and 356 Units Estimate Moskvich-430, 432 Units Estimate Uaz-450, 451, 452 Kamaz-5320, 5410 Units Units Estimate Estimate Abz-50 and miscellaneous Units Estimate Buses Kavz-651, 685 Units Estimate Paz-651, 652, 652B, 672 Zil-115, 118, 127, 155, 158 Units Units Estimate Estimate Ta-6 Units Estimate Laz-695, 695E Laz-698, 699, 699A, 697 Units Units Estimate Estimate Raf-251, 976, 977V, 977D Liaz-677 Units Units Estimate Estimate Trolley buses Units Estimate Automotive spare parts Rubles Estimate Agricultural machinery and equipment sector Agricultural machinery Tracklaying tractors Rubles Units Narkhoz Estimate by model Wheeled tractors Other machinery sector Units Estimate by model Tovari series Rubles Narkhoz Household chemicals deduction Index Narkhoz Furniture deduction Rubles Narkhoz Sanitary engineering products sector Bath water heaters Units Narkhoz, Estimate Enameled iron bathtubs Units Narkhoz, Estimate Heating boilers Units Narkhoz, Estimate Heating radiators Units Narkhoz, Estimate Sewer pipe and fittings Standard kilometer Narkhoz, Estimate Other metalwares sector Other metalwares Index Narkhoz Metallic structurals sector Metal structurals Index Narkhoz Machinery repair sector Machinery repair Index Narkhoz Chemicals and petrochemicals branch Mineral chemicals sector Mineral chemicals Index Narkhoz Basic chemicals sector 224 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) Nitrogen fertilizer Tons Narkhoz Phosphorite fertilizer Tons Narkhoz Phosphorous fertilizer Tons Narkhoz Potassium fertilizer Tons Narkhoz Sulfuric acid Tons Narkhoz Soda ash (95 percent) Caustic soda Tons Narkhoz Tons Narkhoz Anilyne dye products sector Synthetic dyes Tons CMEA Handbook Synthetic resins and plastics sector Plastics and resins Tons Narkhoz Synthetic fibers sector Chemical fibers and knits Tons Narkhoz Organic synthetic products sector Ethyl alcohol (nonfood based) Gallon Estimate Synthetic ammonia Benzol Tons CMEA Handbook Tons CMEA Handbook Chlorine Tons Estimate Phenol Tons CMEA Handbook Paints and lacquers sector Dry zinc whites Tons Estimate Enamels and primers Tons Estimate Litharge and red lead Tons Estimate Natural drying oil Tons Estimate Nitrocellulose varnish and solvents Tons Estimate Oil varnishes and siccatives Tons Estimate Oksol drying oil Rubber products sector Tons Estimate Motor vehicle tires Units Narkhoz Synthetic rubber sector Synthetic rubber Wood, pulp, and paper products branch Tons Narkhoz Logging sector F u wood Industrial logs Cubic meter Narkhoz Cubic meter Narkhoz Sawing and woodworking sector Plywood Cubic meter Narkhoz Lumber Cubic meter Narkhoz Furniture sector Furniture rubles Narkhoz Pulp and paper sector Newsprint Tons Narkhoz, Estimate Wrapping and packing Tons Narkhoz, Estimate 225 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) The SPIOER Sample: Products, Units, and Key Sources Printing Tons Narkhoz, Estimate Writing paper Tons Narkhoz, Estimate Sacking Tons Narkhoz, Estimate Offset printing Cover paper Tons Narkhoz, Estimate Tons Narkhoz, Estimate Winding Tons Narkhoz, Estimate Deep printing Tons Narkhoz, Estimate Lithographic Cartographic Tons Narkhoz, Estimate Tons Narkhoz, Estimate Cable insulation Tons Narkhoz, Estimate Capacitor Tons Narkhoz, Estimate Waxing paper Tons Narkhoz, Estimate Other paper products Paperboard Tons Narkhoz, Estimate Tons Narkhoz, Estimate Wood chemicals sector Oleoresin and rosin Tons Estimate Construction materials branch Cement sector Portland cement�homogeneous Tons Journals, Narkhoz, Estimate Portland cement�mix adjustment Index Journals, Narkhoz, Estimate Slag portland cement Tons Journals, Narkhoz, Estimate Slag cement�mix adjustment Index Journals, Narkhoz, Estimate Pozzolana portland cement Tons Journals, Narkhoz, Estimate Pozzolana cement�mix adjustment Index Journals, Narkhoz, Estimate Decorative cement Tons Journals, Narkhoz, Estimate Tamponage cement Tons Journals, Narkhoz, Estimate Unallocated cement Tons Journals, Narkhoz, Estimate Portland cement�Mark 200 Tons Journals, Narkhoz, Estimate Portland cement�Mark 300 Tons Journals, Narkhoz, Estimate Portland cement�Mark 400 Tons Journals, Narkhoz, Estimate Portland cement�Mark 500 Tons Journals, Narkhoz, Estimate Portland cement�Mark 600 Tons Journals, Narkhoz, Estimate 226 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) Marked, nonportland cement Tons Journals, Narkhoz, Estimate Nonportland�mix adjustment Tons Journals, Narkhoz, Estimate Unmarked cement Tons Journals, Narkhoz, Estimate Concrete sector Precast concrete Cubic meter Estimate, Narkhoz Prestressed concrete Cubic meter Narkhoz Wall materials sector Roofing tile Square meter Narkhoz Construction brick Standard unit Narkhoz Dimension and fieldstone Standard unit Narkhoz Concrete and silicate wall blocks Standard unit Narkhoz, Estimate Other wall materials Standard unit Narkhoz, Estimate Asbestos cement sector Asbestos cement shingle Standard unit Narkhoz Asbestos cement pipe Standard kilometer Estimate, Republic Narkhoz Roofing material sector Soft roofing Square meter Narkhoz Construction ceramics sector Ceramic tiles-facing and floors Square meter Narkhoz, Estimate Ceramic sewer pipe Tons Estimate, Journals Other materials for construction sector Construction lime Tons Estimate, Republic Narkhoz Gypsum Tons Estimate, Republic Narkhoz Mineral wool insulation Cubic meter Journals, Estimate, Repub- lic Narkhoz Rock products Cubic meter Narkhoz Glass and porcelain sector Window glass Square meter Narkhoz Polished glass Square meter Journals, Estimate Light-industry branch Cotton fabric sector Cotton cloth Square meter Narkhoz Silk fabric sector Silk cloth Square meter Narkhoz Wool fabric sector Wool cloth Carpeting Square meter Narkhoz Square meter Narkhoz Linen fabric sector Linen cloth Square meter Narkhoz Hosiery and knitwear sector Knit outerwear Pieces Narkhoz 227 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) The SPIOER Sample: Products, Units, and Key Sources Knit underwear Pieces Narkhoz Hosiery Pairs Narkhoz Sewn goods sector Sewn goods Rubles Narkhoz Other light-industry sector Leather footwear Pairs Narkhoz Rubber footwear Pairs Narkhoz Felt footwear Pairs Narkhoz Processed food branch Fish products sector Canned fish Standard Can Narkhoz Gross fish Tons Narkhoz Meat products sector Mutton Tons Narkhoz Pork Tons Narkhoz Beef and veal Poultry Tons Tons Narkhoz Narkhoz Other meat Tons Narkhoz Dairy products sector Canned milk Standard Can Narkhoz Whole milk Tons Narkhoz Butter Tons Narkhoz Cheese Tons Narkhoz, Estimate Sugar sector Refined sugar Net granular sugar Tons Tons Narkhoz Narkhoz, Estimate 228 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) Flour and cereal sector Macaroni products Tons Narkhoz Flour Tons Narkhoz Flour quality Bread products sector Index Estimate Bread products Confectionary products sector Tons Estimate Confectionary goods Tons Narkhoz Vegetable oils sector Net vegetable oil Tons Narkhoz, Estimate Margarine products Tons Narkhoz Fruit and vegetable products sector Canned juice Standard can Narkhoz Canned fruits Standard can Narkhoz Canned meat Standard can Narkhoz Canned vegetables Standard can Narkhoz Canned tomatoes Standard can Narkhoz Other canned goods Standard can Narkhoz Other food sector Soap Tons Narkhoz Champagne Bottles Estimate Vodka and vodka products Dekaliter Estimate, Republic Handbooks Beer Cigarettes Dekaliter Narkhoz 100 item CMEA Handbook Wine Dekaliter Narkhoz, Estimate 229 93-892 0 - 82 - 16 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 Gross Sector Output Indexes: Ferrous and Nonferrous Metals Ferrous Metals Nonferrous Metals Ferrous Ores Ferrous Metals Coke Products Refractory 1950 23.35 21.00 31.37 42.80 19.01 1951 26.93 23.84 33.10 46.23 21.54 1952 30.84 27.28 35.51 51.06 24.24 1953 34.42 29.90 37.71 55.17 27.03 1954 36.45 32.79 42.96 59.03 29.58 1955 40.09 36.22 47.17 63.13 34.72 1956 43.21 39.03 50.34 66.08 36.81 1957 46.38 41.24 53.12 68.92 38.88 1958 48.75 44.29 57.28 71.31 41.04 1959 51.34 48.71 61.16 76.54 44.38 1960 57.25 52.68 66.86 81.70 48.37 1961 62.73 57.42 68.22 85.65 52.42 1962 68.15 61.94 71.27 89.52 57.07 1963 72.80 65.75 77.10 91.19 61.53 1964 77.28 71.04 81.07 93.88 65.21 1965 81.47 76.05 84.32 95.98 69.88 1966 84.77 81.56 86.49 98.92 76.69 1967 87.51 87.03 89.57 100.12 83.50 1968 90.30 91.46 93.74 100.46 90.17 1969 94.57 94.48 97.85 99.42 94.66 1970 100.00 100.00 100.00 100.00 100.00 1971 103.42 104.09 102.67 100.66 107.02 1972 106.54 108.01 103.14 100.38 112.72 1973 110.83 112.59 105.24 102.58 119.56 1974 114.62 117.93 106.51 104.65 126.92 1975 119.56 123.39 109.85 106.64 132.89 1976 122.74 126.73 112.99 108.05 137.08 1977 123.03 127.93 113.07 107.28 141.26 1978 125.74 131.30 110.43 105.69 145.90 1979 125.63 131.35 110.92 106.33 150.22 230 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Fuels and Electric Power Fuels Electric Power Coal Oil Extraction Oil Refining Gas Peat Oil Shales 1950 39.47 10.73 13.32 2.91 83.62 14.77 12.48 1951 42.75 11.97 14.91 3.16 92.09 18.18 14.20 1952 45.55 13.40 16.69 3.23 86.44 20.45 16.25 1953 48.08 14.95 18.68 3.47 89.27 23.86 18.33 1954 52.37 16.79 21.09 3.79 104.52 27.27 20.49 1955 58.97 20.05 23.55 4.54 117.51 37.50 23.10 1956 64.56 23.74 28.63 6.10 103.95 39.77 26.03 1957 69.57 27.86 32.95 9.39 127.12 42.05 28.51 - 1958 74.62 32.07 36.24 14.19 119.21 51.14 32.00 1959 76.88 36.70 40.68 17.88 129.94 52.27 35.97 1960 78.83 41.88 45.16 22.89 115.25 54.55 39.65 1961 78.91 47.04 49.41 29.80 110.17 59.09 44.46 1962 80.91 52.75 55.23 37.14 72.88 65.91 50.16 1963 83.38 58.37 60.79 45.38 122.60 73.86 55.80 1964 86.70 63.34 64.43 54.85 125.42 80.68 62.03 1965 90.52 68.80 68.83 64.50 96.05 84.09 68.26 1966 92.35 75.10 74.11 72.22 137.85 85.23 73.48 1967 94.49 81.60 80.89 1954. 126.55 85.23 79.13 1968 95.26 87.57 86.44 85.43 103.39 86.36 86.09 1969 97.74 93.01 92.11 91.50 94.35 90.91 92.90 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 102.54 106.81 106.78 107.30 96.61 104.55 108.12 1972 104.73 113.43 115.38 111.84 111.30 113.64 115.80 1973 106.87 121.53 124.11 119.38 108.47 117.05 123.62 1974 109.46 130.00 133.23 131.60 75.71 121.59 131.88 1975 112.31 139.02 141.16 146.14 104.52 122.73 140.58 1976 114.33 147.20 144.73 162.14 63.84 125.00 150.29 1977 115.77 154.60 152.66 174.80 79.10 129.55 155.65 1978 115.76 161.89 161.78 188.03 51.98 131.82 162.90 1979 115.32 165.87 168.52 205.41 76.84 134.09 167.68 231 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Machinery Energy and Power Electrotechnical Machinery Machinery and Equipment Machine Tools Forge Presses Precision Instruments Metallurgical and Mining Machinery and Equipment 1950 16.97 14.42 9.68 6.46 2.62 42.53 1951 20.57 17.43 11.56 8.62 3.34 44.58 1952 26.51 18.93 13.80 11.46 4.24 51.95 1953 35.04 20.96 16.48 15.24 5.38 59.12 1954 39.87 22.16 19.68 20.28 6.80 57.02 1955 46.71 25.32 23.52 27.40 8.71 57.22 1956 47.51 28.72 26.50 31.22 11.24 60.28 1957 44.76 32.64 29.87 35.57 14.50 62.75 1958 48.38 35.59 33.66 40.53 18.71 69.93 1959 52.33 41.74 37.94 46.18 22.28 76.72 1960 62.45 47.57 42.84 52.44 26.51 80.61 1961 72.90 53.81 49.80 57.32 30.75 78.34 1962 81.95 61.49 53.58 59.76 35.71 86.35 1963 82.46 67.24 56.95 71.14 40.35 85.21 1964 91.14 71.37 62.07 65.45 42.33 88.08 1965 97.45 76.73 65.24 65.45 46.14 89.24 1966 106.12 79.01 72.80 71.54 53.67 92.91 1967 106.64 86.09 80.78 78.86 61.56 99.71 1968 112.91 90.23 88.04 87.40 71.19 103.32 1969 104.93 94.73 93.35 94.31 83.59 101.60 1970 100.00 100.00 100.00 100.00 100.00 100.00 1971 99.63 110.96 107.67 110.98 114.35 103.53 1972 93.00 116.81 116.56 120.73 135.76 104.59 1973 97.55 121.67 129.14 133.74 162.58 108.58 1974 107.81 123.99 141.82 150.81 195.84 109.62 1975 117.86 130.74 152.66 161.79 229.35 109.64 1976 115.35 131.53 164.34 184.84 261.79 119.35 1977 113.07 134.93 181.08 198.07 305.93 121.70 1978 113.44 136.84 197.48 216.43 355.52 121.93 1979 117.75 136.94 207.14 231.80 410.37 121.41 232 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Machinery Food Industry Machinery and Equipment Printing Machinery and Equipment Hoist Transport Equipment Equipment Pumps and Compressors Log and Paper Machinery and Equipment Light Industry Machinery and Equipment 1950 3.24 10.11 33.67 28.52 19.01 19.79 1951 4.44 11.25 34.65 29.51 19.17 24.53 1952 5.93 12.50 35.67 30.52 13.08 27.28 33.60 1953 8.01 13.90 36.91 31.77 13.19 1954 9.66 15.46 38.35 33.20 17.24 36.70 1955 11.63 17.19 40.21 35.09 22.24 39.28 36.98 1956 13.32 19.11 41.88 36.74 28.29 1957 16.34 21.25 43.70 38.58 32.96 43.50 1958 18.38 23.63 45.86 38.12 41.57 51.33 1959 27.16 26.70 48.56 42.48 48.53 42.46 1960 34.88 29.53 51.63 47.33 55.50 45.54 1961 38.99 31.42 55.16 49.92 58.00 51.76 1962 43.55 37.09 59.26 52.66 60.71 58.39 1963 47.28 40.16 63.35 55.55 59.13 62.58 1964 56.74 45.12 61.86 58.59 64.98 65.32 1965 66.50 51.03 65.35 64.83 70.04 70.95 1966 76.07 62.32 75.58 71.38 78.12 76.04 1967 81.98 71.95 87.44 81.10 83.73 82.19 1968 88.78 83.44 91.30 86.05 89.29 86.02 1969 95.40 92.28 95.35 95.35 96.63 90.74 1970 100.00 100.00 100.00 100.00 100.00 100.00 1971 112.21 113.20 106.51 102.91 102.18 108.31 1972 121.84 124.24 115.81 112.79 106.94 113.23 1973 134.13 136.09 130.23 122.09 109.52 118.16 1974 144.05 146.80 146.28 135.17 120.83 124.83 1975 155.97 161.59 160.70 145.64 120.44 126.50 1976 166.77 178.79 168.56 155.65 128.42 131.39 1977 174.47 193.85 181.29 165.02 136.62 132.82 1978 184.40 206.13 192.67 169.86 146.65 136.94 1979 188.76 220.16 200.53 175.03 156.69 139.27 233 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Machinery Construction Transportation Automobiles Machinery Machinery and and Equipment Equipment Agricultural Machinery and Equipment Other Machinery Sanitary Engineering Products Other Metalwares Metallic Structurals Machinery Repair 1950 19.92 19.29 13.59 15.12 8.29 13.18 12.25 13.42 12.02 1951 21.02 13.96 13.45 15.07 7.84 16.46 13.89 15.13 13.45 1952 21.62 11.86 14.71 15.77 10.32 19.17 15.57 16.86 15.06 1953 23.62 18.26 17.63 17.12 13.77 21.52 17.44 18.77 16.87 1954 24.80 25.62 21.63 20.60 17.57 23.60 19.62 20.99 18.88 1955 25.67 31.45 24.94 26.40 23.67 25.92 22.51 23.94 21.14 1956 30.14 42.98 27.95 33.85 25.20 29.36 24.77 26.19 23.67 1957 35.70 67.47 31.77 42.99 26.12 33.85 27.13 28.52 26.51 1958 39.53 94.16 36.04 39.46 26.27 39.09 29.88 31.22 29.68 1959 40.75 102.36 40.06 34.81 28.87 46.22 34.06 35.27 33.53 1960 47.01 82.70 41.67 40.14 31.65 53.94 37.05 41.83 37.31 1961 54.75 67.09 44.97 49.28 35.40 60.60 41.13 43.92 41.25 1962 59.21 79.85 48.98 57.60 38.26 66.99 46.31 46.85 46.89 1963 62.81 74.71 52.57 66.77 41.39 73.70 50.39 50.62 52.23 1964 70.95 80.94 57.46 69.75 46.12 78.13 54.09 55.22 58.76 1965 75.40 90.04 59.56 74.03 49.42 83.19 57.80 60.24 64.10 1966 80.79 73.03 67.72 78.55 56.50 86.91 63.58 64.46 68.59 1967 87.53 76.48 73.12 81.48 65.45 90.30 71.68 72.29 75.00 1968 93.21 105.22 78.76 86.68 78.51 92.22 80.35 82.53 82.05 1969 101.82 102.84 82.21 94.79 90.24 95.67 89.60 89.16 90.38 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 109.56 114.78 115.83 108.88 112.52 104.60 110.00 109.00 110.00 1972 116.01 121.82 127.79 118.48 125.62 108.59 119.00 121.00 119.00 1973 121.18 130.33 141.88 133.57 139.99 113.74 131.00 135.00 129.00 1974 126.58 132.11 156.48 151.74 155.48 119.96 142.00 146.00 140.00 1975 134.08 138.17 164.99 163.69 169.70 124.37 153.00 160.00 152.00 1976 136.06 137.03 171.54 173.65 180.84 126.87 162.00 173.00 163.00 1977 137.40 137.47 178.71 181.90 196.31 129.34 171.00 183.00 174.00 1978 132.45 137.57 187.32 193.96 214.51 131.92 181.81 194.57 184.00 1979 132.69 141.50 194.09 203.13 227.54 137.80 188.69 201.93 192.00 234 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Chemicals and Petrochemicals Index:1970=100 Mineral Chemicals Basic Chemicals Aniline Dye Products Synthetic Resins and Plastics Synthetic Fibers Organic Synthetic Products Paints and Lacquers Rubber Products Synthetic Rubber 1950 4.78 12.26 49.61 4.01 3.88 7.27 18.27 21.38 15.75 1951 5.75 13.35 56.08 3.95 5.68 8.30 21.78 21.72 18.82 1952 7.08 14.73 62.25 4.54 7.90 9.55 23.51 21.95 20.57 1953 8.62 16.29 63.14 5.57 10.00 11.57 24.55 23.44 23.19 1954 10.45 18.46 66.94 7.29 12.65 13.08 28.68 26.81 23.41 1955 12.31 21.29 77.87 9.58 17.74 15.22 30.54 29.43 26.26 1956 14.86 24.06 81.68 11.22 20.69 18.07 33.56 32.74 26.91 1957 16.91 25.61 80.29 12.25 23.87 21.03 38.78 36.93 25.93 1958 20.18 27.05 84.64 14.17 26.65 27.46 42.34 41.58 32.82 1959 23.99 28.36 86.53 16.24 28.81 32.24 49.41 44.71 33.92 1960 29.84 30.19 88.74 18.63 33.90 35.54 53.85 49.75 37.96 1961 35.17 33.39 90.31 22.94 40.19 38.16 52.80 54.87 42.01 1962 39.64 37.04 90.32 27.01 44.51 42.33 56.66 60.21 49.78 1963 42.33 42.46 91.94 33.91 49.50 48.80 57.97 65.17 51.09 1964 51.27 50.58 90.87 41.90 57.96 56.65 60.07 70.37 56.24 1965 62.89 59.85 87.09 48.00 65.38 69.28 68.25 76.35 66.08 1966 70.44 67.33 93.69 58.06 73.56 73.63 75.77 79.88 72.65 1967 76.73 74.43 92.84 66.56 81.96 81.85 85.77 85.60 79.87 1968 81.76 80.31 92.62 77.20 88.88 85.99 87.71 91.78 83.92 1969 88.05 85.50 98.05 86.85 93.66 91.72 91.82 94.30 91.47 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 110.69 109.19 100.63 111.44 108.57 106.67 109.96 104.56 109.41 1972 120.13 116.62 94.57 122.07 119.76 112.03 112.65 112.07 115.97 1973 136.48 127.39 91.99 138.72 133.23 119.52 116.37 122.18 126.37 1974 153.46 141.03 91.92 149.05 142.38 126.33 127.40 136.05 141.14 1975 174.00 156.51 93.49 169.92 153.29 133.38 133.47 148.70 158.64 1976 190.00 162.40 94.23 182.83 163.72 136.66 131.09 157.42 171.77 1977 202.00 170.46 97.29 197.84 174.64 143.00 127.13 165.80 186.00 1978 212.00 174.78 96.98 210.21 181.54 149.88 130.55 170.47 196.39 1979 220.00 171.56 98.14 207.94 176.57 160.20 122.36 173.31 204.27 235 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Wood, Pulp, and Paper Products Logging Sawing and Woodworking Furniture Pulp and Paper Wood Chemicals 1950 59.32 41.37 7.54 22.10 60.14 1951 67.23 46.93 8.77 24.70 73.45 1952 66.76 51.00 10.19 27.35 76.55 1953 65.81 55.84 11.68 30.90 82.41 1954 74.80 58.25 15.01 33.97 80.05 1955 76.62 63.43 17.36 35.42 82.51 1956 79.56 64.59 18.66 38.31 82.83 1957 84.71 68.59 21.66 41.69 89.01 1958 88.80 78.22 26.70 44.54 94.40 1959 95.05 86.45 33.32 46.56 99.57 1960 90.58 87.99 39.46 48.66 101.03 1961 87.10 87.40 45.67 51.57 104.39 1962 87.78 87.95 51.38 55.19 106.60 1963 91.84 89.66 56.51 58.29 107.71 1964 95.36 93.24 59.96 62.66 117.42 1965 94.10 94.29 64.63 70.57 125.27 1966 93.15 91.43 69.53 78.10 121.31 1967 97.31 93.45 77.81 84.48 123.84 1968 97.72 94.33 85.66 88.74 120.49 1969 96.37 96.34 91.72 93.52 109.35 1970 100.00 100.00 100.00 100.00 100.00 1971 99.93 102.05 109.32 105.50 96.93 1972 99.61 102.12 119.07 110.25 96.36 1973 101.51 100.38 130.61 116.72 106.71 1974 101.22 99.34 141.47 121.75 114.38 1975 104.00 100.65 152.54 127.73 118.49 1976 100.39 97.80 161.28 133.95 117.24 1977 98.60 95.44 171.84 136.47 120.99 1978 94.61 92.49 182.32 138.82 121.34 1979 91.36 86.87 187.88 130.75 122.31 236 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Index:1970 = 100 Gross Sector Output Indexes: Construction Materials Cement Concrete Wall Materials Asbestos Cement Roofing Material Construction Ceramics Other Materials for Construction Glass and Porcelain 1950 9.38 1.29 25.18 8.84 21.41 6.01 16.58 25.46 1951 11.18 1.69 30.67 11.43 23.76 8.62 19.71 22.80 1952 13.04 2.09 35.40 14.37 26.99 11.97 22.97 21.49 1953 15.18 2.19 39.89 17.49 30.40 15.97 26.98 26.90 1954 17.94 3.08 44.48 21.37 33.43 20.79 31.80 31.68 1955 20.45 5.27 49.41 25.04 37.77 27.17 38.88 36.75 1956 22.04 8.83 51.50 29.88 40.19 32.81 42.01 41.65 1957 26.96 13.89 60.90 34.93 43.56 39.13 45.85 44.89 1958 31.71 19.71 72.70 38.90 48.60 44.12 54.02 49.67 1959 37.06 26.28 82.12 42.00 51.72 46.44 61.48 54.42 1960 42.51 33.65 86.84 48.23 56.24 51.72 68.55 59.64 1961 48.11 40.42 88.34 54.64 59.56 57.53 72.86 61.32 1962 55.28 47.55 85.66 60.76 63.71 62.81 72.94 68.19 1963 61.60 52.42 82.92 63.12 68.40 69.24 72.93 70.13 1964 67.21 57.88 83.56 66.55 74.59 74.50 73.17 77.24 1965 74.37 66.28 85.06 69.36 81.17 77.39 77.77 79.10 1966 82.13 75.67 88.73 76.16 86.73 80.21 80.89 82.91 1967 87.00 83.20 94.31 82.07 90.49 84.08 87.24 84.80 1968 90.56 87.11 95.52 87.05 88.62 87.52 91.45 88.51 1969 93.35 90.85 94.89 88.73 94.53 92.41 91.79 91.33 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 106.30 106.72 103.18 105.61 102.65 105.43 110.14 104.71 1972 111.05 112.54 105.76 111.36 106.25 109.62 116.48 113.48 1973 117.11 119.88 108.61 118.35 116.74 115.68 124.58 121.66 1974 123.53 126.22 109.78 124.87 126.27 120.40 130.65 130.13 1975 131.59 132.37 112.06 132.66 131.96 127.17 134.22 142.13 1976 134.15 137.27 112.11 138.77 141.34 129.91 141.06 147.89 1977 136.67 139.89 110.43 125.27 137.81 136.47 145.13 155.25 1978 137.76 141.91 109.23 126.44 140.06 142.87 151.82 161.65 1979 133.20 139.16 104.37 127.08 131.44 139.88 158.74 166.77 237 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Light Industry Cotton Fabric Silk Fabric Wool Fabric Linen Fabric Hosiery and Knitwear Sewn Goods Other Light Industry 1950 44.62 9.24 28.55 36.41 17.74 19.54 37.42 1951 54.24 12.35 32.78 39.73 22.74 22.27 42.12 1952 57.72 15.70 35.41 32.14 24.83 25.00 42.26 1953 60.99 27.24 38.72 36.21 27.29 27.91 42.84 1954 64.78 35.23 44.91 36.05 31.54 33.19 45.25 1955 68.71 36.24 46.68 38.40 34.65 36.72 47.57 1956 64.56 52.55 50.12 49.97 35.12 40.43 49.63 1957 66.56 57.02 53.17 54.91 37.36 40.84 54.28 1958 70.03 60.23 57.23 62.22 39.79 44.72 60.10 1959 75.02 57.83 61.73 68.57 42.83 49.36 65.36 1960 78.64 58.92 65.34 73.00 45.72 52.97 68.92 1961 79.24 59.55 68.00 69.76 47.55 56.74 72.31 1962 79.88 68.67 70.51 68.56 50.20 58.99 73.69 1963 82.43 69.85 71.28 72.04 53.69 57.80 74.75 1964 87.22 72.60 71.99 76.94 61.37 56.39 76.41 1965 89.39 69.90 71.78 77.51 70.07 56.25 77.20 1966 92.70 75.83 78.69 83.73 77.58 61.88 81.37 1967 96.16 81.85 84.40 90.81 83.72 70.63 86.23 1968 99.41 82.90 90.29 95.62 89.41 81.58 90.69 1969 100.91 89.53 95.70 95.33 95.23 90.72 94.91 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 103.98 103.84 105.35 107.50 103.77 106.25 100.53 1972 104.37 110.82 107.02 109.62 105.35 107.50 96.22 1973 106.92 117.36 111.05 112.59 109.89 109.38 99.10 1974 107.67 125.77 115.70 112.59 112.50 112.50 101.64 1975 107.83 131.59 118.78 110.18 113.99 118.75 103.15 1976 110.19 139.53 123.56 114.14 116.94 125.74 105.80 1977 110.71 143.80 127.97 115.56 119.69 130.81 106.71 1978 113.25 147.91 130.54 117.40 122.04 135.89 106.79 1979 113.41 150.44 132.38 108.63 124.40 141.61 106.20 238 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) Gross Sector Output Indexes: Processed Food Fish Products Meat Products Dairy Products Sugar Flour and Cereal Bread Products Confec- tionary Products Vegetable Oils Fruit and Vegetable Products Other Food 1950 18.36 21.83 7.62 24.88 44.00 49.07 34.29 29.65 17.82 18.29 1951 22.75 24.40 10.10 29.40 49.08 51.86 39.99 33.06 19.97 20.91 1952 25.00 27.36 10.87 30.39 54.48 55.28 44.41 35.79 22.22 22.96 1953 28.68 30.76 12.07 34.14 57.45 58.39 48.69 41.51 24.53 26.01 1954 33.85 30.43 13.44 26.25 62.47 62.11 50.31 45.69 28.50 29.75 1955 39.22 33.38 16.20 34.02 69.65 65.84 47.96 41.41 32.99 31.64 1956 42.99 36.37 23.23 43.28 69.70 69.57 54.63 54.64 36.69 34.38 1957 40.53 40.63 28.93 44.55 72.54 73.91 54.21 60.62 38.44 37.24 1958 41.50 46.07 33.35 53.80 77.13 78.26 57.87 52.66 40.86 39.45 1959 44.13 58.10 38.89 59.41 80.26 79.19 61.71 68.16 44.58 42.36 1960 48.71 60.44 43.98 62.87 79.29 80.12 60.22 56.97 49.18 45.23 1961 51.20 58.02 47.88 82.28 81.52 84.16 62.36 65.32 54.86 48.06 1962 54.68 66.01 49.59 76.69 81.77 88.20 67.33 76.35 59.60 52.71 1963 59.74 74.84 50.66 61.52 77.64 90.06 71.17 79.07 68.69 57.76 1964 68.65 57.34 55.75 80.89 75.64 93.79 79.63 80.83 70.95 61.62 1965 71.93 72.29 62.74 108.01 83.75 94.41 79.94 100.11 68.52 66.46 1966 75.78 80.05 68.64 95.34 88.80 96.27 77.28 99.18 74.38 72.23 1967 81.15 89.90 75.51 97.26 90.30 96.89 81.98 109.94 88.56 77.90 1968 83.70 92.75 85.17 105.03 91.51 95.96 88.09 114.43 94.13 82.59 1969 91.66 91.12 93.42 100.99 92.56 99.07 95.48 107.85 88.06 93.20 1970 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 1971 103.60 114.25 100.68 88.54 102.51 103.42 99.79 104.63 107.25 101.86 1972 112.08 122.05 102.08 87.28 105.24 105.90 102.24 101.00 118.03 103.92 1973 119.84 117.45 109.60 104.97 103.28 105.90 108.56 95.09 124.66 94.42 1974 131.02 132.14 118.35 92.86 100.98 106.21 112.81 122.08 133.31 107.20 1975 145.49 139.28 121.41 101.98 98.02 109.32 112.12 119.52 137.62 114.38 1976 152.41 120.02 120.89 91.15 94.96 112.11 116.95 97.70 128.63 119.50 1977 150.43 131.38 125.61 117.97 104.54 111.18 121.93 103.16 134.18 119.71 1978 155.08 138.46 127.36 119.70 102.10 114.29 127.66 103.67 130.18 106.91 1979 164.99 139.09 127.82 104.69 106.22 114.91 130.15 97.73 141.33 118.39 239 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix B Computation of the Machinery Index Creation of the machinery index requires two separate tasks: � The relative weights of producer durables, consumer durables, and military machinery as a share of all machinery in the base year must be estimated. � Indexes must be derived to drive these weights over time to record the growth in production. These two tasks can be decomposed into the following six steps: The first step is to determine which input-output sectors produce consumer and/or producer durables. Unfortunately, information was inadequate to divide consumption final demand between private and public consumption in the reconstruction of the 1972 input- output table. Thus, we are forced to use the 1966 input-output table in 1970 prices as the basis for splitting machinery deliveries to consumption into private and public components.' Of the 27 machine- building and metalworking (MBMW) sectors in the 1966 table, all except possibly one manufacture pro- ducer durables and only eight produce consumer durables based on patterns of deliveries to final demand. The second step is to construct indexes representing each type of durable for as many of the machinery sectors as possible. These sector indexes are con- structed in much the same way as they are for other branches. The products for every sector are valued in 1 July 1967 prices and then summed for every year. The one difference is that some of the sectors produc- ing both consumer and producer durables are divided into two subsamples, resulting in two indexes for these sectors. Occasionally the sample for a given sector is so limited in scope that we are compelled to use the same index to move both producer and consumer durables. ' A version of this table appears in Vladimir G. Treml and Gene D. Guill, "Conversion of the 1966 Producer's Price Table to a New Price Base," in Treml, Studies, pp. 197-281. 241 Ideally we should have 35 indexes: 27 for the sectors that manufacture producer durables and eight for those making consumer durables. Because of informa- tion gaps reasonable indexes can be constructed for only 27 of the possibilities-20 producer durable sectors and seven consumer durable sectors. More- over, in three of these sectors the same index is used for both kinds of machinery. The sectors with missing indexes and their estimated share of machinery value added in 1972 are as follows: Percentage Share of Value Added Total 31.8 Cables�consumer durables 1.1 Cables�producer durables NEGL Casting machine & equipment�producer durables 0.1 Tools and dies�producer durables 1.3 Construction materials Machine & equipment�producer durables 0.5 Bearings�producer durables 1.0 Other machinery�nonconsumer durables 27.4 Abrasives�producer durables 0.4 Although the tabulation above casts considerable doubt on the coverage of the index for machinery, with nearly one-third of value added unaccounted for, it is somewhat misleading. The bulk of the missing share is in the "other machinery" sector, which is commonly believed to conceal a large military ma- chinery component that is captured elsewhere in our index. If it is assumed that all of the "other machin- ery" is military and the totals are accordingly adjusted, the missing sectors combined add to less than 6 percent of the total. The third step consists of estimating value added in 1972 for each sector and type of machinery (see table B-1). To do this we assume that every ruble of product Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-1 USSR: Allocation of Value Added in the Machinery Sector to Producer Durables and Consumer Durables (1) Sector (2) Total Deliveries to Final Demand (million rubles) a (3) Deliveries to Private Consumption (million rubles) b (4) Consumer Durables Share (Percent) a (5) Producer Durables Share (Percent) d (6) Sector Value- Added (million rubles) a Energy and power machinery and equipment 740.8 0 0 100.0 671.0 Electrotechnical machinery and equipment 2,842.2 455.0 16.0 84.0 3,149.3 Cable products i -243.0 6.9 100.0 0 516.5 Machine tools 1,349.7 0 0 100.0 858.1 Forge press machinery and equipment 297.5 0 0 100.0 200.7 Casting machinery and equipment 64.8 0 0 100.0 52.6 Tools and dies 157.5 0 0 100.0 605.9 Precision instruments 2,490.8 466.3 18.7 81.3 3,326.9 Mining and metal machinery and equipment 1,522.4 0 0 100.0 1,039.0 Pumps and compressors 1,693.8 505.8 29.9 70.1 1,008.4 Log and paper machinery and equipment 224.8 0 0 100.0 142.9 Light-industry machinery and equipment 488.6 35.1 7.2 92.8 352.0 Food-industry machinery and equipment 516.1 0 0 100.0 321.1 Printing machinery and equipment 56.3 0 0 100.0 39.1 Hoist-transport machinery and equipment 1,066.9 0 0 100.0 533.4 Construction machinery and equipment 1,205.3 0 0 100.0 574.8 Construction material machinery and equipment 320.8 0 0 100.0 222.7 Transport machinery and equipment 4,285.4 0 0 100.0 1,812.6 Automobiles 3,846.8 1,003.7 26.1 73.9 2,874.6 Agriculture machinery and equipment 3,099.6 0 0 100.0 2,129.4 Bearings 121.6 0 0 100.0 448.2 Other machinery 19,848.4 2,078.8 10.5 89.5 14,461.5 Sanitary engineering machinery and equipment 53.9 0 0 100.0 578.4 Other metalwares 1,322.3 959.5 72.6 27.4 1,961.9 Metal structures . -7.2 0 0 100.0 734.7 Repair machinery and equipment 10,282.2 0 0 100.0 8,470.4 Abrasives i -85.7 0 0 100.0 170.8 Total machinery 57,562.6 5,511.1 47,256.4 a Drawn from the 1972 producer prices input-output table. b Drived from the 1972 table and the 1966 table as estimated in 1970 producer prices. For sectors with nonzero deliveries to consumption in 1972, the private consumption share of that total is assumed to be the same percentage as it is in the 1966 table. a 100 x column (3)/column (2). 242 a 100 - column (4). a See a. Total outlays - interindustry purchases. f Column (4) x column (6)/100. Column (5) x column (6)/100. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-1 (continued) USSR: Allocation of Value Added in the Machinery Sector to Producer Durables and Consumer Durables (I) Sector (7) Value Added in Manufacture of Consumer Durables (million rubles) f (8) Value Added in Manufacture of Producer Durables rubles) $ (9) Consumer Durables Index Status h (10) Producer Index Status h Energy and power machinery and equipment 0 671.2 NC Electrotechnical machinery and equipment 509.2 2,645.0 EQ EQ Cable products i 516.5 0 NI NI Machine tools 0 858.1 NC Forge press machinery and equipment 0 200.7 NC Casting machinery and equipment 0 52.6 NC NI Tools and dies 0 605.9 NC NI Precision instruments 622.8 2,704.1 NC Mining and metal machinery and equipment 0 1,039.9 NC Pumps and compressors 301.2 7072 Log and paper machinery and equipment 0 142.9 NC Light-industry machinery and equipment 25.3 326.8 EQ EQ Food-industry machinery and equipment 0 321.1 NC Printing machinery and equipment 0 39.1 NC Hoist-transport machinery and equipment 0 533.4 NC Construction machinery and equipment 0 574.8 NC Construction material machinery and equipment 0 222.7 NC NI Transport machinery and equipment 0 1,812.6 NC Automobiles 750.0 2,124.6 Agriculture machinery and equipment 0 2,129.4 NC Bearings 0 448.2 NC NI Other machinery 1,514.6 12,946.9 NI Sanitary engineering machinery and equipment 0 578.4 NC Other metalwares 1,423.2 538.1 EQ EQ Metal structures 0 734.7 NC Repair machinery and equipment 0 8,470.4 NC Abrasives i 0 170.8 NC NI Total machinery 5,657.7 41,598.7 h Key NC: This sector does not produce any consumer durables according to the input-output table. Ni: No reliable index is available for measuring either producer or consumer durables production in this sector. u: The production index used is unique either to producer or consumer durables in this sector. EQ: The same production index is used both for producer and consumer durables in this sector. The negative final demand of cable products, metal structures, and abrasives prevents determination of the producer and consumer durables shares. Since for cables the apparent consumer durables share is positive and the producer durables share is negative, we arbitrarily allocate all of that sector's value added to consumer durables. Since metal structures and abrasives apparently have no private consumption, we allocate their entire value added to the producer durables group. 243 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 shipped to final demand in a given sector embodies the same value added regardless of whether the machinery is a producer or consumer durable. Based on this assumption, the value added for each machin- ery type can be estimated by multiplying total sector value added by each component's share of deliveries to final demand. Some bias is introduced by determining the relative importance of producer and consumer durables as described above. Deliveries of many machinery sec- tors to final demand categories other than private consumption undoubtedly include substantial amounts of purely military machinery; not all military hardware is produced in the "other machinery" sector of table B-1. This gives producer durables an exces- sively high weight and consumer durables too low a weight. In the fourth step the producer and consumer dura- bles indexes are calculated separately. Indexes of each type are converted into value added by linking them to the values derived in table B-1: the resulting values are then summed for every year. The fifth step derives the production index for civilian machinery by using the control totals for 1972 value added of consumer durables and producer durables in table B-1, that s, 41,599 and 5,658 million rubles, respectively. Applying these weights to the producer durables and consumer durables indexes and adding them together provide the index for civilian machinery. Finally, the civilian and military machinery indexes are combined into an index of total Soviet machinery production. The weights are obtained according to the following procedure. The figure for military machin- ery production in 1972 (after deducting common use durables) is converted to value added by using the ratio of total machinery final demand to value added as given in the reconstructed 1972 input-output table. The military share of value added in machinery production in 1972 is derived by comparing this value with total value added in the machinery branch. The indexes of output for civilian machinery and military machinery are then used to find the shares in the base year, 1970�for military machinery, about one-third and for civilian machinery, about two-thirds. 244 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part III. AN INDEX OF AGRICULTURAL PRODUCTION IN THE USSR By Barbara Severin and Margaret Hughes 245 93-892 0 - 82 - 17 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Contents Page I. Summary II. Introduction III. Construction of the Index A. Coverage of the Sample B. 1970 Price Weights C. The Index IV. Evaluation of Official Soviet Statistics A. Availability B. Accuracy C. Lack of Consistency Over Time D. Comparability With Western Statistics V. Deductions for Waste A. The Nature of the Problemn B. Calculation of Waste in Sunflower Seed and Grain VI. Deductions for Seed and Livestock Feed A. Grain and Potatoes Used for Seed B. Estimates of Livestock Feed and Hatching Eggs C. Testing the Estimates of Seed and Feed VII. Sensitivity Tests A. Use of Alternative Discounts and Feed Values 251 253 253 253 257 259 260 260 261 263 265 266 266 267 269 270 271 274 275 276 B. Use of Alternative Price Weights 276 VIII. Comparison of the CIA Index with Other Indexes of Soviet Agricultural 278 Production A. The Official Soviet Index of USSR Gross Agricultural Output 279 B. The FAO Index 281 C. The USDA Index of Soviet Agricultural Output 281 D. The US Index of Agricultural Output 283 Appendixes A. Derivation-of Quantity Data Used in the Index of Soviet 285 Agricultural Production B. USSR: Average Realized 1970 Prices of Agricultural Commodities 297 C. USSR: Intrasector Use of Agricultural Output 303 247 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Tables 1. USSR: Value of Agricultural Output, 1970 255 2. Commodities Included in CIA and Soviet Indexes of Agricultural 258 Production 3. USSR: Index of Net Agricultural Production, Selected Years 260 4. Comparison of Official and Estimated Grain Output, 1950-1962 265 5. USSR: Estimated Waste and Losses in the Gross Grain Harvest 270 6. Intrasector Use of Agricultural Output 271 7. Sensitivity Tests of CIA Index 277 8. Sensititity Tests of Shares of Net Output 278 9. Comparison of CIA and Soviet Official Indexes of Agricultural 280 Production 10. Comparison of Structure of Output in Soviet and CIA Indexes 281 11. Comparison of CIA and FAO Indexes of Soviet Agricultural 282 Production, 1966-79 12. Comparison of CIA and USDA Indexes of Soviet Agricultural 283 Production 13. Comparison of Structure of Output in CIA and USDA Indexes 283 14. Comparison of Relative Prices in CIA and USDA Indexes of Soviet 284 Agrjcultural Production 248 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 List of Standard Citations Full Citation Abbreviated Citation USSR Central Statistical Administration, Statistical Handbooks Sel'skoye khozyaystvo SSSR, 1960, (Agriculture USSR) Selkhoz 1960 Sel'skoye khozyaystvo SSSR, 1971, (Agriculture USSR) Selkhoz 1971 Narodnoye khozyaystvo SSSR v 19�godu (National Economy of the USSR in 19�) Narkhoz 19� Soviet Periodicals Voprosy ekonomiki (Problems of Economics) Vop ek Vestnik statistiki (Herald of Statistics) Ekonomika sel'skogo khozyaystva (Economics of Agriculture) Vest stat Ek selkhoz Planovoye khozyaystvo (Planned Economy) Plan khoz US Government Publications CIA, The Soviet Grain Balance, 1960-73, A (ER) 75-68, September 1975 Joint Economic Committee, Congress of the United States Gross National Product of the USSR, 1950-80, 1982 A (ER) 75-68 JEC, GNP, 1950-80 An Index of Industrial Production in the USSR, 1982 JEC, Industry An Index of Agricultural Production in the USSR, 1982 An Index of in the USSR, 1982 Consumption in the USSR: An International Comparison, 1981 CIA, USSR: Gross National Product Accounts, 1970 A (ER)75-76, November 1975 JEC, Agriculture JEC, Consumption JEC, Consumption Comparison CIA, GNP 1970 Gross National Product of the USSR: An International Comparison, 1982 JEC, GNP Comparison Other Publications Vladimir G. Treml and John P. Hardt, eds., Soviet Economic Statistics, Treml and Hardt Durham, N.C., Duke University Press, 1972 249 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 An Index of Agricultural Production in the USSR I. Summary The CIA index of Soviet net agricultural production measures trends in the value of agricultural produc- tion available for sale and home consumption for each year in the USSR since 1950. The output index measures production in the year in which it is pro- duced, although some of this production may be marketed or consumed in subsequent years. The index is devised to measure agriculture's contribution to Soviet GNP. The index also has served as the basis for international comparisons of farm output and for studies of productivity in Soviet agriculture. The following tabulation shows the relatively close corre- spondence of the CIA index and other major indexes of Soviet agricultural production. Average Annual Percentage Rates of Growth 1951-79 1961-70 1971-79 Indexes of net output CIA 3.0 3.7 0.9 US Department of Agriculture 3.1 3.6 1.5 Indexes of gross output CIA 3.2 3.6 1.2 Official Soviet 3.2 3.3 1.4 The CIA index is based on output of 28 individual crops, ten livestock products, and four items of live- stock inventory change. When the CIA index is calculated on a gross basis and compared with the official Soviet index of gross output, the livestock component covers about 95 percent of the Soviet measure of livestock products and the crop component about 80 percent of crop production. We assume that the trend in output of residual crop and livestock products is the same as that of the price-weighted aggregate of commodities included in the sample. In the CIA index, grain and potatoes make up over half of crop output while meat and milk dominate livestock production. The CIA index omits production of hay and other forage crops, decorative plants, fishing, fur production, and minor livestock products such as feathers, beeswax, and silkworm eggs. Also excluded are manure and "unfinished production" included in the Soviet definition of gross agricultural production. Output estimates in the CIA index are largely based on Soviet agricultural statistics. Estimates are made, however, where data are missing. Official production statistics are corrected as necessary for measurement error, or where Soviet data seriously overstate usable or standard-weight output. The physical production data for the commodities in the index are aggregated for the most part with average prices received by all producers for products sold in 1970, into two subsector indexes�one for crops and the other for livestock output. Average realized prices for the majority of commodities can be estimated with adequate reliabil- ity. In some cases, however, state procurement prices had to be substituted even though they are less desirable since they exclude collective farm market prices. Despite this bias, sensitivity tests indicate that price weights are not a major source of error in the index. Much less certain are the estimates of intra-agricul- tural use of farm output�seed and feed�that are deducted from gross output to derive net agricultural production. Seed estimates are based on annual sown area data and on officially prescribed seeding rates for a fixed period. The use of a constant seeding rate probably introduces an element of error, yet seed estimates are relatively more reliable than those for feed. Although estimates of grain fed derive from official data, estimates of potatoes fed are particularly tentative for years where official data are lacking. Only occasional Soviet statements on quantities of whole milk and vegetables fed are available to derive estimates of quantities fed. Quantities of other com- modities fed are too small to be a source of substantial error. A potentially more important source of error is the paucity and unreliability of published Soviet agricul- tural statistics. Although data are more plentiful now 251 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 than 10 or 20 years ago and reliability may have improved, many gaps remain. Estimates must be made, especially for agricultural products used in the production process. The accuracy of important series is also questionable. For example, statistics on private sector production, which are based on sampling, prob- ably contain a considerable margin of error, with particular consequences for the measurement of out- put in the livestock sector. Further reducing reliability of estimates of net output in the livestock sector is the scarcity of published feed statistics which, in any case, are believed to be less reliable than official commodity output data. Deliberate falsification is another source of diminished reliability in agricultural statistics. Grain output statistics for the early 1950s published nearly a decade later almost certainly reflect deliber- ate understatement of the crop. Examples of recent falsification can also be found. Because most recent falsification appears to originate at lower levels in the reporting process, it is unclear how it impinges on the overall aggregate data. Soviet gross output statistics also include a large element of waste. For example, there is considerable evidence to suggest that the usable quantities of grain, sugarbeet, potato, vegetable, fruit, sunflower seed, and egg production are smaller than official produc- tion statistics report. Moreover, standard weight of these commodities may be even less. Adjusting for waste is very difficult because of the shortage of data. We confine our deductions for waste and losses to grain and sunflower seed output, where we believe data exist to make such adjustments feasible. The waste in sugarbeet production is eliminated by use of procurement statistics�which are reported in stan- dard weight. Failure to deduct for waste elements in other crops is potentially the most serious cause of overstatement of net output in the CIA index. How- ever, we adopted the policy of not imposing arbitrary adjustments on official Soviet data where no informa- tion exists on which to base such adjustments. To the extent that these adjustments are proportionately constant over time, the trend is not distorted. Because of these and other deficiencies in available Soviet statistics, we believe our index is a more reliable measure of trends in agricultural production than of levels of output. In this context it is a more reliable indicator of the change over a period of years - than of changes between any two consecutive years. The CIA index shows net output growing more rapidly in the 1950s and slowing steadily during the 1960s and 1970s. This trend is clearly seen in output of the livestock sector. Crop output grew more rapidly in the 1960s than in the 1950s but growth fell to rates below either of these periods in the 1970s. The rapid growth of the livestock sector in the 1950s caused the share of livestock output in total net production to increase from 45 to 54 percent between 1950 and 1960. Since 1960 share of livestock output in net agricultural production has remained unchanged. Average Annual Percentage Rates of Growth 1951-60 1961-70 1971-79 Total output 4.3 3.7 0.9 Crop production 2.6 3.7 0.7 Livestock production 6.1 3.7 1.0 We applied several sensitivity tests to the index to assess changes that would be caused by different discounts for waste, different (1960) price weights, and different approaches to valuing feed and livestock inventory. None of the tests changed average annual growth of total output for the 1951-79 period by more than one-tenth of one percentage point. The livestock index was most affected by the use of 1960 prices while the crop index was most altered by removing the discounts on grain and sunflower seed. Because 1970 prices are relatively more favorable to livestock pro- ducts than 1960 prices, the switch to 1960 prices caused the largest shift in the shares of total output originating in the crop and livestock sectors. We compared the CIA index to three other indexes of Soviet agricultural output. Surprisingly, for the 1960s and 1970s, growth rates of total output calculated from these indexes differ by less than half a percent- age point, although the indexes themselves vary wide- ly in coverage and weighting: � The FAO index incorporates a recently revised methodology and thus covers only 1966 forward; it is based on a large sample. 252 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 � The USDA index covers all years since 1950 and is also based on a large sample, but is weighted with average prices received by farmers in Western Europe during 1969-71. The latter diverge some- what from Soviet relative prices. � The official Soviet index measures gross rather than net output, that is, it includes the value of crops and livestock products used in agricultural production as well as unknown quantities of waste. The CIA index is calculated on a gross basis for this comparison. The major difference between the CIA index on a gross basis and the Soviet index of gross agricultural output is the heavier weight placed on livestock production in the CIA index. In the Soviet index since 1960, crops and livestock have contributed equally to gross output, while in the CIA index during this period the livestock sector accounts for about 54 to 56 percent of gross output. Nevertheless, for the 1951-79 period as a whole, gross output in the Soviet and CIA indexes and net output in the CIA index all grow at about the same rate. The largest discrepancy in growth rates occurs in 1951-60, when the official index shows much more rapid growth than the CIA index of net output. When we adjust the CIA index to a gross basis and use the same price weights as are in the official Soviet index, the differences in growth narrow. Some of the discrepancy in the shares of crops and livestock in total output remains, however, be- cause we do not include the value of hay and green feed in crop output. Moreover, the CIA index omits a number of other crops included in the official Soviet index. H. Introduction.' The CIA index of agricultural production is a key element in CIA's estimates of growth in Soviet GNP. Because about 16 percent of GNP originates in agriculture, the GNP measure must incorporate a reliable indicator of year-to-year changes in value added in agriculture�especially since weather causes ' The authors wish to thank John Carroll, Constance Krueger, and Luba Richter for their assistance in the preparation of this paper. They are particularly indebted to Constance Krueger, whose meticulous research is largely responsible for the prices and the seeding rates used in construction of the index. wide fluctuations in agricultural output with substan- tial effect on annual changes in GNP. The USSR does not publish an index of value added in agricul- ture, however.' We estimate value added by first deriving net agricultural output, that is, by reducing the value of gross production by the value of output consumed in the production process (seed and feed) and by waste. When the value of agriculture's pur- chases from other sectors of the economy�fuel, fertil- izer, spare parts, services, and the like�are subtract- ed from net output, the result is value added.' This paper describes and evaluates the CIA index of net agricultural output. First, the derivation of the sample coverage and 1970 price weights is described. We then consider the validity of Soviet agricultural statistics on which the index is based. We present our estimates of seed, feed, and waste. After describing the construction of the index of net output, we apply sensitivity tests to assess the effects of different waste measures and price weights. Finally, we compare the structure and trends in the CIA index with those in three other indexes of Soviet agricultural output, including the official Soviet index of agricultural production. The details of our estimates and the sources for all data used in the index are presented in the appendixes. III. Construction of the Index A. Coverage of the Sample Estimates of net agricultural output are derived by aggregating the value of production of 28 individual crops, 10 livestock products and four items of live- stock inventory change using the 1970 average prices The USSR publishes data on net output of agriculture in current prices in official national income statistics. This is not comparable to the Western definition of net output, however, because the Soviet series deducts all material inputs and not just those produced within agriculture. The Soviet national income series excludes depreci- ation, which is part of value added and includes the value of services purchased from outside the sector such as transportation, recreation, financial services, and the like which are not included in the Western definition of value added. Thus the Soviet series does .not correspond exactly to our definition of value added, although it is probably closer in concept to value added than to net output as measured by our index. See CIA ER 78-10505, USSR: Toward a Reconciliation of Marxist and Western Measures of National Income, October 1978. ' Estimates of purchases by agriculture from other sectors are discussed in the paper by John Pitzer, JEC, GNP, 1950-80. 253 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 received by all producers.' Agricultural commodities are included in the index in the year in which they were produced although some of the commodities may be marketed or consumed in subsequent years. We divide agriculture into two subsectors: crops and livestock. Net production of the crop sector is the value of crop production available for sale outside the crop sector and for direct consumption by farm households�that is, gross crop production minus the value of seed grain and seed potatoes and minus waste elements in grain and sunflower seed production. In theory, waste should be deducted for all crops, but lack of data makes it impossible to estimate these quantities for crops other than grain and sunflower seed. Crops used exclusively within agriculture for feed such as hay, corn for silage, feed roots, and so forth, are not counted. Similarly, to obtain "net" output of the livestock sector, gross output is reduced by animal products used for feed and hatching eggs. When the two sectors are aggregated to measure total net agricultural output, the value of commodities transferred between them for use in the production process is subtracted to avoid double counting. These transfers represent feed produced in the crop sector but consumed by livestock such as grain, potatoes, whole milk, and vegetables. Because hay and other forage crops are not included in crop output, they are not part of these transfers. Data are lacking to estimate transfers such as manure from the livestock sector to crop production. When the two subsector indexes are considered independently, feed is counted as crop output and also is included implicitly in the value of livestock output. In measuring total net output, we subtract the value of crops and whole milk fed as well as hatching eggs from livestock output. Thus, the value of hay and other forage crops is automatically included in net livestock output. The CIA index, then, defines net livestock production as gross output minus a) the value of selected agricultur- al commodities fed to livestock and b) the value of hatching eggs. Because our crop index and feed deduction make no allowance for hay and other forage ' The index is a Laspeyres quantity index where / P70, j Qi j I, -- j:11 / P70, j Q70, j = crops, the value of net livestock output is somewhat overstated relative to the value of net crop output. The value of these feed crops is small, however, and its exclusion does not have a significant effect on the results.' Below, we define the sample categories in more detail.' We touch briefly on waste as it affects each category; a fuller discussion of the waste prob- lem can be found in section V below. Table 1 shows the ruble value and percentage distribution of agricul- tural production in 1970 according to our index. Grain and Potatoes. Grain and potatoes together amount to 60 percent of net crop output. We account separately for nine types of grain: wheat, rye, corn, barley, oats, rice, millet, buckwheat, pulses, and "oth- er grains." Other grains amounted to less than 1 percent of the value of grain output in 1970. The following tabulation shows the value of grain produc- tion in 1970. Wheat and barley together account for over two-thirds of the ruble value of net grain output. While wheat has always been the single most impor- tant grain, barley has been in second place only since the early 1960s. Growth in barley production is associated with the emphasis on rapid expansion of feed grain output. Before then, rye was the second largest grain crop in value terms. Million Rubles Percent Wheat 7256.0 53.1 Rye 990.5 7.3 Buckwheat 224.0 1.6 Rice 307.4 2.2 Corn for grain 1009.6 7.4 Oats 839.4 6.2 Barley 2282.9 16.7 Millet 138.2 1.0 Pulses 600.9 4.4 Other 8.3 0.1 Total 13657.2 100.0 While the CIA index is primarily used to derive value added in agriculture, with some adjustments it can also be used to gauge trends in output of the crop and livestock sectors available to consumers. For this purpose, net crop output is defined as gross output less seed, waste, and grain, potatoes, and vegetables used for feed. Net livestock output is defined as gross output less whole milk fed and eggs for hatching. Redefining the subsectors in this way raises the growth in livestock output and reduces the growth in crop output reflecting the relatively rapid gains made by the Soviet consumer in consumption of livestock products. 6 Details on the derivation of the quantity data used in the index are presented in appendix A. The derivation of 1970 average realized prices is explained in appendix B. 'These include sorghum, spelt, vetch, lupin, seradella and other minor miscellaneous grains. 254 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Gross potato production includes without differenti- ation the so-called "standard" quality output and the inferior, nonstandard production grade. To measure net output of grain and potatoes, gross output is reduced by quantities used for seed and, in the case of , grain, by waste. No waste is deducted from gross output of potatoes because data are lacking. (Our estimates of seed are discussed below in sections IV and VI.) Vegetables and Fruits. Production of vegetables and fruit accounted for almost one-fifth of net crop output in 1970 with the value of output evenly split. Until the late 1960s, however, vegetables predominated. Fruit production has continued to gain and exceeded annual average vegetable production in 1975-79. The struc- ture of production in 1970 is shown below. Million Rubles Percent Fruit 3296.6 48.8 Beets 128.3 1.9 Cabbage 711.4 10.6 Carrots 198.0 2.9 Cucumbers 485.7 7.2 Onions 866.4 12.8 Tomatoes 933.7 13.8 Other vegetables 136.5 2.0 Total 6756.6 100.0 Official Soviet statistics on vegetable production- published only as a total-include vegetables raised in "open beds" (field grown), and in hothouses and heated beds. Field-grown vegetables are by far the largest category of production.' Vegetables in our sample include carrots, beets, onions, cabbage, cu- cumbers, and tomatoes. Vegetables not listed sepa- rately in the CIA index but included in other vegeta- bles (parsley, mushrooms, squash, turnips, radishes, lettuce, spinach, dill, and so on) accounted for only 2 percent of the value of vegetable output in 1970. Fruit g Melons are often grouped with vegetables in Soviet statistics. However, melons are not included in official vegetable output statistics, although they are included in official acreage reports and in vegetable consumption statistics. Insufficient data are available on production to include melons in the index. Table 1 USSR: Value of Agricultural Output, 1970 a Percent Category Number of Components Million Rubles Grain 10 13657.2 35.5 Potatoes 1 9286.6 24.1 Vegetables 7 3460.0 9.0 Oil crops 3 1303.6 3.4 Fruits, berries, nuts 1 3296.6 8.6 Sugarbeets 1 1856.0 4.8 Cotton 1 3823.9 9.9 Tobacco 1 475.6 1.2 Makhorka 17.5 negL Fiber flax 1 1068.9 2.8 Tea 1 256.3 0.7 Net crop output 38502.2 100.0 46.1 Meat 5 28797.7 51.5 Milk 1 16271.1 29.1 Eggs 1 4074.0 7.3 Wool 1 1947.9 3.5 Honey 1 336.0 0.6 Silk cocoons 1 171.9 0.3 Livestock inventory change 4 4366.8 7.8 Gross livestock output 55965.3 100.0 Less: feed hatching eggs 10724.6 185.4 Net livestock output 45055.3 53.9 Net agricultural output 83557.4 100.0 a In 1970 average realized prices. A more detailed version of this table covering the years 1950-79 can be found in appendix A. output includes grapes, berries, and other fruit (ap- ples, pears, quinces, cherries, plums, apricots, peaches, and citrus fruit). Fruit is a single entry in the CIA index because insufficient data exist to derive annual estimates of individual types. Like grain and potatoes, gross output of vegetables and fruits should be re- duced for waste to convert total output to a net basis. Lack of a consistent time series of required deductions prevent this adjustment, although waste is no doubt considerable. 255 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Technical Crops. Our sample, shown in the following tabulation, includes oilseeds, sugarbeets, cotton, to- bacco, makhorka, fiber flax, and tea. Cotton alone accounts for almost half of the value of technical crop production. Sugarbeets, sunflower seed, and fiber flax account for almost all of the remaining half. These shares have not changed appreciably over time. Million Rubles Percept Sunflower seed 1057.0 12.0 Soybeans 156.5 1.8 Other oil crops 90.0 1.0 Sugarbeets 1856.0 21.1 Cotton 3823.9 43.5 Tobacco 475.6 5.4 Makhorka 17.5 0.2 Fiber flax 1068.9 12.1 Tea 256.3 2.9 Total 8801.7 100.0 Among oilseeds, we count separately only sunflower seed and soybeans. Together, these account for 93 percent of total oilseed output.' Other crops grown exclusively for oilseeds but not listed separately in- clude castor beans, flaxseed, mustard seed, and at least 11 other minor oilseeds. A waste discount of 8.0 percent is applied to sunflower seed output. In addi- tion, oilseeds are produced as a joint product with cotton and hemp. Cottonseed is included in cotton production which is measured as raw, unginned cotton including seeds. Hemp and associated seed, a minor crop, is not included. Meat. Meat output in our index is measured at slaughter weight and includes meat on the bone, all raw fats, and edible offal derived from livestock and poultry slaughtered in goverment-operated packing 9 Earlier versions of this index accounted separately for flaxseed, castor beans, and mustard seed in addition to sunflower seed and soybeans. In revising the index for this paper, it was established that continuous time series of official data for these other oilseeds were not available. Our category "other oil crops" is a residual derived by subtracting sunflower seed and soybean production from Soviet data on output of all oil crops. plants, on socialized farms, and by private sector households.' We account separately for beef and veal, mutton and kid, pork, poultry, and other meat. Other meat includes rabbits, horses, deer, camels, and game, and amounted to 3 percent of the value of meat output in 1970. The shares of individual types of meat in total output have changed somewhat. The share of poultry has doubled from 6 percent in 1950 to 13 percent in 1979, while mutton dropped from 14 percent to 4 percent. The share of beef dropped from 47 percent to 35 percent between 1950 and 1955 and slowly recov- ered to 47 percent in 1979. Shares of pork demon- strated the reverse trend, climbing from 31 percent to 42 percent between 1950 and 1955 and then declining to 33 percent in 1979. Since 1950, however, beef, veal, and pork have accounted for at least three-quarters of the value of total output. The following tabulation shows the distribution of meat output in 1970: Million Rubles Percent Beef and veal 13234.4 46.0 Pork 10230.8 35.5 Mutton and kid 1827.6 6.3 Poultry 2536.1 8.8 Other meat 968.8 3.4 Total 28797.7 100.0 Other Livestock Products. Milk, eggs, wool, honey, and silk cocoons are other livestock products in the index. All are shown in table 1. Gross meat and milk production, however, roughly accounted for 80 per- cent of gross output of livestock products in 1970. This share was almost 90 percent in 1950, and has risen since 1970 to 84 percent in 1976-79. Milk output includes all milk from cows, sheep, goats, and mares. An estimate of whole milk fed to livestock is deducted in deriving net livestock production. Also excluded from net output are eggs used for hatching. I� Edible offal includes the internal organs of the animal: lungs, liver, heart, kidneys, stomach, and others. It also includes the head, brains, feet, and other parts that are used for food in the USSR. Soviet statistics formerly grouped these products in four categories. Sometime during the 1960s, these were collapsed to two. 256 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Changes in Livestock Inventories. The CIA index measures the annual change in the number of cattle, hogs, sheep and goats, and poultry." Published Soviet herd statistics do not regularly include other domesti- cated animals such as camels, donkeys, and reindeer. The increase or decrease in numbers is valued at the average realized price per live animal in 1970, which is derived from the average weight of animals sold to procurement organizations in that year. We assume that the larger average weight of mature animals offsets the lower per animal weight of young animals so that the average weight for the entire herd is equal to the average weight of animals designated for slaughter. Although average animal weight changes every year, sensitivity tests presented below indicate that, for most years, the index is not much affected by failure to take this change into account. General Assessment. Sufficient Soviet data are available to assess the coverage of the CIA index relative to the more comprehensive Soviet measure of gross agricultural production.' Table 2 compares the commodities in- cluded in both indexes." The CIA index includes the commodities shown in column one; the Soviet index includes the commodities in both columns." Although the CIA sample seems to exclude a long list of crops, most of the excluded crops are used entirely within agriculture and are not part of output available for sale and home consumption. Crops omitted from the CIA index that are not produced for intra-agri- cultural use include the additional technical crops such as hops, as well as flowers and decorative plants, " The change in numbers of horses is excluded because horses are included in the Soviet definition of agricultural capital stock. Increments in horse inventories, therefore, are not part of current net output available for sale. 'Gross output includes the value of all agricultural products and makes no deduction for agriculture's use of its own output in the production process. A'complete list of the commodities in the Soviet index is available in F.E. Savitskiy et al., Spravochnik po planirovaniyu sel'skogo khozyaystva, Moscow, 1974, pp. 462-464. " Meat output is measured quite differently in the two indexes. In the Soviet index, output is equal to the difference in liveweight of animals at the beginning and the end of the year minus the weight of purchased animals plus the liveweight of all animals sold for slaughter. and some items of inventory change. In addition to the broader coverage shown in table 2, the Soviet index has finer detail for many of the basic commodities. For example, the CIA index is based on output of nine specific grains while the Soviet index includes 17 individual types. The CIA index accounts separately only for sunflower seed and soybeans under oilseeds; the Soviet index includes 16 individual items in this category. The coverage of the livestock sector is conceptually closer in the two indexes than that for the crop sector despite the differences in measurement of meat output. The coverage of the CIA index can also be assessed by comparing the ruble values of gross agricultural out- put as measured by the Soviet and CIA indexes. '6 When the two indexes of gross output are compared , the CIA index includes 90 percent of Soviet output of agriculture. Over 95 percent of livestock products and 80 percent of crop output are covered. '6 The CIA index would show somewhat greater coverage of crop production if estimates of hay, pasture feed, and other forage crops had been included when converting the CIA index to a gross output basis. The comparison suggests that the CIA index has generally good coverage probably accounting for roughly 95 percent of total output net of intrafarm use of crops. B. 1970 Price Weights Each commodity in the index of agricultural produc- tion is valued at the weighted average of prices paid by the USSR's three major purchasers of farm pro- ducts in 1970. For a number of commodities, such as vegetables and meat '7prices received by farm produc- ers vary substantially depending on the purchaser. The largest purchasing organization is the Ministry of " To make this comparison, commodities in the CIA index on a gross basis were valued in the 1965 comparable prices used in the Soviet index. In addition, the value of seed and feed were added back to create a CIA measure of gross output. '6A detailed discussion of the differences in the growth rates and the structure of the CIA and Soviet indexes is presented below in section VIII B. "Prices for meat are based on procurement prices for live animals and are converted to a slaughter weight basis. See appendix B. 257 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 2 Commodities Included in CIA and Soviet Indexes of Agricultural Production Components of CIA Addditional Components Used in Index Soviet Gross Output of Agriculture A. Crops 1. Grain 2. Technical crops a. fiber crops: cotton and flax b. sunflower seed c. soybeans d. other oil seeds e. sugarbeets f. tobacco and makhorka g. tea 3. Potatoes 4. Vegetables 5. Fruits, berries, and nuts I. Byproducts of grain crops (straw,' chaff, and so forth) 2. Technical crops a. other fiber crops b. essential oil raw materials c. medicinal plants d. chicory root e. seeds and planting material for technical crops f. other technical crops (hops, tea, and so forth) g. Other oilseeds 3. Feed crops a. root crops b. hay c. green fodder d. silage crops e. other feed crops f. seeds of feed crops 4. Crops for green manure 5. Flowers and decorative plants 6. Expenses for starting and caring for perennial plantings 7. Unfinished production (change in value during the year of expenses for sowing winter crops and soil preparation) B. Livestock I. Meat (slaughter weight) a. beef and veal b. pork c. mutton and kid d. poultry e. other meat 2. Change in number of livestock 3. Milk 4. Eggs 5. Wool 7. Silk cocoons 1. Weight gained by livestock during the year (liveweight) 2. Offspring and increase of working livestock (horses, camels, donkeys and mules) and of reindeer 3. Fur-bearing animals (hides and offspring) 4. Change in number of bee colonies 5. Fish breeding (young fish and fish catch) 6. Other animal products (hair, horns, feathers, manure, beeswax, silkworm eggs) Procurement, which buys agricultural commodities from state farms, collective farms, and individual private sector producers. Other state purchasing orga- nizations are the Central Union of Consumer Cooper- atives, and the Ministries of the Food Industry, Meat and Dairy Industry, Light Industry, and Trade. The second major sales channel for farm products is the system of collective farm markets where producers sell agricultural commodities at prices determined largely by the interplay of supply and demand. Prices paid in collective farm markets normally exceed procurement prices, because products sold through this channel are of higher quality or because a given product is scarce or unavailable in state retail stores. For example, in 1970 the average collective farm market price for milk was almost double that paid by procurement organizations. In practice, average realized prices could not be obtained for each commodity in the index. Surrogates, some more satisfactory than others, had to be used in a number of cases. Although average realized prices for all grain, vegetables, and meat can be estimated, the prices needed to value each individual type of grain, vegetable, and meat are missing. Data on average collective farm market prices for individual commodities are especially scarce and must be esti- mated in many cases. Soviet literature provides rela- tively ample data on list procurement prices 's for individual commodities but obtaining USSR-wide averages of prices actually paid in a given year is difficult. In the case of honey and some oilseeds, we had to substitute RSFSR list procurement prices. Collective farm procurement prices paid in 1970 are ' List procurement prices are paid by procurement organizations for products of standard quality. Prices for a given product are differentiated by region in the USSR. In Belorussia, for example, in 1970-72 there were 113 price zones for milk; the milk prices ranged from 170 to 620 rubles per ton (N.I. Goryachko, Obosnovaniye sistemy zakupochnykh tsen, Minsk, 1978, p. 20). List prices exclude adjustments made at the time of sale for product quality. Grain with moisture content above standard levels, for example, will be purchased at prices below list prices. List procurement prices also exclude bonuses paid for sale above the plan quota. '9 Although the RSFSR prices are only for state and collective farms and exlude the private sector, this is not a source of significant error. The private sector produces almost no oilseeds, and the price for honey was made the same for all producers in 1970 (Zakupki sel'skokhozyaystvennykh produktov, no. 9, 1970, p. 1). 258 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 better surrogates in that they include price bonuses and penalties, but they are for one producer only. The average of procurement prices paid in 1970 to all producers is the best surrogate for average realized prices. The following tabulation shows where substitutions have been made for average realized prices. Each price used in the index is derived in appendix B. Average Realized Prices RSFSR List Procurement Prices Procurement Average Prices Paid Procurement to Collective Prices Paid Farms to All Producers Grain Potatoes Vegetables Meat Livestock inventory Milk Eggs Wool Sunflower seed Oil crops (except sunflower seed) Honey Sugarbeets Flax fiber Tobacco Makhorka Silk Fruit Cotton Tea The error introduced by these substitutions probably is small. Average realized prices have been used for the most important commodities in the index. In the two cases where list procurement prices have been used the value of output is small. The value of commodities priced with collective farm procurement prices probably is overstated; a comparison of pro- curement prices for commodities where we have prices for state farms, collective farms, and private produc- ers shows that average procurement prices paid to state farms are often somewhat less than those paid to collective farms and private producers. Since collec- tive farm market sales of oilseeds, flax, tobacco, makhorka, silk, cotton, and tea are insignificant, procurement prices in these cases are an acceptable substitute for average realized prices. The average procurement prices understate the value of output significantly only in the case of fruit and honey, where collective farm market sales are substantial. Cotton and tea are sold exclusively through the state procure- ment system. Valuing commodities fed at average realized prices overstates feed use if the portion fed is of much lower quality than the portion marketed. In the case of potatoes and vegetables, a lower price is used. By virtue of the calculation, quantities of grain fed are standard weight so should be priced at average real- ized prices. Whole milk fed, however, may not be of standard butterfat content-the basis for the price- so could be overvalued. The effect of this over- statement is small; sensitivity tests indicate that valu- ing feed at Soviet cost of production does not affect trends. (See section VII.) C. The Index The CIA index of Soviet net agricultural production shows steadily declining growth after 1960. This trend is especially prominent in net output of the livestock sector. Table 3 shows indexes of output for major commodity groups in benchmark years related to the base year 1970, while the following tabulation sum- marizes growth rates for these commodities. Average Annual Percentage Rates of Growth 1951-79 1951-60 1961-70 1971-79 Grain 2.5 3.4 4.0 -0.3 Potatoes 0.2 -0.8 2.0 -0.5 Fruits and vegetables 5.1 6.5 5.3 3.3 Technical crops 3.3 4.6 4.0 1.3 Net crop output 2.4 2.6 3.7 0.7 Meat 4.1 6.1 3.5 2.7 Milk 3.4 5.7 3.0 1.3 Other 4.6 9.0 5.5 -0.9 Net livestock output 3.7 s 6.1 3.7 1.0 Net agricultural output 3.0 4.3 3.7 0.9 Among crops, fruits and vegetables grew most rapidly over the 1951-79 period, rising from 10 percent of net crop output in 1950 to 22 percent in 1979. Growth in grain output held at fairly steady rates while potato output posted almost no growth. At the same time, potatoes fell from 40 percent of net crop output in 1950 to 22 percent in 1979. Crop output shows more variation in growth rates than the livestock sector where growth rates slowed over the entire period. By 1971-79, only fruits, vegetables, and meat were grow- ing at average annual rates above 2 percent. For many 259 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 3 USSR: Index of Net Agricultural Production, Selected Years a 1976 1977 1978 1979 1950 1955 1960 1965 1970 1975 Grain 48.3 56.4 67.2 66.0 100.0 76.6 120.5 103.3 131.6 97.7 Potatoes 88.9 66.9 82.2 88.8 100.0 90.4 87.9 86.2 89.3 95.4 Fruits and vegetables 31.8 47.5 59.5 75.8 100.0 115.8 124.0 122.0 127.3 133.7 Technical crops 43.2 56.8 67.5 87.6 100.0 104.4 114.9 118.8 112.0 111.9 Net crop output 54.0 57.5 69.6 78.2 100.0 93.2 112.0 106.0 116.2 106.7 Meat 39.1 51.5 70.7 80.3 100.0 122.9 112.5 120.7 126.9 126.8 Milk 42.5 51.8 74.3 87.4 100.0 109.4 108.0 114.4 114.0 112.4 Other livestock products (including inventory change) 24.7 47.6 58.3 85.6 100.0 58.1 82.7 106.5 97.8 92.1 Net livestock output 38.4 54.1 69.3 86.7 100.0 102.4 101.1 115.3 113.3 109.0 Net agricultural output 45.6 55.6 69.4 82.8 100.0 98.2 106.1 111.0 114.6 107.9 a 1970=100 commodities, 1971-79 growth rates were less than half of the rates posted for 1951-60." IV. Evaluation of Official Soviet Statistics The accuracy of the CIA index of agricultural output ultimately depends on the reliability of the Soviet statistics used to construct it. Western observers have long criticized Soviet agricultural statistics for being unavailable, inaccurate, inconsistent over time, or not comparable with Western measures of farm output. In constructing the CIA index of Soviet agricultural production, we have made some adjustments to com- pensate for these deficiencies in Soviet statistics. A. Availability Availability of Soviet statistics is a broader problem than the mere scarcity of data on physical output of commodities. Data on commodity use are also scarce as are the definitions needed to interpret some of the published statistics correctly. The reliability of the 2� Poor weather in 1979 depressed crop growth and thus growth in total agricultural output. If the comparisons were for the period 1971-78, crop output would have grown at an average annual rate of 1.9 percent, and net output at 1.7 percent per year. CIA index is affected more by the absence of statis- tics on the use of farm products for seed, feed, and the like than by a shortage of output data. Although troublesome shortages of production data still exist, more utilization data and definitional material have become available and the accuracy of statistical re- porting may have improved somewhat. Earlier, Western investigators puzzled, for example, over whether milk output statistics were recorded in physical weight or converted to standardized butterfat content. How milk fed to calves was reported in output statistics was also ambiguous." Definitional material now available explicitly states that gross output of milk is in physical weight, while procure- ment statistics are in terms of standardized butterfat content." The issue of milk fed to calves has also been clarified: milk sucked directly by calves is excluded " D. Gale Johnson and Arcadius Kahan, "Soviet Agriculture: Structure and Growth," Comparisons of the United States and Soviet Economics, U. S. Congress Joint Economic Committee, Washington, D. C., 1959. Nancy Nimitz also discussed this issue. See RM 2326, Soviet Statistics on Meat and Milk Output: A Note on Their Comparability Over Time, Rand Corporation, February, 1959. " Z. G. Tresorukova, Tovarnaya produktsiya sel'skogo kho- zyaystva, Moscow, 1974, p. 103. 260 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 from gross output. Milk fed by other means is includ- ed." Part of the problem of understanding milk, statistics remains, however, because a large share� nearly 40 percent�of milk output is not marketed and must be estimated from survey data. Moreover, much of the data on milk marketings is a calculated milk equivalent of marketed cream. Mistakes in the conversion factor could result in erroneous figures for total milk output. Production data used in the CIA index for most commodities are the official Soviet gross output fig- ures, with some surrogates. In the case of vegetables, the USSR publishes only a single figure for total output of vegetables. Production of individual types of vegetables must be estimated by applying the percent- age distribution of state vegetable procurements to the figure for total output. For sugarbeets, tobacco, mak- horka, and tea, official procurement statistics provide a reasonably reliable measure of net output. We assume home consumption of these products to be a very small share of total output. Although scattered statistics on the use of agricultural commodities have become available, the CIA index must incorporate a number of estimates of seed, feed, and waste in order to have continuous series. Seed estimates are based on officially "normed" seeding rates which may well differ from the true rates. Statistics on waste of agricultural commodities are especially scarce." Ideally an index measuring agri- cultural output should incorporate waste estimates for grain, sunflower seed, potatoes, fruits, vegetables, and eggs. Although the Soviet press often reports exam- ples of high loss rates for these commodities, the data are so incomplete that the index only deducts waste from production of grain and sunflower seed. Output of other commodities is therefore overstated. How- ever, to the extent that the share of gross output wasted remains roughly the same over time, the failure to make waste adjustments will not affect trends. " Selkhoz 1971, p. 685; A. M. Bryanskiy, Statistika zhivotno- vodstva, Moscow, 1956, p. 122; V. Starovskiy, Vest stat, no. 4, 1961, p. 105. " Waste is broadly defined to include extraneous matter, damaged output, and losses in handling as well as excess moisture (that is, moisture above a standard level). Waste therefore can include usable product. Broken kernels, for example, in grain would be classified as waste, but would also be usable. Estimates of agricultural commodities fed to livestock also suffer from lack of data. The CIA index deducts from gross output estimates of the grain, potatoes, vegetables, and whole milk used for feed. The release to a USDA feed-livestock delegation to the USSR in 1971 of data on quantities of concentrates by type fed to livestock simplified the task of estimating grain fed." Other products fed, however, must be estimated using commodity balances that attempt to reconcile Output statistics with estimates of utilization. For potatoes, however, statistics on utilization are often inconsistent so that a satisfactory independent bal- ance cannot be constructed. For example, for some years, the sum of estimated uses of potatoes for seed, feed, and industrial purposes exceeds total production as reported in statistical handbooks. (See appendix C.) B. Accuracy The accuracy of Soviet agricultural statistics has been debated by Western scholars for decades." Inac- curacy is believed to result in part from reporting errors and in part from deliberate falsification. De- spite the extensive writing on the shortcomings of Soviet agricultural statistics, the evidence is still ambiguous concerning the degree of accuracy of published official series. " The data were published in USDA, ERS Foreign 355, Livestock- Feed Balances for the USSR, (undated). Grain is the major component (roughly 85 percent) of concentrated feed fed in the USSR. Concentrates are low in fiber and high in total digestible nutrients. Aside from grain, concentrates include milling byprod- ucts, oilseed meal, and alfalfa meal. Part of the grain is fed as a component of mixed feed, while the remainder is fed "straight." " A complete review of the debate is beyond the scope of this paper. The most important sources of the last 40 years begin with Naum Jasny's work in the 1940s, and continue with writings by Kahan, Volin, and Richter in the 1960s. Finally, in 1972, a volume dealing with Soviet economic statistics was published containing three chapters on agricultural statistics. See Naum Jasny, The Socialized Agriculture of the USSR, Stanford University Press, Stanford, California, 1949; Naum Jasny, "Interpreting Soviet Statistics," Soviet Survey, October-December, 1958, p. 9.; Naum Jasny, "Some Thoughts on Soviet Statistics: An Evaluation," Internation- al Affairs, no. 1, 1959, p. 53.; Lazar Volin, "Agricultural Statistics in Soviet Russia," The American Statistician, April-May and Juse-July issues, 1953.; Luba 0. Richter, "Some Remarks on Soviet Agricultural Statistics," The American Statistician, June, 1961; Arcadius Kahan, "Soviet Statistics of Agricultural Output," Soviet Agricultural and Peasant ?affairs (Roy Laird, ed.), Universi- ty of Kansas Press, Lawrence, Kansas, 1963.; Luba 0. Richter, "Commentary" (on Arcadius Kahan's article), p. 165.; V.G. Treml and J.P. Hardt, eds., Soviet Economic Statistics, Duke University Press, Durham, N.C., 1972. See the chapters by Philip M. Raup, Eberhard Schinke, and Karl-Eugen Wadekin, all dealing with the validity of Soviet agricultural statistics. 261 93-892 0 - 82 - 18 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Western scholars generally agree, however, that inac- curacy varies widely over time and affects some statistical series more than others. Political pressure in the Stalin and Khrushchev eras led to falsification of output data. The expansion and improvement in the statistical reporting system that began in the early 1960s may have resulted in more accurate data in recent years. Even today, however, data for politically sensitive commodities such as grain are subject to more manipulation than data for less sensitive pro- ducts. The prevailing Western opinion still is that reasonably accurate results are obtained using Soviet agricultural statistics if necessary adjustments and cross-checks of the data are made and if the supplied definitions are carefully read." Soviet writers often paint a more dismal picture of the reliability of their official statistics. Khrushchev stat- ed that "figures for average yield (of grain) which you read in the press these days reflect wishful thinking rather than reality." 28 He also said "unless we put things in order, our plans will be fulfilled statistically, but we will still be short of food." " More recently a Soviet emigre characterized the manipulation of Sovi- et agricultural statistics as follows. "Soviet hens lay a certain percentage more eggs each year but with one biological peculiarity. The annual increase in egg laying begins only with the advent to power of the durrent rulers.'"� While we cannot pinpoint the degree of unreliability in Soviet statistics, we can identify those statistical series that are most unreliable. The larger the share of output that originates in the private sector, for exam- ple, the more error is likely to occur. Private sector output is estimated by the Central Statistical Admin- istration from a sample survey of collective farm families. Data are collected by schedule takers who visit each family not less than two times a month. " Karl-Eugen Wadekin, "Soviet Agricultural Statistics: Summary and Assessment," in Treml and Hardt, p. 282. " N. S. Khrushchev, Khrushchev Remembers: The Last Testament, (Strobe Talbott, ed.), Little, Brown and Co., Boston, Toronto, 1974, p. 131. " Quoted from the New York Times report on January 15, 1961 (p. 28) of the 1961 Party Plenum. " Lev Navrozov, "What the CIA Knows About Russia," Commen- tary, September, 1978, p. 51. Efforts are made to choose "representative" families, but the survey embraces only 1.5 to 2 percent of collective farm families. The following tabulation shows the percentage of gross output of major pro- ducts produced by the private sector in 1979: Grain 1.0 Potatoes 59.0 Cotton 0 Meat 30.0 Sugarbeets 0 Milk 29.0 Sunflower seed 2.0 Eggs 33.0 Vegetables 31.0 Wool 19.0 The figures suggest that the livestock sector is more affected than the crop sector by inaccuracies in estimates of private sector production. One Western writer on Soviet statistics concludes that the degree of error in these statistics is difficult to assess without more detail on the sample coverage. We can only be aware that such error exists.' Socialized sector output statistics are derived from the annual reports of farms. These reports are based on an elaborate accounting system that is said to incorpo- rate cross-checks to prevent error and falsification. Such a system should provide accurate statistics, but failure to follow prescribed practice and shortages of qualified statisticians and bookkeepers introduce an element of error at the initial stage. Moreover, farms have no incentive to correct for waste because reduc- tions in gross output entail more difficulty in plan fulfillment and higher unit costs, whereas success requires high output and low unit cost. For example, farms frequently fail to weigh their output accurately. Truck scales are in short supply and often faulty. Grain output is thus often estimated according to the fullness of the combine hopper, although it is supposed to be weighed prior to record- ing in output accounts. For potatoes and vegetables, output estimates are haphazard. Potatoes are fre- quently stored in the fields in pits or piles. The weight of output is determined according to the dimensions of " Eberhard Schinke, "Soviet Agricultural Statistics," in Treml and Hardt, p. 244. 262 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 the pile and the actual weight of one cubic meter of output. Requirements for weighing vegetables are relaxed at the peak of the harvest, and the quantity of vegetables is measured according to the number of units, bunches, or basketsfull brought from the field. Later, these are converted to kilograms according to the actual weight of a sample of the produce." According to one Soviet source, on vegetable farms where harvested area is large and hundreds of workers are involved, it is impossible to carry out even this measuring of vegetable output. The first accurate weighing is done only when the vegetables are sold." Deliberate falsification of output statistics is another source of inaccuracy that is very difficult to evaluate. There is ample evidence from Soviet sources suggest- ing that in the Khrushchev era ambitious agricultural campaigns and unrealistic output targets led many officials to inflate output statistics. Soviet officials claim that falsification is less now than before the 1961 decree that imposed prison sentences for falsifi- cation of data." Although we tend to believe that instances of deliberate falsification are probably less , frequent now than in earlier periods, references to statistical malpractice occur periodically. Farms still have incentives to understate one year's production in order to reduce plan obligations in the following year or to obtain permission to curtail production of an unprofitable commodity. In 1978 a resolution of the Georgian Central Committee cited frequent cases of padding, underreporting, and other gross "distor- tions" in overall statistical reporting in the republic. Over 3,800 statistical checks were conducted by state statistical organizations; almost one third of the re- cords inspected were found to have some type of deliberate misrepresentation." The First Secretary of the Tadzhik SSR recently criticized state and party organs in the republic for insufficient implementation of the 1961 resolution against fraudulent reporting. He cited false reporting of statistics on sown area, production, sales, number of cattle, animal disease rates, and other statistics.36 " M. Z. Pizengol'ts, Bukhgalterskiy uchet v sel'skom khozyaystve, Moscow, 1974, pp. 111-112. " Uchet ifinansy v kolkhozakh i sovkhOzakh, no. 10, 1979, p. 16. Fletcher Pope, Collecting Agricultural Statistics in the Soviet Union, U. S. Department of Agriculture, Foreign Agricultural Report No. 112, November 1975, P. 15. " Zarya vostoka, 4 June 1978, p. 1. Not all of the instances cited refer to agricultural reporting. Kommunist Tadzhikistana, 27 March 1979, p. 2. Involvement of several ministries in statistics on mar- keted commodities may offer some constraints to falsification of those data. Present accounting practice particularly provides opportunities for false reporting of commodities which remain on the farm after sales or are produced solely for farm use, such as animal feed. In 1979, both the Georgian Central Committee and the First Secretary of Azerbaydzhan publicly denounced falsely inflated reports of fodder produc- tion in their republics." Milk production can be inflated by claiming that nonexistent output was fed to livestock. Farms have been known to purchase output from individuals or on collective farm markets and to credit the amount to farm production." Error in and falsification of agricultural statistics probably vary greatly among regions and from year to year. Because references to the subject are scarce and the extent to which it occurs cannot be determined, the impact on output statistics cannot be quantified. We can only conclude that falsification probably causes some upward bias in the level of output figures and that the degree of bias may not be the same for every year. As a result, the net effect over time, in the context of a trend value, remains unclear. C. Lack of Consistency Over Time Since 1950 a number of Soviet agricultural statistics series have undergone definitional changes without corresponding adjustments to published data. Be- tween 1939 and 1953, Soviet grain crops were meas- ured in terms of so-called "biological" output per hectare. These were estimates based on samples of the crop as the ripe grain stood in the field and did not take into account losses of grain prior to and during " Zarya vostoka, 1 June 1979, p. 1 and Bakinskiy rabochiy, 25 July 19'19,p. I. " Even procurement statistics have been doctored, although these have always been considered more reliable than output statistics (J.W. Willett,'"The Recent Record in Agricultural Production," Dimensions of Soviet Economic Power, US Congress, Joint Eco- nomic Committee, Washington, D.C., 1962, pp. 96-98). Instances of collusion among farm officials, state procurement agents, and inspection officials have been reported (Zakupki sel'skokhozyayst- vennykh produktov, no. 2, 1978). Farms, Mr example, have been credited with fictitious deliveries of agricultural products to pro- curement agencies. Zakupki sel'skokhozyaystvennykh productov, no. 10, 1975, reports such fraudulent transactions in the Ukraine, Lithuania, and Belorussia. 263 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 harvesting. The "bunker weight" " yield of the crop (that is, the grain as it weighed directly after combin- ing before preliminary cleaning and drying and before handling and transportation losses occur), is usually below the biological yield. Similarly, the clean, dry, standard-weight portion of the crop is usually less than the bunker weight. In 1954, the bunker weight concept was adopted for official grain output statis- tics. However, bunker weight statistics for the 1955- 58 period and output data for 1950-54 restated in bunker weight were not published until December 1958.� In addition, in 1958 the Central Statistical Administration published instructions for estimating the grain crop. These instructions were never publicly disseminated, but are believed to represent an alter-.. ation in the bunker weight measuring system adopted only four years earlier. Published yield statistics suggest that bunker weight grain output statistics before and after 1958 are inconsistent. During 1958-62, the average yield of grain is reported to have increased to 10.9 centners per hectare�an increase in average annual yields of 27 percent over 1954-57. Although grain output in pre-1958 statistics probably was understated by offi- cial manipulation of the data, the jump in yields that occurred in 1958 appears to be at least partly due to a change in statistical methodology that was never explained.' To test the consistency of official grain statistics before and after 1958, official production data for 1950-62 were compared with output data estimated from weather data, seeding and harvesting reports, procurement data, statements by Soviet officials, and the like." The comparison in table 4 of estimated and "Soviet statistical handbooks use the term "gross harvest" (valovoy sbor). Statistical handbooks prior to 1963 contained the phrase "barn yield" (ambarniy urozhay) in parenthesis, but later issues omit the reference to barn yield. 4� The USSR never published details of the conversion of biological yield data to bunker weight for pre-1954 data. One Soviet publica- tion stated that annual reports of farms were the basis for recalculating yields. Farms had collected bunker weight data for 1950-54 and earlier. (N.N. Zhivilin, Sovremennaya organizatsiya statistiki zemledeliya. Moscow, 1960, P. 102.) " For a complete discussion of the 1958 change in grain statistics, see CIA/RR ER 64-33, Production of Grain in the USSR, October, 1964, p. 19-22. 41 Ibid., p. 15-17. actual crops in 1950-1962 shows that for 1950-54, estimated production is equal to or larger than offi- cially reported output. After 1958, however, official production exceeds our estimates by a large margin. The comparison suggests that either 1950-54 grain output statistics are deliberately understated or that statistics following 1958 are exaggerated.' Our grain balance calculations, which begin in detail in 1960, indicate that grain output as shown in official statistics for 1960-62 are reasonably consistent with the sum of grain uses estimated on a bunker weight basis." We tend to accept the hypothesis, therefore, that grain statistics for 1950-54 (bunker weight) are deliberately understated. We attempt to compensate for this understatement by making no deduction from official data for waste and losses in 1950-54. For other years a weather-related discount is used to eliminate excess moisture and waste. These estimates and a full discussion of grain waste are in section V. below. The treatment of corn in official Soviet grain statistics has also changed. Before 1955, immature corn (in the milky-waxy stage of ripeness) was included in statis- tics for grain. Between 1955 and 1962, Soviet statisti- cal handbooks reported totals for grain output with and without immature corn.' Since then, farms have accounted separately for fully ripe corn and corn in the milky-waxy stage of ripeness. Even so, corn statistics are still not entirely consistent with the bunker weight measure for other grain crops. Ripe corn is converted to grain according to the average yield of grain from the cobs as measured by threshing of samples and is expressed in terms of a standard " The differences in 1955 and 1957 are small but the change in sign from negative to positive indicates some change in reporting or a sudden improvement in agrotechnology. The comparatively large discrepancy in 1956 is attributed to excessive postharvest losses resulting from inadequate transportation and storage facilities in the new lands areas to handle the bumper crop produced there. 4� CIA/A (ER) 75-68 The Soviet Grain Balance, 1960-73 Septem- ber 1975, p. 24. 'To make this calculation total corn output was stated in terms of dry corn equivalent. From this total, output of fully ripe corn was subtracted. The remainder was the dry corn equivalent of immature corn. This figure was subtracted from total grain output to derive total output excluding immature corn. The grain equivalent of immature corn was apparently not a component of total grain output prior to 1954 (Narkhoz, 1962 p. 268). 264 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 4 Comparison of Official and Estimated Grain Output, 1950-62 a Grain Production b (million metric tons) Official Data Excess of Officially Reported Output Estimated Over Estimated Production (percent) 1950 81 85 �4.7 1951 79 , 80 �1.2 1952 92 92 0.0 1953 82 83 �1.2 1954 86 87 �1.1 1955 107 103 3.9 1956 128 115 11.3 1957 105 100 5.0 1958 141 125 12.8 1959 126 100 26.0 1960 134 100 34.0 1961 138 115 20.0 1962 148 115 28.7 a CIA/RR ER 64-33, Production of Grain in the USSR, October 1964, p.16. b These statistics include the grain equivalent of corn harvested in an immature stage which is no longer included in Soviet statistics on grain production. moisture content of 22 percent.' Moisture content of other bunker weight grains varies widely, depending on harvesting conditions as well as degree of ripeness. No aggregated data on moisture content at the time of harvest are published. Meat statistics have become more inclusive over time. Between the 1920s and 1940s the definition of meat was expanded from beef, veal, pork, and mutton to include poultry, rabbit, and fat from all types of animals. By 1954, edible offal had been added to the E.G. Dolgushevskiy and A. G. Kiiristich, Serskokhozyaystven- naya statistika s osnovami ekonomicheskoy statistiki, Moscow, 1976, p. 94. Reporting corn in a standard 22 percent moisture content is similar to a bunker weight concept inasmuch as 22 percent is the upper limit of moisture at which husked ears can be stored in slatted cribs where they will -dry by spring to the 14-15 percent moisture needed for safe warm-weather storage. definition of meat." Approximately in 1956, the defi- nition of meat was expanded again to include horse, camel, and other minor meats." Published data are available from 1950 covering the broader definition of output. In 1965, the USSR revised its method of reporting the size of livestock herds. While this did not result in definitional changes, it may have caused statistics for subsequent years to be less accurate than earlier ones. Prior to 1965, the annual census of livestock on I January was taken by enumerators who visited social- ized farms during the first weeks of January. In 1965 the livestock census was discontinued. Herd numbers for 1 January are now derived from the monthly and quarterly livestock reports submitted by these farms to the Central Statistical Administration. The change in procedure was ascribed to the improved quality of farm bookkeeping and to the increasing share of livestock in the socialized sector. Numbers of pri- vately owned livestock on 1 January are taken from accounting records of rural councils." As in the pre- 1965 period, local statistical offices spotcheck private sector livestock reporting by surveying 10 to 15 percent of households with privately owned holdings. D. Comparability with Western Statistics Soviet agricultural output statistics are often not directly comparable with those used to measure agri- cultural output in the West. Coverage is frequently broader and the quality of the Soviet product is often lower than that of Western counterparts. This lack of comparability clearly affects comparisons of levels of output and can complicate comparisons of growth in agricultural output over time. International compari- sons overstate the relative position of the USSR unless "Offal is defined in footnote 10. " For a complete discussion of these statistical revisions, see Nancy Nimitz, Soviet Statistics of Meat and Milk Output: A Note on Their Comparability Over Time, RM 2326, the Rand Corp., February, 1959. aural councils (soviets) are the local administrative agencies of the central government. Certain agricultural matters are included in their administrative responsibility for local trade and industry. 265 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 adjustments such as those using ruble-dollar conver- sion ratios are made to compensate for the lower quality of Soviet output." Lack of quality comparability probably poses less of a problem for comparisons of growth of agricultural output than it does for comparisons of levels of output. Growth comparisons are affected, however, if non- comparable Western and Soviet data are used to construct price weights and component indexes of overall indexes of farm output. If relative prices for agricultural products in both countries do not reflect production tradeoffs (marginal rates of transforma- tion), then the validity of growth comparisons is reduced. For example, farm-gate prices in the US index of agricultural production probably measure marginal rates of transformation reasonably well; Soviet prices, however, are set by the government with little consideration of actual costs. In a US-USSR comparison, however, the effect of these deficiencies in Soviet prices on growth comparisons is small.' Of course, relative prices can shift over time with the result that growth comparisons would vary depending on the base year chosen for indexes of output. The relatively broader coverage of Soviet agricultural statistics on meat production is another example affecting weights and therefore comparisons of growth. Soviet statistics include meat from rabbits, horses, deer, camels, and so on, which few Western countries include. In a US-USSR comparison Soviet meat output is not seriously overstated because these quantities are small in the USSR and even smaller in the United States. A more serious source of difference in the weights is the inclusion of edible offal and US-USSR comparisons of agricultural output are discussed in Douglas Whitehouse and Joseph F. Havelka, "Comparison of Farm Output in the US and the USSR, 1950-1971," Soviet Economic Prospects for the Seventies, Joint Economic Committee, US Con- gress, Washington, D. C., 1973, p. 340. "To test the effect on the index of deficiencies in Soviet prices, we substituted cost of production figures in 1970 (sebestoimost' from ,Selkhoz /97/) for 1970 average realized prices. The substitution slowed growth in crop production by one tenth of one percent. Livestock output growth accelerated by two tenths of one percent for the 1951-78 period as a whole. While official Soviet cost data have major deficiencies (for example, a return on land and interest charges on capital are not included) they are probably closer to marginal rates of transformation than average realized prices. slaughter fat in Soviet meat production. The Soviet definition of slaughter weight includes internal and subcutaneous fat which, for example, can add 10 percent or more to the weight of a beef carcass." Without some adjustment, the structure of Soviet agricultural output would give meat production too heavy a weight relative to the weight of meat in the US output. For comparisons therefore, meat output in both countries is measured on a liveweight basis to improve comparability of definitions. Growth comparisons are also affected by changes in product quality over time. An index based on physical production understates real growth in output if qual- ity has improved simultaneously. International com- parisons of growth in agricultural output assume constant quality although the assumption may be unwarranted. Evidence suggests some improvement in the quality of Soviet livestock products, especially beef, between 1950 and 1978. Soviet meat animals have more meat on the bone than formerly, and the quality of milk and eggs has improved somewhat. Furthermore, the oil content of sunflower seed has risen. In theory, indexes of output of these commod- ities could be adjusted for quality to improve growth comparisons, although such an adjustment would be difficult to construct in practice. In the case of US- USSR comparisons of growth over time, the bias introduced by shifting quality probably is small be- cause improvement in quality of US products, par- ticularly pork, has also occurred. V. Deductions for Waste. A. The Nature of the Problem Soviet gross output statistics for many agricultural commodities are inflated by waste." Grain output statistics, for example, measure the harvest prior to any cleaning and drying. In the USSR, grain harvest- ing procedures and weather patterns tend to result in unusual amounts of extraneous matter being included in gross output. Excess moisture, damaged kernels, " Sel'skokhozyaystvennaya entsiklopediya, Vol. I, Moscow, 1969, p. 693. "See footnote 24. 266 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 and extraneous matter not found in large quantity in harvested grain in most countries are counted as grain output in the USSR. Other commodities affected are potatoes, sugarbeets, fruits and vegetables, sunflower seed, and eggs." Although waste included in Soviet statistics is an important difference between US and Soviet agricultural statistics, deducting waste is not merely a matter of improving comparability. Waste must be deducted from gross output because it is not included in that part of output available for sale and home consumption. Furthermore, procurement prices apply to output on a "standard" basis, that is, net of excess moisture and trash. The CIA index deducts only for waste and losses in grain and sunflower seed. Potatoes, fruits, vegetables, and eggs are not dis- counted because no consistent methodology or data eould be developed to remove waste from these com- modities although Soviet sources claim that losses of these commodities are significant. In the case of sugarbeets, we use procurements as a surrogate for output data. Procurement statistics are expressed in standard weight which, by Soviet definition, excludes waste." Nevertheless, Soviet sources suggest that losses of potatoes, vegetables, fruits, and sugarbeets are significant. Losses of agricultural output occur at several stages in the production and marketing process. Not all are relevant for measuring net output. Harvesting losses consist of output left in the field at harvest time or lost in transporting the harvested output to the point of weighing and recording. These amounts are never recorded as gross output and therefore need not be deducted; they represent losses of potential output rather than actual output. The second stage of losses, which should be deducted from reported output, is that output rendered either totally unusable or unusable in part by weather conditions (rain, frost, snow), by insect or disease 5" Soviet agricultural periodicals and monographs frequently refer to losses of these commodities. See for example, Ek selkhoz, no. 4, 1979, pp. 60-66.; Ek selkhoz, no. 1, 1978, p. 32.; Sel'skaya zhizn, 13 September 1972, p. 2.; Plan khoz, no. 7, 1978, pp. 44-55.; and N.M. Bashkirev, Organizatsiya proizvodstva, zagotovok i povy- sheniye kachestva yaits v ptitsevodcheskikh ob'yedineniyakh, Mos- cow, 1979. " Selkhoz 1971, p.682. damage, or by damage in harvesting. Combine har- vesting of potatoes, for example, reportedly damages 30 to 40 percent of output." Only part of the damaged product would be completely unusable; much would be usable as feed. Reported output should also be reduced by the amount of extraneous matter (weeds, stones, dirt, and so on) that is mixed with the har- vested crop at the time of weighing and recording. Transportation losses incurred in moving the product from the point of weighing and recording to initial storage should also be deducted. Storage losses, primarily spoilage or pest damage in storage facilities, are not relevant for purposes of calculating net output. Once the crop has been har- vested, cleaned, and initially stored, it is theoretically available for use on the farm, for processing, or for export. Subsequent losses in storage and shipping need not be deducted, although these are occasionally very large. Losses of potatoes, for example, in storage after harvesting have been estimated at 10 to 25 percent." B. Calculation of Waste in Sunflower Seed and Grain The CIA index of Soviet agricultural production makes an 8 percent discount for sunflower seed waste and a fluctuating discount for grain waste. Our estimate of sunflower seed waste is based on a Soviet source that cited the results of calculations for 1958. According to the author, the yield of sunflower seed after cleaning was 8 to 8.5 percent below the gross crop." No subsequent comparable data have been found." The allowance for grain waste is based on the premise that the level of waste fluctuates primarily according to the amount of precipitation during the two-month " Ibid. 37 Ek selkhoz, no. 11, 1979, p. 38. " Ek selkhoz, no. 6, 1959, p. 32. In the only other reference found, the author claimed that the yield after cleaning was 6 percent below the gross harvest in 1970 and 1971. We have not modified our discount because the deriva- tion of these percentages is unclear. The tabulation in which they appear includes production statistics that agree with official data. Sales and procurement statistics in the tabulation differ from those published elsewhere. Tresorukova, op. cit.,p. 53. 267 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 period immediately preceding and during harvest.' Wet harvesting conditions tend to raise moisture content of harvested grain to levels above internation- ally accepted standards. Excess moisture inflates bunker weight output statistics and increases chances of subsequent losses from spoilage. Although Soviet postharvest cleaning and drying is intended to restore, wet grain to full value, the wetter the harvesting conditions, the more difficult this becomes. Mishan- � dled wet grain may be grossly damaged or entirely _ _ _ spoiled for one or more of its intended uses. For the fall-sown winter grains, the months are June and July, and for spring grain, August and September. For each year in the index, the periods are categorized by degree of "wetness": very dry, dry, normal, wet, and very wet according to the average number of millime- ters of rainfall received, as follows: 61 Spring Wheat Winter Wheat Very wet Wet Over 45.8 Over 76.3 40.5 - 45.7 65.3 - 76.2 Normal 35.3 -40.4 53.8 - 65.2 Dry 29.6- 35.2 42.3 - 53.7 Very dry Below 29.5 Below 42.2 Each moisture category, in turn, is assigned a percent- age grain discount; a discount of 11 percent is adopted for years of normal precipitation.' We arbitrarily 6� The theory that variation from average precipitation during harvesting is the main determinant of moisture and foreign matter in harvested grain was set forth in U.S. Department of Agriculture, ,ERS, Methodology for Estimating Variations in Soviet Bunker Weight Grain Crops, 1975, (unpublished). Although the grain discount also includes extraneous matter and unripe and damaged kernels, no systematic separate methodology has been devised to measure them. Excess moisture is believed to be the largest and most variable component of waste with the greatest impact on trends in output. Amounts of damaged kernels also fluctuate widely, but they probably have a smaller impact on trends. Precipitation data are compiled by the US Air Force. Mean monthly precipitation data by oblast for each two-month period are weighted by the respective sown area of spring and winter wheat. " The average discount of 11 percent was derived indirectly from a rough calculation based on quality (feed unit or nutritive value) of concentrates fed on state and collective farms. (See A (ER) 75-68, 'pp. 13-15.) Because of the way the official series on concentrated feed is constructed, much of the exaggeration in Soviet grain production statistics resulting from excessive moisture, dirt, da- maged kernels, weed seeds, and the like, (waste), appears in the data on quantities of concentrates fed. Grain makes up roughly 85 percent of the total tonnage of concentrates fed (see ibid., p. 33). Our hypothesis is based on the difference between a) the average feed unit value of concentrates fed as derived from published Soviet raise this figure to 13 percent for wet years and to 15 percent for very wet years. In the other direction, 11 percent is lowered to 9 percent for dry years and to 7 percent for very dry conditions. The discounts for winter and spring grains are weighted together using 30 percent for winter grains and 70 percent for spring grains. These weights reflect the approximate per- centage of spring and winter grains in total output. 63 For 1950-59, weather related discounts must take into account the fact that 1950-54 official output statistics probably understate the actual crop. For 1950-54, therefore, the weather-related discount is not ap- plied.64 For 1955-59, the necessary monthly precipita- tion data are not available. For this period, the 1960 weather-related discount is moved back using an statistics (Selkhoz 1971, pp. 332-333) and b) an average feed unit value derived from the quantities of grain by type available for feed (from the grain balances) over the same years, 1961-70 pp. 25-29). We assume the assortment of grain actually fed is the same as that of estimated grain available for feed. When these tonnage figures are converted to feed units using standard Soviet norms (see G. V. Kulik, Spravochnik ekonomista kolkhoza i sovkhoza, Moscow, 1970, p. 538), the resulting average feed unit value is substantially higher than the average derived from the published series. The , discrepancy�which we attribute to waste including higher mois- ture�ranged from 12 percent to 21 percent over the 10-year period for which the data were available. Because we assume the waste level to be uniform for the entire crop on the supply side, the overall discount rate must be smaller. In crop year 1967/68, for example, the estimated waste in feed is 20 percent. The tonnage represents about 8 percent of grain produced in that year. Quantities of waste as shares of output ranged from 4.3 to 11.6 percent over the 10-year period; the average was 8 percent which we adopted as an average discount. To this we add a 3-percent allowance for losses in transportation and handling (A (ER) 75-68, p. 18). Although in theory subsequent losses of grain need not be applied for purposes of estimating net output, they are included in order to be consistent with our estimates of grain balances and grain fed. " We recognize that equating these moisture categories with specific waste levels implies a more precise and consistent relation- ship between precipitation and grain waste than actually exists in fact. To date, however, this is the most satisfactory, consistent methodology developed to measure fluctuations in grain waste. " Despite the presumed understatement in official Soviet grain output statistics in those years, excess moisture and waste existed. See, for example, the statement that waste, shrinkage in drying, and postharvest losses amounted to 5.1 percent of 1953 gross grain output in kolkhozes. (Al. Gozulov, Statistika sel'skogo kho- zyaystva, Moscow, 1959, p. 450.) See also Nancy Nimitz, RM- 4127-PR, Soviet Government Grain Procurements, Dispositions, and Stocks, 1940, 1945-63. Rand Corporation, November, 1964, p. 4. We omit the weather-related discount for these years in our estimates of net grain output only to compensate for the understate- ment in official statistics. We do not imply that these losses did not exist or that farm statistical reports did not contain bunker weight output data. 268 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 index of discounts proposed by Arcadius Kahan. " This results in discounts of official statistics that resemble the discounts implied by the comparisons in Table 4 of official and estimated output statistics. The index of discounts is also consistent with the belief of another writer that pre-1954 crop statistics are under- stated and that the years 1954-57 require smaller discounts than subsequent years." As Table 5 shows, with the exception of 1956, discounts derived in this manner are smaller for 1954-57 than for most other years in the sertes. Kahan uses a 6 percent discount for 1954, 7 percent for 1955 and 1957, and 10 percent for 1956, 1958, and 1959. These discounts suggest drier conditions in 1954, 1955, and 1957 than in 1956, 1958, and 1959, and are supported by a recent Soviet article on comparative precipitation levels in the major grain areas of the USSR.' The article lists the incidence of dry years in five major grain areas: European Russia, Ukraine, the "Volga Valley," Western Siberia and AltaS, kray, and Northern and Central Kazakhstan. During the 1950s, over 80 percent of area sown to grain was in the European USSR, the Ukraine, and parts of the Volga Valley. In all three major regions, 1954 and 1957 are listed as "dry years"; 1955 is listed as dry in the Volga Valley. On the other hand, 1956, 1958, and 1959 are listed as wet in two of the three major.grain areas of the 1950s, indicating the need for larger waste allowances. The second factor in the grain discount is the adjust- ment for crop size. Grain crops that are larger than average strain Soviet capacity to harvest, transport, clean, and dry the grain, especially when a large crop coincides with rainy weather at harvest time. We assume waste is larger under these conditions than when small harvests and dry weather coincide, as in 1975. To adjust the discount for crop size, we derive " See Kahan's article "Soviet Statistics of Agricultural Output," Soviet Agricultural and Peasant Affairs, (Roy Laird, ed.), Univer- sity of Kansas Press, Lawrence, Kansas, 1963. Luba 0. Richter, "Commentary" (on Arcadius Kahan's article), !bid, p. 165. " Yu. L. Rauner, lzvestiya akademii nauk SSSR, no. 6, 1976, pp. 37-54. the percentage difference between the actual crop as reported in Soviet sources, and the crop that would have resulted under average conditions." We use half of this percentage difference to adjust the weather-related discount. In this manner we account for that portion of the grain crop lost because of inadequate harvesting and processing capacity. In 1973, for example 2.0 percent is added to the weather- related discount to account for these losses. In 1975, on the other hand, the crop was small enough to be handled by existing capacity. In addition, the weather was dry. Thus, 1.2 percent is subtracted from the weather-related discount to account for minimum losses in that year. Table 5 shows the composition of the grain discount. VI. Deductions for Seed and Livestock Feed To measure agricultural output available for sale and home consumption, gross agricultural production should be reduced by the quantities of output used for seeding crops, feeding livestock, and for hatching poultry. The CIA index makes deductions for grain, potatoes, vegetables, and whole milk fed to livestock, eggs used for hatching, and quantities of grain and potatoes used for seed. Sunflower seed used for seed is not deducted because, according to seed norms, less than 1 percent of the crop is used for seed. Appendix C reports the methodological details and source refer- ences for these estimates. In the following discussion of seed and feed use, we are concerned with the implications of the estimates and their reliability. The trends in feed and seed use as a share of gross output are shown in table 6. Annual averages are used instead of data for individual years to smooth the year-to-year fluctuations in harvest size. The table shows seed use declining as a share of gross crop " Grain crops that would have resulted under average conditions (trend) are derived by first subtracting the moisture discount from gross grain output and dividing by sown area to derive "clean" yields. These yield figures are regressed against time to derive clean yields that would have been obtained under average conditions. Clean yields are multiplied by sown area and by 1.11 to derive an "average" gross harvest with a normal waste content of 11 percent. 269 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 5 USSR: Estimated Waste and Losses in the Gross Grain Harvest Percent Weather Related Crop Size Adjustment Total a 1950 1951 1952 1953 1954 1955 7.7 0.5 8.2 1956 10.8 1.0 11.8 1957 7.6 0.0 7.6 1958 10.1 1.4 11.5 1959 10.2 0.6 10.8 1960 9.8 0.2 10.0 1961 8.4 0.3 8.7 1962 7.6 0.0 7.6 1963 7.6 -1.1 6.5 1964 9.8 0.0 9.8 1965 7.6 -0.7 6.9 1966 8.2 0.5 8.7 1967 10.4 -0.2 10.2 1968 8.2 0.4 8.6 1969 13.0 -0.2 12.8 1970 13.8 1.1 14.9 1971 11.0 0.7 11.7 1972 9.6 -0.2 9.4 1973 14.4 2.0 16.4 1974 13.6 0.2 13.8 1975 9.0 -1.2 7.8 1976 13.0 0.7 13.7 1977 15.0 -0.4 14.6 1978 12.2 1.0 13.2 1979 12.4 -0.9 11.5 a Total is sum of columns 1 and 2. output. The same trend is observed if seed is taken as a share of only gross grain and potatoes. The trend implies increased output per unit of seed.� The reverse is true of intrasector use for livestock output. The share of deductions in gross output increases over time, even with hatching eggs removed from the series. This is consistent with our observation of increased use of grain for feed in recent years without proportionate increases in livestock output.' The increasing share of crop output used for feed also reflects the shift toward sale and home consumption of livestock products rather than direct consumption of crops. A. Grain and Potatoes Used for Seed Estimating seed use is a relatively straightforward process. Soviet data on sown area are multiplied by seeding rate norms to derive quantities of seed needed for grain and potatoes. We assume that actual seeding rates approximate those norms prescribed by Soviet guidelines for farm managers. The total includes area sown to grain in the fall but subsequently damaged by winterkill or used for winter and early spring grazing. The estimate also allows for corn area harvested as forage (silage, green feed, or dry fodder). Quantities required for fall seeding of grain and for spring seeding of grain and potatoes are deducted from gross output of grain and potatoes in the given year to derive net output. Gross grain output is first reduced by the grain discount to eliminate waste. No allowance is made for seeding of other crops. " Because the evidence indicates little or no reduction in seeding rates per hectare, nearly all the growth in output per unit of seed results from rising yields per hectare. Average overall grain yields for the three year period 1976-78 were 54'percent above the average yield in 1950-72. For the most part, this reflects a substantial increase in use of fertilizer on grain crops. For example, measured in standard units, the quantity of fertilizer used on grain increased from 2.2 million tons in 1960 to 14.6 million tons in 1970. (See ER 77-10557, The Impact of Fertilizer on Soviet Grain Output 1960-80, November 1977, p. 19.) '� Not only has the absolute quantity of grain fed been increasing, but since 1976, the share of feed units provided by concentrates, largely grain, has been increasing. For the most part, this trend reflects the failure of non-grain feed crops (silage, hay, etc.) to increase at the same rate. (See ER 79-10057, USSR: Long-Term Outlook for Grain Imports, January 1979, p. 19.) This trend was intensified during 1978/79 when the USSR was severely affected - by weather conditions that forced a further increase in the share of grain being fed. 270 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 6 Intrasector Use of Agricultural Output, Annual Averages, Selected Years Million 1970 rubles 1977-79 1950-52 1959-61 1964-66 1969-71 Seed Grain 2139.7 2478.2 2817.7 2624.4 2738.6 Potatoes 1818.7 1991.6 1841.4 1803.7 1525.8 Total 3958.4 4469.7 4659.1 4428.1 4264.4 Seed as a share of gross crop output 17.0 13.7 12.1 10.1 8.7 Feed and hatching eggs Grain 1298.8 3400.0 3852.2 6071.6 9308.6 Potatoes 1350.3 2370.9 2251.2 2467.5 2436.0 Vegetables 25.3 145.7 186.8 117.2 193.2 Milk 908.1 1574.5 1679.1 2221.3 2234.4 Total feed 3582.6 7491.1 7969.3 10877.6 14172.2 Hatching eggs 35.3 108.7 94.2 175.0 324.4 Total intrasector use 3617.9 7599.8 8063.5 11052.6 14496.6 Intrasector use as a share of gross livestock output 16.8 18.8 18.2 20.3 22.2 Shortcomings of the seed estimates center on the seeding rates. We use a constant seeding rate for the entire 1950-79 period whereas the actual rate prob- ably has changed over time. Evidence indicates, fur- thermore, that our seeding rates may be too low. One Soviet source claims that 20 centners per hectare of potatoes were seeded during 1962-65 and 25 centners during 1967-69.7' We estimate potato seeding at 19 centners per hectare for all years. In the case of grain,, a Soviet writer claims that seed use averaged 30.8 million tons per year during 1971-75." Our estimates show average seed use of 26 million tons during the period. The grain calculations may understate actual use because the norms refer to 'first-class' seed, which Estimating feed fed to livestock poses many more exceeds the quality of much seed grain." As of 1 problems than deriving estimates of seed use. The January 1979, for example, only 71 percent of seed CIA index includes the value of feed produced and used within agriculture such as hay, corn for silage, Zakupki sel'skokhozyaystvennykh produktov, no. 3, 1973, p. 18. feed roots, and pasture feed in the value of livestock 72 Plan khoz, no. 3, 1979, p. 38. See also, Pravda Ukrainy, 15 July 1979, p. 2, which argues that farms incorrectly increase the norms output. Although it would be more correct to add for seeding, and notes that increasing the norm does not make up their value to crop production and deduct it from for poor soil preparation, poor use of fertilizer, and so on. Zakupki sel'skozyaystvennykh produktov, no. 1, 1978, p. 6, implies that during 1971-75, farms sowed from 22 to 37 million tons annually. " First-class seed is seed with no more than 1 percent (by weight) content of broken kernels and admixtures and with viability not less than 95 percent. for spring grain and pulse crops met standards for first or second class seed." Presumably, the lower the seed quality the more seed is required for a given area. B. Estimates of Livestock Feed and Hatching Eggs We estimate quantities of grain, potatoes, vegetables, and whole milk fed to livestock. We do not estimate quantities of skim milk fed for reasons discussed below. Finally, although some fruit is fed to livestock in the USSR-largely because of marketing prob- lems-we make no estimates of the quantities because of data limitations." " /bid. "Statements are limited to "farms every year are forced to send millions of tons of fruit for feed" (Trud, 8 August 1967, p. 2); "as is known, the larger the fruit harvest, the bigger the share fed to cattle" (Plan khoz, no. 8, 1968, p. 59); and "a goodly share of fruit is fed to livestock" (Literaturnaya gazeta, no. I, 1973, p. 10). 271 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 livestock output along with other feeds produced in the crop sector, this is a difficult, if not impossible, task. Problems include lack of consistent and com- plete production data, extensive waste�particularly spoilage�of these products making it impossible to know how much of each would actually be fed, and the difficulty of deriving prices for products that to a large extent are not sold in the USSR. In any case, the index of total net output remains the same whether hay and other forage crops are included in livestock output or in output of the crop sector. Grain. Estimates of grain fed to livestock are based on the official Soviet series for concentrated feed fed to livestock. According to the Soviet definition, concen- trated feed includes grain, oilseed meals, dehydrated alfalfa or other high quality forage, and grain milling byproducts together with screenings and other ele- ments of usable waste such as damaged kernels from grain cleaning operations. Feeds of animal and syn- thetic origin are not included. The concentrates series is believed to reflect the excess moisture and waste found in harvested grain, bunker weight. To derive the grain component of concentrated feed, we subtract oilseed meal, grass meal, and grain milling byproducts from total concentrates. Conceptu- ally, the remainder consists of grain as well as the waste associated with the grain production series:6 To remove waste elements from grain fed, we allocate 80 percent of the quantity of grain written off in the " The residual may include small amounts of nongrain, nonoilseed products which go into the production of mixed feed such as meat, blood, and bone meals, fish meal, and vitamin and mineral supplements as well as ground hay and other materials with low feed energy value. Farms are required to report quantities of mixed feed fed as one of the components of the concentrates group. It is not known if the farm reduces the reported quantity of mixed feed fed to conform with the strict definition of concentrates. To the extent it does not, we are overstating the quantities of grain fed. The degree cannot be large, however. In 1978, total production of meat, blood, and bone meal was 475 thousand tons (Myasnaya industriya SSSR, no. 3, 1979, p. 6); production of fish meal averaged about 600 thousand tons during 1975-77 (information exchanged under the US-USSR Agricultural Agreement. No data for 1978 were transmitted.). grain discount (see above) to feed use.77 In this way, we estimate clean grain for feed that is compatible with the definition of clean grain on the output side. Although this procedure is arbitrary, it is consistent with the apparent low overall quality of Soviet grain used for feed. Estimates of grain fed for 1960 forward fit fairly well into our grain balance calculations.78 Official data on concentrates fed for the 1950s, however, are not available. Feed can be estimated by assuming that all grain not allocated to seed, food, industrial uses, and stocks is fed or by estimating the quantities of grain required to produce the livestock products and to maintain or increase herds in those years:9 We chose the second method because grain balance calculations show only small quantities avail- able for livestock feed and stock changes in many years of the 1950s. For several of these years, grain balance residuals are below the apparent amount of grain�along with standard norms of nongrain feeds�required to produce the livestock output ob- tained in those years. We have not reconciled these inconsistencies except to note that grain fed estimates for the 1950s are less reliable than those for later years. We believe the feed series based on concen- trates required to produce the output and to support changes in herds leads to a more reliable measure of the value of net livestock output in the 1950s than does a series based on grain balance residuals.' " We allocate the bulk of grain waste to feed because of the higher- than-average storage losses as well as a lesser degree of cleaning associated with grain for feed. Moreover, this would be expected under Soviet accounting procedures. Soviet farms often clean and dry drain that is to be marketed in order to avoid financial penalties for excess moisture and other elements of waste. Grain left on farms is not usually processed to the same extent. " See A (ER) 75-68. The balances are updated in ER 79-10057, USSR: Long-Term Outlook for Grain Imports, January 1979, p. 15. " The latter estimates are derived by multiplying the estimated quantity of grain required per unit of output times the quantities of livestock product produced annually in the 1950s. The estimates also take into account feed necessary to support livestock inventory change and to maintain horses. Soviet data are available on units of concentrated feed required per unit of output. See, for example, N. Burlakov, Ek selkhoz, no. 5, 1972, p. 36. We recognize that the amount of concentrates required per unit of output is not constant over time as implied by this methodology. Actual use of concen- trates depends on quantities of other feeds available to substitute for or complement the nutrient value of grains and other concen- trates as well as the mix within concentrates. However, data are not available to adjust for these fluctuations. Grain balances for the 1950s are of necessity far more crude and thus subject to larger error than those we have been able to develop for 1960 forward. 272 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Estimated quantities of grain and potatoes used for feed are lagged to be consistent with crop year data. The harvest of a given year is assumed to provide one- third of the feed used in that calendar year plus two- thirds of feed used in the subsequent calendar year. Although this assumption becomes less plausible in years of sharp crop fluctuations, we do not alter these shares over time. Potatoes. Estimating potatoes fed to livestock presents difficulties similar to those encountered in estimating grain fed in the 1950s. In the balance, subtracting seed, food, and industrial uses from reported produc- tion leaves insufficient quantities for feed use in five of the 11 years for which we have official Soviet statistics on quantities of potatoes fed to livestock. We believe that the data inconsistencies observed in the potato balance are caused by inaccuracy in Soviet potato statistics. Production statistics are subject to an especially large margin of error because 60 percent of potato output comes from private plots." Reporting of the potato crop in the socialized sector also involves estimation. After potatoes are harvested, they may not be removed from the fields but stored in pits or piles. In this case the weight of output is estimated by taking the dimensions of the pile and determining the weight of 1 cubic meter of stored potatoes. The amount of dirt and leaves in the output is estimated by weighing several samples before and after cleaning." The potato balance is distorted on the utilization side by the fact that ungarnered potatoes left in the field are consumed by livestock permitted to scavenge." Potatoes fed in this way are likely to be included in officially reported quantities of potatoes fed. This is true of all pasture feed provided to livestock without prior harvesting. The weight of "pasture feed" " See above for discussion of statistics of private agricultural output. " M. Z. Pizengol'ts, Bukhgalterskiy uchet v sel'skom khozyaystve, Moscow, 1974, pp. 111-112. " V.K. Radostovets et al., Spravochnik bukhgaltera sovkhoza i kolkhoza, Alma Ata, 1972, p. 31 "Pasture feed is broadly defined to include crop residues other than grass for pasture. Ibid. p. 354. M.Z. Pizengol'ts et al.. Bukhgal- terski uchet v sel'skokhozyaystvennyk predpriyatiyakh, Moscow, 1975, p. 94. consumed is determined by the farm's chief agrono- mist or zootechnician." The degree to which this causes understatement in gross output is probably not large." The question of quality of the potato crop also remains unresolved. According to the literature, large losses of potato production from spoilage occur." Earlier sources claim as much as one-fifth to one- third of the potatoes received by retail trade turn out to be unsaleable." The ranges in Soviet estimates of potato spoilage indicate the difficulty of developing any reasonable series of discounts over time. Any adjustment would merely add an arbitrary calculation without improving the measure. Moreover, applying any discount would throw the balance further out of line." Vegetables and Whole Milk Soviet data on feeding of vegetables to livestock are scarce; indeed, there are no published data on total vegetables fed. Conse- quently, our estimates have to be based on a crude balance. The few data available report vegetable feeding on state and collective farms only. Our vege- table balance is, for most years, fairly consistent with the few references available. Soviet statements such as "12 percent of vegetables produced by collective farms are fed by them," " and "1.8 million tons of vegetables produced in the communal sector were fed'"' are, as expected, below the quantities fed as implied by the balance. The understatement is prob- ably accounted for by vegetables fed by the private " Ibid., p. 354. " Raw potatoes are not particularly palatable. Chopping is recom- mended to increase palatability for cattle and sheep and cooking is recommended for hogs and poultry. "See above for a discussion of waste in potatoes. " Pravda, 25 August 1969, p. 2, Sovetskaya torgovlya, No. 9, 1971, p. 15. Some of this waste is returned to farms and fed. " Although not affecting our potato balance, another unresolved question is the accounting for potatoes sold to procurement organi- zations. Due to a lack of sufficient storage facilities a portion of procured potatoes is left on farms for storage. Every year an unknown part of this amount is used by farms themselves (Z. G. Tresorukova, op. cit., Moscow, 1974, p. 56). If quantities used by farms are not deducted from the earlier reported marketed output, procurements would be exaggerated. " L.T. Dageev, Podsobnyye promyshlenniye predpriyatiya v skom khozyaystve, Moscow, 1976, p. 14. 9' Pravda, 6 August 1966, p. 2. 273 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 sector which produces substantial quantities of vege- tables and may well feed some of the surplus. Vegeta- bles, however, are a small component of feed; error here does not have a significant impact on the overall index movement.' Whole milk fed to livestock can be estimated with a greater degree of confidence. Data for, whole milk fed on state and collective farms were published for a number of years. An occasional source has noted how much whole milk is fed by the private sector, usually in percentage terms. Finally, two sources have pro- vided benchmark data on total quantities of whole milk fed." Although estimates of whole milk fed can be made with acceptable confidence, the problem of accounting for skim milk fed remains. Roughly 60 percent of total milk production is purchased by the state; about one-half of that is used for manufacture of butter. While some of the resulting fluid skim milk is dried, much of it is returned to farms for use as feed." In a sense, this can be considered intrasector use since the chief criterion determining prices paid to farms for milk is butterfat content, not fluid quanti- ties, and the prices paid by farms for the returned skim milk are negligible." At any rate, we do not include an estimate of skim milk fed, although an average of 27.5 million tons of skim milk were reported fed during 1961-70.96 Any resulting bias is small; an arbitrary calculation incorporating an esti- mate of skim milk fed had almost no effect on the total estimated value of feed fed. Hatching eggs. In addition to estimating feed used in the production of livestock output, we also deduct for hatching eggs. These eggs, which amount to about 5 percent of all eggs produced, are required for hatching to produce poultry for meat and to increase poultry flocks. Few official Soviet data are available on the " To test the sensitivity of the index, the quantities of estimated vegetables fed were arbitrarily doubled. The change in value of all feed fed was negligible. "See Appendix Table C-10. "State farms, collective farms, and other state agricultural enter- prises, selling milk-to the state, have the right to receive skim milk according to norms set by the Councils of Ministers of the union republics. These norms differ according to republic and to type of farm. A.F. Bochalin and G.M. Rogozin, Spravochnik pa zakupkam produktov zhivotnovodstva, Moscow, 1974, pp. 179-183. "Farms are charged 10 rubles per ton. Ibid., p. 179. "USDA, ERS Foreign 355, Feed Balances for the USSR, (undated), p. 20. number of eggs used for hatching. The most recent Soviet statement, however, is consistent with our estimates." Our estimate is based on the increase in poultry flocks from year to year and the relationship between poultry meat output and the number of birds necessary to produce that quantity of meat. An allowance is made for mortality in young chicks and for eggs that fail to hatch. Hatching and mortality rates can be estimated from Soviet sources." Al- though the level of losses from both sources is higher than in the United States," we assume it is reasonable since the literature contains frequent references to problems in poultry management.m Hatching eggs are a relatively minor item in the index and errors here are not significant. No attempt is made to construct an egg balance to test the validity of the estimates. C. Testing the Estimates of Seed and Feed We tested our estimates of seed and feed against the Soviet input-output tables for 1966 and 1972. We compared the shares of gross output going to seed and feed use in our index with the shares shown by the input-output tables.'" Because the Soviet tables meas- ure gross output and value commodities produced and used within the sector at cost '" some adjustments had to be made to our index to achieve comparability. For the years 1966 and 1972, we valued all seed and feed produced in the crop sector at cost.'" Values at cost are included in output and in totals for feed use. We converted the CIA index of net crop production to a " In May 1979, an official of the Ministry of Procurement stated that the number of eggs used for incubation amounts to about 3 billion eggs for the USSR as a whole (Zhurnal(st, no. 5, 1979, pp. 41-43). Our estimate for 1978 is 3.2 billion. "See I.N. Zamyslov, Ekonomicheskaya otsenka otrasley zhivotno- rdstva, Moscow, 1973, p. 91; also, Spravochnik: promyshlennoye ptitsevodstvo, Moscow, 1971, pp. 48-116. "USDA, Agricultural Statistics 1978, Washington D.C., 1978, pp. 403, 414. See, for example, Finansy SSSR, no. 11, 1973, p. 28. - 'Data in the 1966 and 1972 input-output tables were converted to 1970 prices using indexes developed by Vladimir Treml. (See V.G. Treml, ed., Studies in Soviet Input-Output Analysis, Praeger Publishers, New York, 1972, pp. 218, 219, 272.) 102 Yu. E. Gaabe et al., Statistika sel'skogo khozyaystva, Moscow, 1971, p. 228. 1" This calculation does not include milk used for feed or eggs for hatching. 274 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 gross basis by eliminating the discounts and seed deductions from crop output. Gross livestock output is derived by eliminating the feed deduction. We then compared our index and the input-output tables for 1) the share of gross crop output used for feed, 2) the share of gross crop output used for seed, and 3) the proportion of feed from the crop sector in the gross value of livestock output. The results are summarized below: Share of gross crops used for feed Share of crops used for seed Crop-sector feed as a share of gross livestock output Percent 1966 1972 Soviet CIA Soviet CIA 28.3 16.7 23.7 20.5 8.8 6.8 9.6 6.8 23.9 12.7 19.7 12.6 The results of the comparison are consistent with known differences between the Soviet and CIA in- dexes, and suggest that our estimates of seed and feed use are reasonable. Considering the different compo- nents of the two indexes, the comparisons are fairly close. The rise in the share of seed use between 1966 and 1972 in the Soviet data may reflect a rise in seeding rates. We have already acknowledged that our use of a constant seeding rate probably is not accurate. Although both comparisons for feed shares indicate that our index understates feed use relative to Soviet measurements, the disparity between the shares narrowed between 1966 and 1972. This result is obtained partly because our crop index does not include hay and other feed produced and used entirely within agriculture. These feeds have increased more slowly than grain, and are a declining share of feed use. The share of grain, which is included in the CIA index, has risen. We show a rising share of crop output devoted to feed use and a constant share of livestock output consisting of feed inputs. Soviet data, on the other hand, show these shares dropping. How- ever, this trend may be due to lack of comparability between the 1966 and 1972 input-output tables.' It is more likely that these shares remained constant or rose between 1966 and 1972 than declined. In any case these comparisons should be regarded as general indications of the shares and not as precise measures. Intertemporal comparisons of the shares are especially tentative. VII. Sensitivity Tests To test the sensitivity of the index of Soviet agricul- tural production to various estimating procedures, we calculated several variants of the index by altering quantities and price weights. In general, procedures that raise the value of livestock sector output relative to crops, should raise the growth rate of net agricul- tural output, except in 1971-79 when growth in livestock output slowed significantly. Overall growth of farm output should drop when the relative share of the crop sector is raised. In any event, the index is generally insensitive to the tests we applied. None of the modifications had a material effect on the growth rates for the 1951-79 period as a whole. The results of the tests are presented in tables 7 and 8 in terms of the changes in growth rates and in shares of livestock products and crops in total output. To rank the sensitivity tests in order of their effect on the index, we calculated an average absolute percentage difference to measure the deviation of agricultural output under the sensitivity tests from the original 1" There is some evidence that the USSR's definition of sales by the crop sector to animal husbandry underwent a change between construction of the 1966 and the 1972 input-output tables. Sales by the flour and bread sector to animal husbandry are inexplicably low in the 1966 input-output table compared with the 1959 and 1972 tables. The hypothesis is that the crop sector sold material inputs directly to animal husbandry in 1966 rather than to the flour and bread sector for subsequent processing and resale to animal hus- bandry as was the case in 1972. Research on this subject has not been completed, but if the hypothesis proves correct, the shares for gross crops used for feed and crop sector feed as a share of livestock output as reflected in input-output tables are overstated in 1966 relative to 1972. 275 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 index in 1970 prices.'" The average absolute percent- age difference calculation provides an unambiguous measure of the variation among the indexes. These coefficients are shown in the last column of table 7. A. Use of Alternative Discounts and Feed Values In the first test, discounts for grain and sunflower seeds were removed from production and from feed use. In the second, output of these crops and quanti- ties fed were discounted at a flat rate of 20 percent for grain and 8 percent for sunflower seed. In the third variant, additional discounts were made for potatoes (10 percent), vegetables (15 percent), fruits (25 per- cent), sugarbeets (7 percent), eggs (3 percent).'" Pota- toes and vegetables fed were discounted by the same percentages. The fourth and fifth tests affected live- stock output directly. Feed was valued at cost of production in 1970 rather than at average realized prices for nonfeed uses on the assumption that most crops fed to livestock are not of sufficiently high quality to bring prices as high as average realized prices. In the fourth test, prices applied to changes in livestock inventory were adjusted each year for the variations in weight per procured animal over time.'" Major alterations in the discount for grain and sun- flower seed and the addition of discounts for other crops have little effect on the index of total net output. The average absolute percentage difference in all cases' is about 1 percent for total output. Large 1" Percentage difference (D) is calculated using indexes of output in the following equation: 1 1979 D = � 30 t = 1950 CIA index in 1970 prices � variation CIA index in 1970 prices 1" We adopted the 10 percent discount on potatoes used by Johnson and Kahan in their index, although Soviet sources indicate it may be too low. (D. Gale Johnson and Arcadius Kahan, "Soviet Agriculture: Structure and Growth," Comparisons of the United States and Soviet Economies, Joint Economic Committee, Con- gress of the United States, Washington, D.C., 1959). The discounts on vegetables, fruits, sugarbeets, and eggs are suggested by Soviet sources. 1" The CIA index rests on the assumption that animals in inventory are on average the same weight as those sold to procurement organizations. This assumption probably is acceptable except for very poor crop years the average weight of animals in inventory would not necessarily correspond to the average weight of animals sold. changes can be made in the discount without chang- ing trends in output growth. Removing the discounts accelerates the growth of crop output slightly except for 1971-79 and raises the share of crop output in total agricultural production. Removing the discount slows growth in livestock output, while the rate of growth for total output remains virtually unchanged. The flat discount of 20 percent on grain and 8 percent on sunflower seed reduces the share of crops in total output. Growth in crop output for the periods shown rises slightly because the weather-related discount was not applied in 1950-54 and is relatively large in 1970 and 1979. Additional discounts on other crops have little effect on the index. The average absolute percentage difference is very small, indicating that discounts on other crops do not affect trends significantly. Accounting for the variation in animal weight over time for purposes of measuring livestock inventory change causes no appreciable change in growth of livestock output. The average absolute percentage difference is 1.1 percent�less than that in crop output caused by altering the discounts. Error in total output is less than one percent. Because average slaughter weights show little change, using 1970 average realized prices to value all herd changes over time gives almost identical results to the more labori- ous process of adjusting the price each year for variations in animal weight. Valuing quantities of grain, potatoes, vegetables, and whole milk fed at average cost of production in 1970�the fifth test�does not change the value of net output available for sale and home consumption. The procedure lowers the value of crop output and raises the value of livestock output by the same amount. Growth in total output remains the same. Growth in livestock output as well as its share in total output, however, increases because feed deductions are small- er. Crop output grows more slowly when the feed portion of crop output is also valued at cost. B. Use of Alternative Price Weights Average absolute percentage difference calculations indicate that the shift to 1960 prices has the largest effect on the index. As table 8 shows, the share of crops is raised relative to livestock output. Since 1960, prices of livestock products have risen more than crop 276 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 7 Sensitivity Tests of CIA Index Average Absolute Percentage Difference Average Annual Percentage Rates of Growth 1951-79 1951-60 1961-70 1971-79 1970 prices' Net crops 2.4 2.6 3.7 0.7 Net livestock 3.7 6.1 3.7 1.0 Total 3.0 4.3 3.7 0.9 No discounts Net crops 2.6 3.1 3.9 0.5 .023 Net livestock 3.5 5.7 3.6 1.0 .010 Total 3.0 4.3 3.8 0.7 .007 Flat discounts on grain and sunflowers Net crops 2.5 2.9 3.9 0.6 .022 Net livestock 3.7 6.0 3.7 1.1 .008 Total 3.1 4.5 3.8 1.7 .008 Additional discounts on crops and eggs Net crops 2.4 2.6 3.7 0.7 .002 Net livestock 3.6 6.1 3.7 1.0 .002 Total 3.0 4.4 3.7 0.8 .002 Varying animal weight Net crops 2.4 2.6 3.7 0.7 Net livestock 3.7 5.9 3.9 1.0 .011 Total 3.0 4.2 3.8 0.8 .006 Feed valued at cost Net crops 2.0 2.0 3.5 0.2 .023 Net livestock 4.0 6.5 3.9 1.3 .012 Total 3.3 4.3 3.7 0.9 .002 1960 prices Net crops 2.5 2.5 4.0 0.8 .013 Net livestock 3.8 6.3 3.6 1.3 .068 Total 3.0 4.1 3.8 1.0 .012 277 ' 93-892 0 - 82 - 19 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 8 Sensitivity Tests of Shares of Net Output Percent 1950 1960 1970 1979 1970 prices Net crops 55 46 46 46 Net livestock 45 54 54 54 Total 100 100 100 100 No discounts Net crops 55 48 49 48 Net livestock 45 52 51 52 Total 100 100 100 100 Flat discounts on grain and sunflowers Net crops 52 45 46 44 Net livestock 48 55 54 56 Total 100 100 100 100 Additional discounts on crops and eggs Net crops 53 44 44 44 Net livestock 47 56 56 56 Total 100 100 100 100 Varying animal weight Net crops 54 46 46 46 Net livestock 46 54 54 54 Total 100 100 100 100 Feed valued at cost Net crops 54 44 43 40 Net livestock 46 56 57 60 Total 100 100 100 100 1960 Prices Net crops 62 53 54 53 Net livestock 38 47 46 47 Total 100 100 100 100 prices.'" As a result, the average absolute percentage difference is much larger for livestock output than for crops. 1" In 1962, prices paid to farms were raised for livestock, milk, eggs, and for some crops. Under the Brezhnev agricultural program, inaugurated in 1965, procurement price bonuses were established for quantities of agricultural produce delivered above the plan. Grain and milk prices were increased. In 1970, livestock prices went up and 50 percent price bonuses were introduced for sales above the plan for livestock, milk, eggs, and wool. In the 1965-1975 period, procurement prices rose by 70 percent for livestock products while crop prices rose by only 30 percent. Cattle prices rose by 77 percent and milk prices by 62 percent. Grain prices went up by only 41 percent during this period. (A. S. Baranov, Gosudarstvenniye zagatovki v usloviyakh spetsializatsii i konsentratsii serskokho- zyaystvennogo proizvodstva, Moscow, 1978, p. 162.) Within the livestock sector, however, when 1960 prices are used, growth accelerates sufficiently to offset the dampening effect of the increased share of crop output for all periods except 1951-60. Growth in livestock output is slower in 1970 prices than in 1960 prices because the largest price increases between these two years occurred in the slowest growing components of livestock output�herd inventories and meat production. Egg and poultry production posted the largest increases among livestock products be- tween 1960 and 1970, but the price increase for eggs was the smallest among livestock products. The share of poultry is too small to affect growth in totaj livestock output. VIII. Comparison of the CIA Index with Other In- dexes of Soviet Agricultural Production In this section we compare the CIA index with two Western indexes of Soviet agricultural production� one compiled by the Food and Agriculture Organiza- tion of the UN, and the other by the USDA. In addition, we contrast our index to the Soviet official index of gross agricultural output. Finally, we relate our index in terms of definitions and methodology to the US index of agricultural output compiled by the USDA. The following tabulation summarizes growth in Soviet agricultural production as measured by the various indexes. Average Annual Percentage Rates of Growth 1951-79 1951-60 1961-70 1971-79 Net output CIA index 3.0 4.3 3.7 1.5 USDA index 3.6 4.1 3.7 1.5 FAO index NA NA NA 0.9 Gross output Official Soviet index 3.2 4.8 3.3 1.4 CIA index 3.2 4.6 3.6 1.2 Each comparison is intended to define the extent and causes of the differences in the indexes. We then attempt to reconcile the indexes being compared. 278 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Our overall measure of variation is the average absolute percentage difference between the CIA index and each of the indexes being compared. The differ- ence calculation provides a less ambiguous measure of variation than comparisons of growth rates for arbi- trarily chosen periods. We supplement the difference calculations with measures of variations in growth rates and structure of output. We assess differences in sample coverage, estimating procedures, and price weights. The final step in the comparisons is to construct a variant of the CIA index that matches the index being compared as closely as possible. By eliminating as many differences as possible between the indexes, we are able to identify many of the factors that cause the indexes to grow at different rates. In most cases, for example, this reconstruction can eliminate differences in the indexes caused by different price weights. Average absolute percentage difference calculations are used to determine whether the reconstruction improved the match between CIA index and the indexes being compared with it. A. The Official Soviet Index of USSR Gross Agricul- tural Output The official Soviet index measures gross output of agriculture. Products used for seed and crops fed are counted as output of the crop sector; feed is also included in the value of livestock production. Al- though the value of agricultural output is overstated in the official index, our focus is on intertemporal comparisons between the two indexes and not on the overall magnitude of production measured in rubles. To compare the CIA and Soviet indexes of agri- cultural output, both must be on either a net or gross basis. Given the lack of Soviet statistics on uses of output, we chose to convert the CIA index to a gross basis rather than to create a net output index from Soviet data. The official Soviet index in 1965 comparable prices is compared with the CIA index of net agricultural output in 1970 prices and with the CIA index recon- structed to a gross output basis, weighted with Soviet 1965 comparable prices.'" The CIA index was calcu- lated on a gross basis by adding back the value of seed and feed and by eliminating the discounts on grain and sunflower seed. Our reconstructed index is not strictly comparable to the Soviet official index, how- ever. Although the Soviet index is nominally in constant prices, it is actually a "linked" index incor- porating several sets of price weights."� Data are not available to correct the official Soviet index for this deficiency. Furthermore, we did not allow for crops included in the official Soviet index but excluded from the CIA index. (See Table 2.) Table 9 shows that the average absolute percentage difference between the Soviet gross output index and the CIA net output index is 3.6. The difference is smaller for crops than for livestock, indicating that omissions from the CIA crop sample are not a source of serious bias in the index. Despite more similar coverage, the CIA index of livestock output is farther from the Soviet variation than is the index of crop output. The CIA measure of net output grows at approximately the same rate as the Soviet measure of gross output during the 1951-79 period, even though growth rates for crops and livestock in the two indexes do not agree well. Growth rates for total output match because differences in growth of crop and livestock indexes are offset by differences in CIA and Soviet weights used to aggregate crop and livestock output into total agricultural production. As table 10 shows, for the past two decades crops and livestock con- tributed equally to Soviet gross output while the CIA index (both gross and net) gave greater weight to " In the Soviet definition of comparable prices, marketed output is valued at actual sale prices while products used entirely within the sector are valued at cost. Private sector production that is not marketed is valued at the average price for marketed output of the particular commodity. A complete list of 1965 comparable prices used in the official Soviet index and in our reconstruction of the CIA index is found in F.E. Savitskiy et al., Spravochnik po planirovaniyu sel'skogo khozyaystva, Moscow, 1974, pp. 462-464. u� According to Soviet statistical handbooks, 1950 indexes are expressed in 1926/27 prices; 1951-55 are in 1951 prices; 1956-57 are in 1956 prices; 1958-64 are in 1958 prices; 1965-75 are in 1965 prices, and since 1976, the index has been calculated in 1973 prices. When a new set of price weights is introduced, the total ruble value of agricultural output is adjusted by one aggregate price index instead of a detailed set of deflators. The procedure is not equivalent to revaluing each item in the index in new prices. Trends in the official index, therefore, are affected by this imperfect transition from one set of price weights to another. 279 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 9 Comparison of CIA and Soviet Official Indexes of Agricultural Production Average Annual Percentage Rates of Growth Average Absolute Percentage Difference 1951-79 1951-60 1961-70 1971-79 Soviet official 1965 prices Total 3.2 4.8 3.3 1.4 Crops 2.8 4.1 3.3 0.8 Livestock 3.9 6.4 3.3 2.0 CIA-net output 1970 prices Total 3.0 4.3 3.7 0.9 .036 Crops 2.4 2.6 3.7 0.7 .013 Livestock 3.7 6.1 3.7 1.0 .074 CIA-gross output 1965 prices Total 3.2 4.6 3.6 1.2 .015 Crops 2.4 3.0 3.6 0.5 .012 Livestock 3.9 6.2 3.6 1.8 .018 livestock output. In 1979, largely as a result of the poor crop output, the share of gross output originating in the livestock sector increased relative to crops in the official Soviet index. The reconstruction of the CIA index on a gross basis with 1965 Soviet comparable prices eliminates differ- ences in growth rates for total output and livestock output for 1951-79. Growth rates do not match for intervening periods; differences are especially large for 1971-79. Furthermore, growth rates in the CIA and Soviet indexes of gross crop production remain far apart. In eliminating deductions for intrasector use of crops as a source of disparity, we discovered that the amount of deviation between the two indexes due to intrasector use is evidently small. Differences in sample coverage probably are responsible for much of the remaining difference between the two indexes. Average absolute percentage difference calculations reveal that despite occasional large differences in growth rates, the reconstructed CIA index of gross crop output is very close to the Soviet index. Although growth rate comparisons suggest more correspon- dence between the Soviet and CIA reconstructed livestock indexes, average annual difference calcula- tions indicate that trends in these indexes vary more than those in the crop indexes. However, on average, the CIA reconstructed gross output indexes of crops, livestock, and total output differ from the official index by less than 2 percent which is not material. Although the reconstruction of the CIA index on a gross basis reduced the average absolute percentage difference to 1.5 percent, the disparity in the weights for crops and livestock in total output increased. Eliminating the deduction of livestock feed from livestock production in the CIA index did not improve the correspondence between CIA and Soviet weights except for 1950. We attempted to eliminate some of the discrepancy by adding a rough estimate of the value of hay and green feed produced to crop output. As a result the share of crops rose from 46 to 47 percent. The shift to 1965 comparable prices caused growth of livestock output in the CIA index to accelerate sharp- ly in periods before 1960. Total output grows more slowly than the Soviet official measure, however. 280 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 10 Comparison of Structure of Output in Soviet and CIA Indexes, Percentage Shares 1950 1960 1970 1979 CIA index, 1970 prices (net output) Crops 55 46 46 46 Livestock 45 54 54 54 Total 100 100 100 100 CIA index, 1965 prices (gross output) Crops 58 46 46 43 Livestock 42 54 54 57 Total 100 100 100 100 Soviet official index (gross output) Crops 56 51 51 48 Livestock 44 49 49 52 Total 100 100 100 100 After 1960, the increased weight of the livestock sector causes the CIA index of gross output to grow faster than the Soviet index. The CIA measure of total gross agricultural output grows at 2.9 percent for, the 1961-79 period as a whole, while the Soviet index grows at 2.4 percent. Crop output grew more slowly than livestock output during the period. If the CIA index had a more complete crop sample, thus decreas- ing the weight of the livestock sector, growth in gross output would slow. B. The FAO Index The Food and Agriculture Organization (FAO) of the United Nations publishes annually an index of net agricultural output for the world as a whole and for 149 individual countries." The output indexes are weighted with 1969-71 average producer prices of the given country and incorporate deductions for seed, feed, hatching eggs, and for waste. The FAO index for the USSR Offers from the CIA index because changes in livestock inventories are excluded and because certain semiprocessed feeds such as bran and oilcake are deducted. Meat output in the FAO index, FAO Production Yearbook, Food and Agriculture Organization of the United Nations, Rome, 1979, Vol. 33, p. 78. 281 moreover, is registered in terms of liveweight. Sample coverage in our index and the FAO index is similar, especially for crops. In the livestock sector, however, the FAO index includes animal hides, cheese, dry milk, and other milk products. Table 11 compares the CIA and FAO indexes of net Soviet agricultural output for those years covered by the FAO index."' Although the CIA and FAO index- es have similar price weights, the average absolute percentage difference between the two indexes is 4 percent. When the change in livestock inventories is removed from the CIA index in 1970 prices, the CIA- FAO match is improved considerably; the direction of change becomes the same in each year; and the average difference falls to about 1 percent. Average annual rates of growth for the 1967-79 period as a whole differ slightly; removal of livestock inventory change eliminates the difference. In com- paring the 1971-76 period, the two indexes initially differ by a large amount. Again, however, the differ- ence is virtually eliminated when livestock inventory change is removed from the CIA index. Using growth rates to assess the similarity of these indexes is thus ambiguous. We place more weight on the average absolute percentage difference calculation that shows the FAO and reconstructed CIA indexes to be the best match achieved in any of our reconstructions. C. The USDA Index of Soviet Agricultural Output The USDA publishes indexes of agricultural produc- tion for Europe and the USSR."3 The index for the USSR is weighted with 1969-71 average prices re- ceived by farmers in Western Europe converted to US dollars at official exchange rates. Production data are official Soviet output statistics. A constant 38-percent "'The FAO revised the index in 1977. Data in earlier editions of lhe yearbook are not comparable with currently published data. Older versions of the index are weighted with 1961-65 average wheat-based price relatives. These weights are derived by express- ing the national producer prices for all commodities as a percentage of the national producer price of an equal weight of wheat. The older index included a greater number of processed products such as wine and refined sugar. " The current version of the index was published in May, 1981, after research for this paper was completed. Unpublished data � provided by USDA were used to compare the CIA and revised USDA indexes. The most recent USDA publication is Indices of Agricultural and Food Production for Europe and the USSR, ESCS, Statistical Bulletin no. 620, June 1979. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Sample coverage in the USDA index resembles that of the CIA index with some minor exceptions. The USDA index includes only sunflower seed in, oilcrop production. In livestock production, the USDA index omits production of honey, silk cocoons, other meat, and livestock inventory change. Table 11 Comparison of CIA and FAO Indexes of Soviet Agricultural Production, 1966-79 a FAO 1969-71 Prices CIA 1970 Prices CIA Less Livestock Inventory Change 1970 Prices 1966 91.2 86.6 89.2 1967 93.1 86.6 92.6 1968 97.1 91.7 97.7 1969 92.2 89.0 92.9 1970 100.0 100.0 100.0 1971 102.0 99.6 102.1 1972 97.1 94.0 99.3 1973 113.7 107.8 111.3 1974 108.8 106.5 111.0 1975 106.9 98.2 106.2 1976 111.8 106.1 110.9 1977 113.7 111.0 113.6 1978 122.5 114.6 119.0 1979 115.7 107.9 113.0 Average annual rates of growth (percent) 1967-70 2.3 3.7 2.9 1971-76 1.9 1.0 1.7 1967-79 1.8 1.7 1.8 Average absolute percentage difference .044 .012 1970=100 deduction is applied to the value of livestock output to account for use of domestic and imported feed. The feed share is estimated according to the relationship between the value of feeds (excluding forage) and the value of livestock products in 1969-71."4 No deduc- tions are made for seed use; grain and sunflower seed are not reduced by a waste allowance. "The USDA 38-percent share is higher than the share of crop- sector feed in livestock output as shown in the 1972 input-output table in current prices. Even when purchases by animal husbandry from the food industry are added, the share of feed in livestock output is still under 30 percent. Crop-sector feed as a share of livestock output in the CIA index is about 20 percent in the 1969- 71 period; it includes only feeds counted elsewhere in the index. In subtracting 38 percent of livestock output for feed, the USDA appears to be deducting more feed than is counted in the output index. Table 12 compares growth in the CIA and USDA indexes for the years 1950-79. For the period as a whole and for 1971-79 the USDA index shows faker growth in all categories. The USDA crop index places more weight on output of fruits and vegetables than on grain and potatoes. During 1951-79 fruit and vegetable production grew at an average annual rate of 5.1 percent while grain and potatoes grew by only 1.4 percent. The CIA crop index weights output of grain and potatoes more heavily than fruits and vegetables and therefore grows more slowly. The average absolute percentage difference for crops is only two percent, however, while the difference for livestock is almost 7 percent. To assess the effect of the differing methodologies, a variant of the CIA index was constructed using gross crop production, eliminating livestock inventory change, and applying a 38-percent feed allowance to the value of livestock output: This procedure reduced the difference for livestock significantly, but the difference for the crop series increased. By eliminat- ing grain discounts and seed deductions to create a variant of the CIA crop index definitionally com- parable to that of USDA, we increased the weight of grain and potatoes. The effect of this change was to widen the gap in growth between the two crop indexes. Table 13 compares the indexes in terms of crop and livestock shares of net agricultural output. Since 1960 the USDA index shows livestock as representing only about one third of total agricultural output whereas in the CIA index livestock has accounted for more than half of the total value of output since 1960. The CIA index constructed with USDA methodology increases the relative share of crops but this share is still below that in the USDA index. 282 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 12 Comparison of CIA and USDA Indexes of Soviet Agricultural Production Average Absolute Percentage Difference Average Annual Percentage Rates of Growth 1951-79 1951-60 1961-70 1971-79 USDA Index Crops 2.7 3.2 3.7 0.9 Net livestock 4.0 5.9 3.5 2.5 Total 3.1 4.1 3.6 1.5 CIA Index (net output, 1970 prices) Crops 2.4 2.6 3.7 0.7 .018 Livestock 3.7 6.1 3.7 1.0 .068 Total 3.0 4.3 3.7 0.9 .032 CIA Index (USDA methodology, 1970 prices) � Crops 2.3 2.8 3.5 0.4 .027 Livestock 4.0 6.1 3.3 2.4 .009 Total 2.9 4.0 3.4 1.2 .025 Table 13 Comparison of Structure of Output in CIA and USDA Indexes Percentage shares 1950 1960 1970 1979 USDA index Crops 70 64 65 62 Livestock 30. 36 35 38 Total 100 100 100 100 CIA index, 1970 prices Crops 55 46 46 46 Livestock 45 54 54 54 Total 100 100 100 100 CIA index in USDA methodology, 1970 prices Crops 66 58 59 54 Livestock 34 42 41 46 Total 100 100 100 100 The remaining differences between the indexes are caused by the differences in the price weights. In .using prices of Western Europe to value output, the USDA index "understates" somewhat the value of livestock products in terms of Soviet relative prices. Prices for most livestock products compared to crops are relatively lower in Western Europe than in the USSR. Relative prices for crops are more alike in the two systems although Western European grain and potatoes are cheaper relative to other food crops. Table 14 compares relative prices for selected com- modities in the two indexes. In each case, all prices are expressed as index numbers with the wheat price equal to 100. The table shows clearly the disparity in crop prices as opposed to livestock prices in the two systems. D. The US Index of Agricultural Output Both the CIA index of Soviet agricultural production and the official Soviet index of gross agricultural production can be compared with the US index of farm output, which measures farm output on'both a gross and a net basis.'' us A complete description of the US index is found in USDA, Major Statistical Series of the U.S. Department of Agriculture, vol. 2, 1970, pp. 15-17. The index is published on an annual basis in the USDA statistical handbook. Data for the most recent years are reported in USDA, Agricultural Statistics, 1978, Washington, D.C., 1978, p. 445. 283 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 14 Comparison of Relative Prices in CIA and USDA Indexes of Soviet Agricultural Production a USDA Index CIA Index Food crops Wheat 100.0 100.0 Rye 86.0 112.6 Barley 89.5 78.6 Potatoes 89.5 110.7 Vegetables 278.9 158.3 Fruits 200.0 273.8 Technical crops Cotton 1358.1 538.8 Sunflower seed 193.0 181.6 Fiber flax 789.5 2275.7 Livestock products Beef and veal 2021.1 2382.5 Pork 1875.4 2186.4 Poultry 1856.1 2299.0 Milk 177.2 190.3 Eggs 1628.1 176.7 Wool 3877.2 4514.6 a Wheat =100 The US gross output index includes seed and feed and is similar in other ways to the official Soviet index. In both indexes, the value of hay and harvested roughage (silage and forage) is included in crop production. Both include a large number of items with many more in the crop sample than in the livestock sample. The US index includes 111 individual crops and 29 items for the livestock sector. The US index covers 95 percent of total output, which is somewhat better coverage than our sample of Soviet agricultural pro- duction. The US and Soviet indexes also have in common the use of different price weights for differ- ent periods. The US index uses 1957-59 average realized prices for years since 1955, 1947-49 prices for 1939-53, and 1935-39 prices for years before 1939."6 The Soviet index is considerably more frag- mented. In the period 1950-1979, it incorporates prices of 1951, 1956, 1958, 1965, and 1973. The two indexes are based on quite different sources of data, however. The US index is based on sample survey data supplemented by probability sampling. The So- viet output statistics are theoretically a literal enu- meration of all production in collective farms and state agricultural enterprises, with the private sector output based on sampling. In estimating net farm output in the United States, the USDA encounters some of the same difficulties involved in constructing the CIA index of Soviet output. First, in both cases it was impossible to make complete deductions for all seed produced and used within agriculture. The US index deducts only hay- seed, pasture seed, and cover crop seed. No deductions are made for other types of seed. We deduct only seed for grain and potatoes from Soviet gross output. In both indexes, data are insufficient to deduct the value of pasture feed from livestock production. Although the US index excludes intrasector use of agricultural commodities in estimating net output, no allowance is made for waste. Waste, however, is a much less serious problem in US statistics than in Soviet statistics. "'Because more than one set of price weights is used in the index, the series is spliced in 1940 and 1955 using calculations both in old and new prices for those years. 284 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 APPENDIX A USSR: Derivation of Quantity Data Used in the Index of Soviet Agricultural Production This appendix lists the sources for the quantities used in the index of Soviet agricultual production. The index itself is shown in table A-1. Table A-2 summa- rizes the gross output data for crops; table A-3 contains data for output of livestock products and changes in livestock inventories. Gross output of grain and sunflower seeds is discounted for excess moisture and waste before it is used in the index, presented in table A-1. Grain Grain production is taken from official Soviet statis- tics, except for 1951 and 1952 which are estimates. The index uses unrounded data for nine individual types of grain. A figure for "other grain" is calculated by subtracting production of the nine types from the official total. Sources for statistics used in the index are listed below. Unless otherwise indicated, the source cited reports data to the nearest thousand tons for total grain production and for each individual type of grain. 1979: Vest stat, no. 9, 1980, p. 75. 1978: Vest stat, no. 10, 1979, p. 75. 1977: Vest stat, no. 10, 1978, p. 91. 1976: Vest stat, no. 9, 1977, p. 89. 1975: Narkhoz 1975, pp. 360-366 contains unrounded production data for all grains except oats and barley. For these grains, data are from USDA Foreign Agricultural Service reporting, SS 7003, 18 February 1977, p. 70. 1974: Production of all grains except rice is reported in Vest stat no. 10, 1975, p. 88. Rice production is reported in Narkhoz 1975, p. 365. 1973: Vest stat, no. 10, 1975, p. 88. 1973: Vest stat, no. 10, 1974, p. 88 reports unrounded production data for all grains except rice which is reported in Narkhoz 1975, p. 365. 1971: Narkhoz 1974 pp. 355-362 reports unrounded production data for all grains except oats, barley, and rice. Data for oats and barley are taken from Nar- khoz SSSR 1922-1972, p. 222, and data for rice from Narkhoz 1975, p. 365. 1960-70: Unrounded data for all years and for all types of grain are reported in Selkhoz 1971, pp. 154- 191. 1950, 1953-59: Unrounded ,data for all years and for all types of grain are found in Selkhoz 1960, pp. 202- 203. 1951-52: Figures for total grain production and for output of wheat and rye are reporting in Selkhoz 1971, p. 152. Production of other grains was estimat- ed using indexes of 1) total production, 2) wheat and rye output, and 3) the residual obtained by subtract- ing wheat and rye output from total grain production. Estimates of individual types of grain are as follows. Buckwheat, oats, pulses Output in 1950 is moved to 1951 and 1952 using an index of the residual obtained by subtracting wheat and rye output from total grain. Rice Output in 1951 and 1952 is arbitrarily held constant at the 1950 level. Corn for grain CIA/RR ER 64-33, Production of Grain in the USSR, p. 28. Barley Output in 1950 is moved to 1951 and 1952 using an index of total grain production. Millet An index of wheat output is used to move 1950 millet output to 1951 and 1952. 285 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Other grain Other grain is estimated for 1951 and 1952 by subtracting the production of nine individual types from the total. Potatoes 1976-79: Narkhoz 1979, p. 253. 1971-75: Narkhoz 1975, p. 371. 1950-70: Selkhoz 1971, p. 206. Vegetables 1976-79: Narkhoz 1979, p. 254. 1971-75: Narkhoz 1975, p. 373. 1950-70: Selkhoz 1971, p. 211. The total harvest is distributed by type of vegetable according to the percentage distribution of state pro- curements of vegetables by type. State procurement statistics are available for 1950, and 1960-70 in Selkhoz 1971 pp. 68-70 and in Selkhoz 1960 p. 103. Percentage distributions of procurements for 1951- 1959 are estimated by a straight-line interpolation of the 1950 and 1960 distributions. From 1971 forward, the 1970 percentage distribution is used. Figures for the production of vegetables by type in the socialized sector are available for recent years. Since these figures exclude the large quantity of vegetables pro- duced in the private sector, the 1970 distribution of total procurements is used. Fruits, berries, nuts 1975-79: Narkhoz 1979, p. 259. 1971-74: Narkhoz 1975, p. 381. 1960, 1965-70: Selkhoz 1971 p. 237. 1958, 1963-64: Narkhoz 1965, p. 297. 1953, 1959, 1961-62: Narkhoz 1962, p. P7. 1956-57: Selkhoz 1960, pp. 254, 256. 1955: Narkhoz 1960, p. 446. Published statistics for 1955 exclude citrus production. An arbitrary allow- ance of 40,000 tons has been added to the published figure. 1954: Calculated from average annual production for 1954-58 given in Narkhoz 1960, p. 375. An arbitrary allowance of 40,000 tons of citrus fruit was added to the official total. 1951-52: Straight line interpolation. 1950: Narkhoz 1967, p. 410. Sugarbeets (procurements) 1976-79: Narkhoz 1979, p. 256. 1971-75: Narichoz 1975, 376. 1950-70: Selkhoz 1971, p. 197. Cotton 1976-79: Narkhoz 1979, p, 250. 1972-75: Narkhoz 1975, p. 367. 1950-70: Selkhoz 1971, p. 194. Tobacco and Makhorka 1979: Vest slat, no. 9, 1980, p. 76. 1975-78: Narkhoz 1978, p. 203. 1\970-74: Narkhoz 1974, p. 319. 1960, 1965-70: Selkhoz 1971, p. 52. 1963-64: Narkhoz 1965, p. 268. 1961-62: Narkhoz 1962, p 239. 1950, 1953, 1955-59: Selkhoz 1960, p. 90. 1954: Calculated from annual average procurements for 1954-58 as given in Narkhoz 1962, p. 239. 1951-52: Straight line interpolation between 1950 and 1953. Sunflower seed 1976-79: Narkhoz 1979, p. 252. 1971-75: Narkhoz 1975, p. 370. 1950-70: Selkhoz 1971, p. 203. Soybeans 1979: Vest stat, no. 9, 1980, p. 76. 1978: Vest slat, no. 10, 1979, p. 75. 1977: Total .soybean production is estimated on the assumption that production in the ItSFSR accounts for 96 percent of the total,'as was the case in 1971-74. For these years, data on total production are available (see below). Data on RSFSR production for 1971-74 are from Narkhoz 1975, p. 209. Comparison of RSFSR and all-USSR production statistics shows that the annual average ratio of RSFSR production to total output is 96 percent. Data on 1977 production of soybeans in the RSFSR are found in Narkhoz RSFSR 1977, p. 123. 286 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 1976: Vest stat, no. 9 1977, p. 90. 1975: USDA Agricultural Situation: Review of 1978 and Outlook for 1979, Economics, Statistics, and Cooperatives Service, April 1979, p. 12. 1973-74: Vest stat, no. 10, 1975, p. 89. 1971-72: Vest stat, no 10, 1974, p. 89. 1960, 1965, 1970: Maslo-zhirovaya promyshlennost', no. 8, 1972, p. 8. 1963-64, 1966-69: Total soybean production is esti- mated on the assumption that RSFSR production accounts for 98 percent of total output (Ek selkhoz, no. 7, 1973, p. 46). Soybean production in the RSFSR for the relevant years is reported in Narkhoz RSFSR 1965, p. 243 and Narkhoz RSFSR 1969, p. 184. 1961-62: Straight line interpolation between 1960 and 1963. 1950, 1953-59: Selkhoz 1960, p. 202-203. 1951-52: Output in 1950 is moved forward to 1951 and 1952 using an index of sown area from Posevnyye ploshchadi SSSR, vol. 2, Moscow, 1957, p. 94. Other oilseeds This category includes castorbeans, mustard seed, flaxseed, hemp seed, tung nuts, peanuts, falseflax, rape, colza, sesame, and others. Output is estimated by subtracting production of soybeans and sunflower seeds form total oilseed output. Total oilseed produc- tion is reported in the following sources. 1975-79: Narkhoz 1979, p. 220. 1970-74: Narkhoz 1975, p. 318. 1950, 1960-69: Selkhoz 1971, pp. 148-149. 1953, 1959: Narkhoz 1962, pp. 234-235. 1956-58: Selkhoz 1960, pp. 26-27. 1955: Narkhoz 1960, p. 375. 1954: Calculated from 1954-58 average production given in Narkhoz 1960, p. 375. 1951-52: Estimated by moving 1950 total oilseed production forward with an index of sunflower seed production. Fibe, flax 1976-79: Narkhoz 1979, p. 120. 1971-75: Narkhoz 1975, p. 369. 1950-70: Selkhoz 1971, p. 201. Tea (procurements) 1975-79: Narkhoz 1979, p. 261. 1971-74: Narkhoz 1975, p. 382. 1960-70: Selkhoz 1971, p. 239. 1953, 1955-59: Selkhoz 1960, pp. 90, 257. 1951-52, 1954: Total tea procurements are estimated by moving 1950 procurements forward with an index of tea procurements in Georgia, which accounts for over 95 percent of Soviet tea procurements. Procure- ment figures for Georgia are found in Narodnoye khozyaystvo Gruzinskoy SSR v 1962 gody, Tbilisi, 1963, pp. 134-135. 1950: Strana sovetov za 60 let, Moscow, 1967, p. 147. Milk, eggs, wool 1979: Vest stat, no. 9, 1980, p. 79. 1978: Vest stat, no. 10, 1979, p. 78. 1954-77: Vest stat, no. 6, 1979, p. 66. 1953: Selkhoz 1960, p. 350, 355, 360. 1951-52: Narkhoz 1967, p. 332. 1950: Narkhoz 1965, p. 378, 474, 476. Honey 1979: Vest stat, no. 9, 1980, p. 79. 1978: Vest stat, no 10, 1979, p. 78. 1977: Vest slat, no. 10, 1978, p. 95. 1976: Vest stat, no. 9, 1977, p. 90. 1975: Straight line interpolation. 1973-74: Vest stat, no. 10, 1975, p. 95. 1972: Vest stat, no. 10, 1974, p. 93. 1972: Straight line interpolation 1950, 1960-70: Selkhoz 1971, p. 322. 1953, 1956-59: Selkhoz 1960, p. 333. 1951-52, 1954-55: Straight line interpolation Silk cocoons 1979: Vest stat, no. 9, 1980, p. 79. 1978: Vest stat, no. 10, 1979, p. 78. 1975-77: Narkhoz 1978, p. 203. 1965, 1970-74: Narkhoz 1975, p. 325. 1950, 1960 1966-69: Selkhoz 1971, p. 53. 1963-64: Narkhoz 1965, p. 268. 1961-62: Narkhoz 1962, p. 238. 1953, 1955-59: Selkhoz 1960, p. 91. 1954: Calculated using data on annual average pro- curements for 1954-58 and on annual procurements for 1955-58. 1951-52: Straight line interpolation. 287 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Meat Unrounded data for total meat production are readily available in Soviet statistical handbooks. Unrounded production statistics for each individual type of meat appear less consistently. Production of individual types is subtracted from the official figure for total meat output to derive "other" meat production. Stat- istics on total meat production are taken from: 1979: Vest stat, no. 9, 1980, p. 79. 1978: Vest stat, no. 10, 1979, p. 78. 1954-77: Vest stat, no. 6, 1979, p. 66. 1953: Selkhoz 1960, p. 338. 1951-52: Zhivotnovodstvo SSSR, Moscow, 1959, p. 161. 1950: Selkhoz 1960, p. 289. Production statistics for individual types of meat were drawn from the following sources. 1979: Vest stat, no. 9, 1980, p. 79. 1978: Vest stat, no. 10, 1979, p. 78. 1977: Vest stat, no. 10, 1978, p. 95. 1976: Vest stat, no. 9, 1977, p. 93. 1975: Narkhoz 1978, p. 250. 1973-74: Vest stat, no. 10, 1975, p. 95. 1972: Vest slat, no. 10, 1974, p. 93. 1971: Proizvodstvo produktov zhivotnovodstva v 1972 godu, Moscow, 1973, p. 10. 1950, 1960-1970: Selkhoz 1971, p. 290 1953, 1956-59: Selkhoz 1960, p. 333-335. 1954-55: Zhivotnovodstvo SSSR, Moscow, 1959, p. 159. 1951-52: Except for pork, statistics are from Narkhoz 1967, p. 332. The pork figure is found in Zhivotno- vodstvo SSSR, Moscow, 1959, p. 162. Livestock Investories, 1 January 1980: Pravda, 26 January, 1980. 1979: Narkhoz 1978, pp. 246-247. 1966, 1971, 1976-78: Narkhoz 1977, pp. 256-257. 1972-75: Narkhoz 1975, pp. 391-392, 395. 1951, 1961-65, 1967-70: Selkhoz 1971, pp. 246-249, 272. 1954-60: Selkhoz 1960, pp. 266-269, 320; and Nark- hoz 1960, p. 457. 1953: Zhivotnovodstvo SSSR, Moscow 1959, pp. 29, 31-33. 1950, 1952: Narkhoz 1967, p. 425. Figures for poul- try flocks for 1950, 1952, 1953, and 1956 are interpolated. 288 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 USSR: Value of Net Agricultural Output, 1950-79 Million rubles 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Total grain 6600.1 6168.0 7488.6 6404.4 6657.8 7700.1 8869.7 7256.4 9858.9 8564.8 Food grains 4205.0 4312.1 5055.8 4563.9 4803.8 4748.6 5962.6 5318.0 6973.1 6409.5 Feed grains 2395.1 1855.9 2432.8 1840.5 1854.0 2951.2 2907.1 1938.4_ 2985.8 2155.3 Potatoes 8253.3 4867.9 6109.9 . 6473.9 6666.0 6210.5 8953.6 7892.8 7801.0 7801.6 Vegetables 1345.8 1286.4 1435.4 1689.6 1783.4 2132.1 2185.3 2275.0 2312.8 2317.5 Oil crops 479.5 463.9 594.4 621.0 427.0 813.9 853.0 627.3 974.0 644.8 Fruits, berries, nuts 803.7 837.3 870.8 904.7 989.8 1080.1 970.1 1394.2 1366.6 1396.2 Sugarbeets 512.3 607.8 571.8 595.2 507.6 797.3 817.9 1001.9 1326.6 1075.6 Cotton - 1964.1 2068.5 2097.9 2138.4 2331.0 2154.0 2404.3 2337.1 2408.7 2578.0 Tobacco 123.1 137.7 152.3 169.0 194.0 169.0 164.8 212.8 208.6 233.6 Makhorka 50.1 ' 49.5 48.3 47.7 39.6 62.9 69.3 51.2 59.4 41.3 Fiber flax 597.7 452.4 499.3 379.7 511.0 893.1 1221.2 1031.4 1026.7 853.2 Tea 79.8 89.2 91.8 103.4 103.6 113.7 103.4 105.7 129.9 137.0 Total crops 20809.6 17028.5 19960.4 19527.0 20210.8 22126.5 26612.6 24185.8 27473.1 25643.5 Index (1970=100) 54.048 44.227 51.842 50.717 52.493 57.468 69.120 62.817 71.355 66.603 Annual growth (percent) - 0.0 -18.17 17.22 -2.17 3.50 9.48 20.27 -9.12 13.59 -6.66 Meat 11262.2 10887.7 11910.9 13557.0 14705.2 14830.7 15411.0 17181.1 17898.0 20715.1 Milk 6921.0 7095.2 6997.2 7149.1 7486.6 8429.8 9625.8 10731.0 11500.1 12096.3 Eggs 1169.7 1330.0 1440.0 1605.9 1717.9 1848.1 1953.2 2226.9 2304.0 2559.4 Wool 835.1 892.8 1018.3 1091.8 1069.5 1189.5 1214.1 1343.4 1496.4 1657.3 Honey 291.2 304.0 318.4 332.8 331.2 329.6 329.6 368.0 332.8 336.0 Silk cocoons 126.5 128.5 130.6 132.1 135.1 124.4 143.3 121.9 144.3 151.0 Livestock change 272.0 1709.1 -453.8 888.2 -191.5 1695.7 2595.1 3425.9 3053.5 2657.5 Gross livestock output 20877.6 22347.4 21361.6 24757.0 25254.1 28447.8 31272.1 35398.2 36729.1 40172.6 Net livestock output 17321.1 18740.5 17671.1 20743.1 20941.2 24360.5 26328.3 28668.4 29714.9 33045.1 Index (1970=100) 38.444 41.594 39.221 46.039 46.479 54.068 58.436 63.630 65.952 73.343 Annual growth (percent) 0.0 8.19 -5.71 17.38 0.96 16.33 8.08 8.89 3.65 11.21 Total net farm output 38130.6 35769.0 37631.6 40270.1 41152.0 46487.1 52940.9 52854.2 57188.0 58688.6 Index (1970=100) 45.634 42.808 45.037 48.195 49.250 55.635 63.359 63.255 68.442 70.237 Annual growth (percent) 0.0 -6.19 5.21 7.01 2.19 12.96 13.88 -0.16 8.20 2.62 Three-year moving average 37177.1 37890.2 39684.5 42636.4 46860.0 50760.7 54327.7 56243.6 57956.6 Index (1970=100) 46.264 47.151 49.384 53.058 58.314 63.168 67.607 69.991 72.122 Annual growth (percent) 0.0 1.92 4.74 7.44 9.91 8.32 7.03 3.53 3.05 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 USSR: Value of Net Agricultural Output, 1950-79 (continued) Million rubles ts.) �..0 0 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Total grain 9184.4 10278.5 11045.6 7665.9 11389.2 9012.5 13387.2 11120.4 13425.6 11884.0 Food grains 6024.6 6473.1 6916.1 4306.0 6625.2 5817.9 9302.5 7141.4 9053.6 6957.4 Feed grains 3159.9 3805.3 4129.5 3359.8 4764.0 3194.6 4084.7 3979.0 4372.0 4926.6 Potatoes 7638.0 7683.6 6058.8 6348.0 8834.1 8243.7 8197.5 9078.4 9851.0 8708.3 Vegetables 2625.2 2599.0 2571.7 2308.1 3016.4 2836.3 2907.3 3188.5 3050.2 3003.9 Oil crops 796.7 1006.0 1002.0 928.8 1235.6 1127.3 1332.0 1393.5 1402.3 1265.7 Fruits, berries, nuts 1393.6 1424.1 1685.8 1807.9 1936.2 2284.2 2201.0 2528.4 2995.1 2669.7 Sugarbeets 1357.1 1241.3 1142.6 1077.8 1979.2 1755.0 1812.6 2121.1 2188.4 1697.4 Cotton 2380.4 2507.5 2388.7 2891.5 2933.2 3142.4 3319.5 3313.3 3299.5 3167.9 Tobacco 214.9 208.6 212.8 254.5 383.8 352.5 371.3 448.5 448.5 406.8 Makhorka 40.7 19.2 17.5 16.3 25.0 25.0 22.1 18.6 26.8 22.7 Fiber flax 996.2 935.3 1012.6 890.7 811.0 1125.1 1080.6 1136.8 942.3 1141.5 Tea 153.9 151.9 168.2 183.9 182.1 185.2 223.9 220.3 215.3 229.9 Total crops 26781.2 28054.9 27306.2 24373.5 32725.9 30089.4 34855.0 34567.9 37844.8 34197.8 Index (1970=100) 69.558 72.866 70.921 63.304 84.997 78.150 90.527 89.782 98.293 88.821 Annual growth (percent) 4.44 4.76 -2.67 -10.74 34.27 -8.06 15.84 -0.82 9.48 -9.64 Meat 20359.3 20256.9 22002.4 23687.8 19334.2 23111.6 24924.9 26857.7 27282.6 27683.6 Milk 12096.7 12262.7 12530.5 12004.6 12399.4 14222.3 14894.4 15664.3 16129.8 15981.8 Eggs 2746.4 2930.9 3008.9 2852.3 2669.4 2906.8 3167.2 3392.1 3567.9 3719.0 Wool 1659.1 1703.3 1727.0 1733.1 1584.3 1659.6 1724.7 1834.4 1930.2 1812.1 Honey 337.0 396.8 328.0 350.4 342.4 306.4 , 365.3 337.8 326.6 285.8 Silk cocoons 151.5 ' 147.4 156.1 172.9 169.8 177.5 177.0 188.2 184.1 182.1 Livestock change 1459.8 4462.3 2844.7 -6476.0 2541.7 4278.2 1696.9 -1043.1 -777.6 793.6 Gross livestock output 38809.8 42160.3 42597.6 34325.0 39041.1 46662.4 46950.3 47231.4 48643.6 50458.0 Net livestock output 31211.8 34086.2 34005.8 26262.6 31898.0 39083.3 37482.3 37753.0 38747.1 40126.6 Index (1970=100) 69.275 75.654 75.476 58.290 70.797 86.745 83.192 83.793 85.999 89.061 Annual growth (percent) -5.55 9.21 -0.24 -22.77 21.46 21.53 -4.10 0.72 2.63 3.56 Total net farm output 57993.1 62141.1 61312.0 50636.1 64623.8 69172.6 72337.3 72321.0 76591.9 74324.4 Index (1970=100) 69.405 74.369 73.377 60.600 77.341 82.785 86.572 86.552 91.664 88.950 Annual growth (percent) -1.19 7.15 -1.33 -17.41 27.62 7.04 4.57 -0.02 5.91 -2.96 Three-year moving average 59607.6 60482.0 58029.7 58857.3 61477.5 68711.2 71276.9 73750.1 74412.4 78157.9 Index (1970=100) 74.177 75.265 72.214 73.243 76.504 85.506 88.699 91.776 92.601 97.262 Annual growth (percent) 2.85 1.47 -4.05 1.43 4.45 11.77 3.73 3.47 0.90 5.03 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-1 USSR: Value of Net Agricultural Output, 1950-79 (continued) Million rubles ts..) .c. 1-... 1975 1977 1970 1971 1972 1973 1974 1976 1978 1979 Total grain 13657.2 13911.7 12956.9 16293.9 14383.2 10466.8 16450.8 14109.8 17966.9 13340.6 Food grains 8777.9 9228.5 7981.8 9663.8 7956.4 6241.8 9004.3 8021.5 11237.4 8284.8 Feed grains 4879.3 4683.2 4975.1 6630.1 6426.9 4225.0 7446.5 6088.4 6729.5 5055.8 Potatoes 9286.6 8852.8 7219.7 10598.3 7507.4 8398.4 8166.6 8005.6 8292.8 8860.1 Vegetables 3460.0 3399.4 3252.2 4227.6 4047.1 3808.7 4076.3 3938.9 4549.5 4437.2 Oil crops 1303.6 1218.5 1021.6 1517.8 1371.7 1121.6 1126.3 1229.1 1180.0 1149.3 Fruits, berries, nuts 3296.6 3470.6 2698.7 3765.0 3508.4 4014.3 4303.3 4307.5 4053.5 4597.4 Sugarbeets 1856.0 1672.6 1769.1 2022.8 1754.6 1608.9 2213.7 2206.6 2081.6 1801.8 Cotton 3823.9 3941.1 4049.3 4253.5 4667.0 4364.5 4594.3 4860.7 4717.5 5084.4 Tobacco 475.6 479.8 573.6 569.5 609.1 598.7 623.7 625.8 569.5 615.4 Makhorka 17.5 14.0 9.9 15.1 10.5 5.2 7.0 4.1 4.1 2.9 Fiber flax , 1068.9 1139.2 100.9 1038.4 942.3 1155.6 1193.1 1125.1 881.3 743.0 Tea 256.3- 263.4 273.6 287.1 310.1 331.2 352.9 408.1 426.6 451.2 Total crops 38502.2 38363.0 34893.5 44589.0 39111.3 35873.8 43108.0 40821.5 44723.3 41083.5 Index (1970-100) 100.000 99.639 90.628 415.809 101.582 93.174 111.963 106.024 116.158 106.704 Annual growth (percent) 12.59 -0.36 -9.04 27.79 -12.28 -8.28 20.17 -5.30 9.56 -8.14 Meat 28797.7 31095.5 32150.8 31828.1 34402.8 35378.1 32390.0 34762.2 36557.3 36517.0 Milk 16271.1 16303.9 16303.5 17306.8 17985.0 17797.6 17576.3 18606.1 18556.7 18294.8 Eggs 4074.0 4510.0 4791.0 5115.4 5550.9 5736.7 5618.7 6119.4 6451.7 6558.5 Wool 1947.9 1993.9 1953.5 2014.8 2146.4 2169.7 2025.1 2134.3 2171.5 2194.8 Honey 336.0 315.2 294.4 353.6 318.9 310.4 300.8 332.8 286.4 302.4 Silk COCOCIAS 171.9 187.2 211.1 203.5 197.4 199.4 230.0 219.8 237.1 239.7 Livestock change 4366.8 2341.6 -99.0 1974.6 1973.4 -2084.8 832.3 2803.2 1509.6 738.6 Gross livestock output 55965.3 56747.3 55605.3 58796.9 62574.7 59507.0 58973.2 64977.9 65770.4 64845.9 Net livestock output 45055.3 44830.7 43648.0 45495.3 50730.0 46141.8 45534.9 51932.3 51057.1 49114.9 Index (1970=100) 100.000 99.502 96.877 100.977 112.595 102.412 101.064 115.264 113.321 109.010 Annual growth (percent) 12.28 -0.50 -2.64 4.23 11.51 -9.04 -1.32 14.05 -1.69 -3.80 Total net farm output 83557.4 83193.7 78541.6 90084.3 89841.3 82015.7 88642.9 92753.8 95780.4 90198.4 Index (1970=100) 100.000 99.565 93.997 107.811 106.520 98.155 106.086 111.006 114.628 107.948 Annual growth (percent) 12.42 -0.44 -.5.59 14.70 -0.27 -8.71 8.08 4.64 3.26 -5.83 Three-year moving average 80358.5 81764.2 83939.8 86155.7 87313.7 86833.3 87804.1 92392.4 92910.9 90731.8 Index (1970=100) 100.000 101.749 104.457 107.214 108.655 108.057 109.265 114.975 115.620 112.909 Annual growth (percent) 2.82 1.75 2.66 2.64 1.34 -0.55 1.12 5.23 0.56 -2.35 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 Gross Output of Crops Used in CIA Index of Soviet Agricultural Output Thousand metric tons N.) �.0 l�-) Prices a 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Wheat" 103. 31076.0 32400.0 43800.0 41276.0 42399.0 47289.0 67380.0 58113.0 76568.0 69101.0 Rye" 116. 17961.0 19400.0 15500.0 14514.0 15590.0 16475.0 14096.0 14467.0 15737.0 16902.0 Buckwheat b 306. 1329.0 1000.0 1200.0 762.0 935.0 1253.0 1285.0 769.0 664.0 381.0 Rice" 306. 202.0 200.0 200.0 222.0 222.0 246.0 250.0 211.0 216.0 214.0 Corn for grain" 138. 6644.0 4400.0 5700.0 3697.0 3699.0 11574.0 9861.0 4621.0 10226.0 5653.0 Oats" 82. 13005.0 10000.0 12900.0 10074.0 10799.0 11827.0 13218.0 12729.0 13407.0 13463.0 Barley b 81. 6354.0 6400.0 8200.0 7875.0 7764.0 10350.0 12903.0 8480.0 12957.0 10150.0 Millet b 81. 1705.0 3200.0 2500.0 2681.0 3013.0 2956.0 4556.0 1559.0 2880.0 1299.0 Pulses b 113. 2048.0 1300.0 1700.0 1122.0 923.0 1345.0 1018.0 1284.0 1577.0 1907.0 Other grain" 61. 876.0 400.0 500.0 264.0 224.0 372.0 384.0 406.0 490.0 468.0 Total grain 81200.0 78700.0 92200.0 82487.0 85568.0 103687.0 124951.0 102639.0 134722.0 119538.0 Potatoes" 114. 88612.0 58754.0 69189.0 72572.0 75021.0 71751.0 96015.0 87813.0 86527.0 86561.0 Beets 108. 589.0 548.0 596.0 683.0 703.0 818.0 815.0 827.0 818.0 798.0 Cabbage 95. 4364.0 4065.0 4427.0 5091.0 5244.0 6105.0 6091.0 6187.0 6139.0 5998.0 Carrots 153. 551.0 521.0 567.0 661.0 679.0 790.0 / 801.0 827.0 818.0 798.0 Cucumbers 212. 626.0 636.0 753.0 934.0 1037.0 1297.0 1401.0 1521.0 1605.0 1669.0 Onions 430. 533.0 530.0 606.0 740.0 799.0 987.0 1044.0 1107.0 1159.0 1182.0 Tomatoes 168. 2261.0 2138.0 2375.0 2756.0 2896.0 3440.0 3474.0 3588.0 3612.0 3605.0 Other vegetables 99. 420.0 - '398.0 450.0 524.0 560.0 663.0 672.0 709.0 714.0 724.0 Total vegetables 163. 9344.0 8836.0 9774.0 11389.0 11918.0 14100.0 14298.0 14766.0 14865.0 14774.0 Fruits, berries 282. 2850.0 2969.0 3088.0 3208.0 3510.0 3830.0 3440.0 4944.0 4846.0 4951.0 Sugarbeets 26. 19705.0 23377.0 21991.0 22891.0 19523.0 30664.0 31457.0 38535.0 51023.0 41369.0 Cotton 555. 3539.0 3727.0 3780.0 3853.0 4200.0 3881.0 4332.0 4211.0 4340.0 4645.0 Tobacco 2086. 59.0 66.0 73.0 81.0 93.0 81.0 79.0 102.0 100.0 112.0 Makhorka 582. 86.0 85.0 83.0 82.0 68.0 108.0 119.0 88.0 102.0 71.0 Sunflower seed b 187. 1654.2 1599.9 2028.6 2419.6 1756.3 3493.2 3631.2 2576.9 4255.9 2777.5 Soybeans 260. 166.0 145 0 _ � 142.0 172.0 56.0 151.0 114.0 162.0 229.0 224.0 Other oil crops 402. 316.0 316.0 443.0 308.0 209.0 302.0 359.0 257.0 295.0 167.0 Total oil crops 203. 2136.2 2060.9 2613.6 2899.6 2021.3 3946.2 4104.2 2995.9 ' 4779.9 3168.5 Fiber flax 2344. 255.0 193.0 213.0 162.0 218.0 381.0 521.0 440.0 438.0 364.0 Tea 940. 84.9 94.9 97.7 110.0 110.2 121.0 110.0 112.4 138.2 145.7 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-2 Gross Output of Crops Used in CIA Index of Soviet Agricultural Output (continued) Thousand metric tons ts.) V) t...) Prices a 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Wheat" 103. 64299.0 66483.0 70778.0 49688.0 74399.0 59686.0 100499.0 77419.0 93393.0 79917.0 Rye" 116. 16357.0 16716.0 17024.0 11878.0 13619.0 16228.0 13146.0 12986.0 14120.0 10945.0 Buckwheat" 306. 639.0 867.0 871.0 498.0 714.0 950.0 935.0 1175.0 1472.0 1375.0 Rice b - 306. 186.5 246.8 272.1 376.5 470.6 583.4 712.1 895.4 1063.2 1106.9 Corn for grain b 138. 9823.0 17113.0 15474.0 111410 13849.0 8030.0 8416.0 9163.0 8828.0 11954.0 Oats" 82. 11999.0 8900.0 5691.0 3965.0 5519.0 6186.0 9199.0 11581.0 11639.0 13070.0 Barley b 81. 16021.0 13338.0 19549.0 19804.0 28597.0 20304.0 27879.0 24662.0 28904.0 32652.0 Millet" 81. 3230.0 2887.0 2783.0 1835.0 3485.0 2205.0 3101.0 3218.0 2660.0 3289.0 Pulses b 113. 2706.0 4036.0 7579.0 8029.0 11110.0 6689.0 7031.0 6550.0 7212.0 7846.0 Other grain b , 61. 229.5 203.2 161.9 275.5 308.4 279.6 265.9 237.6 248.8 247.1 Total grain 125490.0 130790.0 140183.0 107492.0 152071.0 121141.0 _ _ _ _ 171184.0 147887.0 169540.0 162402.0 Potatoes b 114. 84374.0 84310.0 69677.0 71834.0 93642.0 88676.0 _ 87853.0 95464.0 102184.0 91779.0 Beets 108. 878.0 711.0 688.0 697.0 895.0 917.0 1018.0 1006.0 1046.0 1125.0 Cabbage 95. 6613.0 6137.0 6140.0 5879.0 7125.0 6504.0 6054.0 7577.0 6369.0 6298.0 Carrots 153. 878.0 877.0 861.0 682.0 1129.0 987.0 964.0 1047.0 1103.0 1331.0 Cucumbers 212. 1956.0 1631.0 1487.0 1515.0 2219.0 1410.0 1750.0 2053.0 1787.0 1725.0 Onions 430. 1376.0 1421.0 1471.0 1000.0 1246.0 1639.0 1661.0 1417.0 1559.0 1575.0 Tomatoes 168. 4044.0 4587.0 4429.0 4294.0 5587.0 5129.0 5143.0 6078.0 5893.0 5436.0 Other vegetables 99. 829.0 792.0 911.0 984.0 1266.0 1041.0 1267.0 1356.0 1254.0 1255.0 Total vegetables 163. 16574.0 16151.0 15989.0 15051.0 19467.0 17627.0 17857.0 20534.0 19011.0 18745.0 Fruits, berries 282. 4942.0 5050.0 5978.0 6411.0 6866.0 8100.0 7805.0 8966.0 10621.0 9467.0 Sugarbeets 26. 52198.0 47742.0 43946.0 41455.0 76124.0 67500.0 6015.0 81579.0 84168.0 65283.0 Cotton 555. 4289.0 4518.0 4304.0 5210.0 5285.0 5662.0 5981.0 5970.0 5945.0 5708.0 Tobacco 2086. 103.0 100.0 102.0 122.0 184.0 169.0 178.0 215.0 215.0 195.0 Makhorka 582. 70.0 33.0 30.0 28.0 43.0 43.0 38.0 32.0 46.0 39.0 Sunflower seed " 187. 3049.6 4372.8 4411.4 3942.2 5573.4 5013.1 5658.0 6079.4 6150.2 5849.4 Soybeans 260. 167.0 336.0 392.0 448.0 286.0 421.0 590.0 548.0 531.0 437.0 Other oil crops 402. 176.0 251.0 187.0 187.0 296.0 200.0 300.0 284.0 284.0 145.0 Total oil crops 203. 3992.6 4959.8 4990.4 4577.2 6155.4 5634.1 6548.0 6911.4 6965.2 6431.4 Fiber flax 2344. 425.0 399.0 432.0 380.0 346.0 480.0 461.0 485.0 402.0 487.0 Tea 940. 163.7 161.6 178.9 195.6 193.7 197.0 238.2 234.4 229.0 244.6 Approved for Release: 2019/07/19 C05210421 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-2 Gross Output of Crops Used in CIA Index of Soviet Agricultural Output (continued) Thousand metric tons l�-) vD -P. Prices a 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Wheat" 103. 99734.0 98760.0 85993.0 109784.0 83913.0 66224.0 96882.0 92200.0 120820.0 90207.0 Rye" 116. 12972.0 12787.0 9633.0 10759.0 15223.0 9064.0 13991.0 8471.0 13607.0 8113.0 Buckwheat" 306. 1081.0 1170.0 811.0 1304.0 974.0 485.0 897.0 1038.0 985.0 836.0 Rice" 306. 1279.3 1429.5 1647.2 1765.0 1913.3 2009.3 2001.0 2220.0 2110.0 2394.0 Corn for grain b 138. 9428.0 8597.0 9830.0 13216.0 12104.0 7328.0 10138.0 10993.0 8951.0 8373.0 Oats" 82. 14203.0 14600.0 14100.0 17516.0 15302.0 12495.0 18113.0 18379.0 18600.0 15162.0 Barley" 81. 38200.0 34600.0 36800.0 55044.0 54208.0 35808.0 69539.0 52653.0 62077.0 47954.0 Millet" 81. 2100.0 2043.0 2123.0 4416.0 2907.0 1125.0 3198.0 2009.0 2210.0 1553.0 Pulses" 113. 7619.0 6948.0 7103.0 8447.0 8714.0 5321.0 8651.0 7477.0 7748.0 4343.0 Other grain b 61. 179.0 240.0 198.0 279.0 450.0 259.0 345.0 260.0 282.0 241.0 Total grain 186795.3 ' 181174.5 168238.2 222530.0 195708.3 140118.3 223755.0 195700.0 237390.0 179176.0 Potatoes" 114. 96783.0 92655.0 78329.0 108200.0 81022.0 88703.0 85102.0 83652.0 86124.0 90956.0 Beets 108. 1188.0 1167.0 1117.0 1451.9 1389.0 1308.0 1400.0 1352.0 1563.0 1524.0 Cabbage 95. 7488.0 7356.0 7037.0 9147.0 8733.0 8243.0 8822.0 8525.0 9794.0 9552.0 Carrots 153. 1294.0 1271.0 1214.0 1576.4 1513.0 1424.0 1524.0 1473.0 1702.0 1660.0 Cucumbers 212. 2291.0 2250.0 2154.0 2800.1 2680.0 2522.0 2699.0 2608.0 3013.0 2939.0 Onions 430. 2015.0 1980.0 1892.0 2457.9 2357.0 2218.0 23/4.0 2294.0 2651.0 2585.0 Tomatoes 168. 5558.0 5462.0 5231.0 6800.7 6500.0 6118.0 6548.0 6327.0 7282.0 7103.0 Other vegetables 99. 1378.0 1354.0 1296.0 1693.0 1639.0 1518.0 1624.0 1570.0 1897.0 1851.0 Total vegetables 163. 21212.0 20840.0 19941.0 25927.0 24811.0 23351.0 24991.0 24149.0 27902.0 27215.0 Fruits, berries 282. 11690.0 12307.0' ''. 9570.0 13351.0 12441.0 14235.0 15260.0 15275.0 14374.0 16303.0 Sugarbeets 26. 71385.0 64329.0 68043.0 77799.0 67484.0 61880.0 85142.0 84869.0 80061.0 69300.0 Cotton 555. 6890.0 7101.0 7296.0 7664.0 8409.0 7864.0 8278.0 8758.0 8500.0 9161.0 Tobacco 2086. 228.0 230.0 275.0 273.0 292.0 287.0 299.0 300.0 273.0 295.0 Makhorka 582. 30.0 24.0 17.0 26.0 18.0 9.0 12.0 7.0 7.0 5.0 Sunflower seed b 187. 5652.5 52 f 0.0 4644.2 6794.2 6241.3 4590.8 4854.8 5431.7 4906.4 4980.9 Soybeans 260. 602.0 536.0 258.0 424.0 360.0 780.0 480.0 524.0 634.0 467.0 Other oil crops 402. 224.0 261.0 214.0 341.0 276.0 150.0 233.0 192.0 243.0 240.0 Total oil crops 203. 6478.5 6007.0 5116.2 7559.2 6877.3 5520.8 5567.8 6147.7 5783.4 5687.9 Fiber flax 2344. 456.0 486.0 456.0 443.0 402.0 493.0 509.0 480.0 376.0 317.0 Tea 940. 272.7 280.2 291.1 305.4 329.9 352.3 375.4 434.2 453.8- 480.0 a 1970 average realized prices; rubles per metric ton. b Gross output; includes seed, feed, and waste. See table A-1 for the value of net output. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Approved for Release: 2019/07/19 C05210421 tv cm Table A-3 USSR: Output .of Livestock Products and Livestock Inventories Thousand metric tons Component Prices a 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Meat Beef and veal 2454. 2355.0 2000.0 2200.0 2090.0 2091.0 2181.0 2348.0 2407.0 2715.0 3226.0 Pork , 2252. . 1478.0 1673.0 1813.0 2305.0 2715.0 2529.0 2666.0 3344.0 3264.0 3633.0 Mutton and kid 1824. 690.0 500.0 700.0 714.0 709.0 826.0 829.0 777.0 885.0 1063.0 Poultry 2368. 278.0 400.0 400.0 513.0 480.0 455.0 475.0 584.0 600.0 731.0 Other meat 3601. 66.0 98.0 57.0 200.0 286.0 333.0 280.0 262.0 236.0 263.0 Total 2351. 4867.0 4671.0 5170.0 5822.0 6281.0 6324.0 6598.0 7374.0 7700.0 8916.0 Other livestock products _ Milk 196. 35311.0 36200.0 35700.0 36475.0 38197.0 43009.0 49111.0 54750.0 58674.0 61716.0 Eggs (million eggs) 100. 11697.0 13300.0 14400.0 16059.0 17179.0 18481.0 19532.0 22269.0 23040.0 25594.0 Wool 4650. 179.6 192.0 219.0 234.8 230.0 255.8 261.1 288.9 321.8 356.4 Honey 1600. 182.0 190.0 ' 199.0 208.0 207.0 206.0 206.0 230.0 208.0 210.0 Silk cocoons 5100. 24.8 25.2 25.6 25.9 26.5 24.4 28.1 23.9 28.3 29.6 Livestock inventories (1 January, thousand head) Cattle 442. 58100.0 57089.0 58800.0 56624.0 55837.0 56669.0 58793.0 61444.0 66766.0 70842.0 Hogs 173. 22200.0 24372.0 27100.0 28506.0 33318.0 30921.0 34003.0 40844.0 44336.0 48680.0 Sheep and goats 37. 93600.0 98953.0 107600.0 109930.0 115473.0 112971.0 116247.0 119812.0 130123.0 139175.0 Poultry (million birds) 5. � 263.8 292.8 325.0 360.7 400.4 390.0 410.5 432.1 449.7 482.8 Component Prices 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Meat Beef and veal 2454. 3252.0 2864.0 3277.0 3741.0 3571.0 3917.0 4377.0 5081.0 5513.0 5569.0 . Pork 2252. 3276.0 3704.0 4011.0 4267.0 2813.0 4143.0 4465.0 4456.0 4079.0 4094.0 Mutton and kid 1824. 1019.0 1006.0 1062.0 1119.0 1052.0 1013.0 933.0 1028.0 1029.0 969.0 Poultry 2368. . 766.0 813.0 822.0 802.0 606.0 696.0 745.0 764.0 817.0 866.0 Other meat 3601. 369.0 313.0 290.0 266.0 245.0 187.0 184.0 186.0 210.0 272.0 Total 2351. 8682.0 8700.0 9462.0 10195.0 8287.0 9956.0 10704.0 11515.0 11648.0 11770.0 Other livestock products Milk _ 196. 61718.0 62565.0 63931.0 61248.0 63262.0 72563.0 75992.0 31672.0 79920.0 82295.0 81540.0 37190.0 Eggs (million eggs) 100. 27464.0 29309.0 30089.0 28523.0 26694.0 29068.0 33921.0 35679.0 Wool 4650. 356.8 366.3 371.4 372.7 340.7 356.9 370.9 394.5 415.1 389.7 Honey 1600. 210.6 248.0 205.0 219.0 214.0 191.5 228.3 211.1 204.1 178.6 Silk cocoons 5100. 29.7 28.9 30.6 33.9 33.3 34.8 34.7 36.9 36.1 35.7 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table A-3 USSR: Output of Livestock Products andlivestock Inventories (continued) Thousand metric tons Component Prices a 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Livestock inventories (1 January, thousand head) Cattle 442. 74233.0 75780.0 82077.0 86988.0 85448.0 87171.0 93436.0 97111.0 97167.0 95735.0 Hogs 173. 53443.0 58674.0 66702.0 69964.0 40858.0 52843.0 59576.0 58028.0 50867.0 49047.0 Sheep and goats 37. 143964.0 140304.0 144498.0 146410.0 139560.0 130674.0 135316.0 141042.0 144041.0 146141.0 Poultry (million birds) 5. 514.3 515.6 542.6 550.4 449.1 456.2 490.7 516.4 528.4 546.9 Component Prices a 1976 1971 1972 1973 1974 1975 1976 1977 1978 1979 Meat N.) 0 Beef and veal 2454. 5393.0 5536.0 5715.0 5873.0 6384.0 6400.0 6552.0 6888.0 7086.0 7029.0 Pork 2252. 4543.0 5277.0 5413.0 5081.0 5515.0 5600.0 4228.0 4950.0 5302.0 5289.0 Mutton and kid 1824. 1002.0 996.0 901.0 954.0 974.0 1000.0 878.0 894.0 921.0 870.0 Poultry 2368. 1071.0 1183.0 1203.0 1295.0 1420.0 1500.0 1414.0 1691.0 1902.0 2017.0 Other meat 3601. 269.0 280.0 401.0 324.0 327.0 468.0 511.0 299.0 290.0 276.0 Total 2351. 12278.0 13272.0 13633.0 13527.0 14620.0 14968.0 13583.0 14722.0 15501.0 15481.0 Other livestock products Milk 196. 83016.0 83183.0 83181.0 88300.0 91760.0 90804.0 89675.0 94929.0 94677.0 93341.0 Eggs (million eggs) 100. 40740.0 45100.0 47910.0 51154.0 55509.0 57367.0 56187.0 61194.0 64517.0 65585.0 Wool 4650. 418.9 428.8 420.1 433.3 461.6 466.6 435.5 459.0 467.0 472.0 Honey 1600. 210.0 197.0 184.0 221.0 199.3 194.0 188.0 208.0 179.0 189.0 Silk cocoons 5100. 33.7 36.7 41.4 39.9 38.7 39.1 45.1 43.1 46.0 47.0 Livestock inventories (1 January, thousand head) Cattle 442. 95162.0 99225.0 102434.0 104006.0 106266.0 109122.0 111034.0 110346.0 112690.0 114086.0 Hogs 173. 56055.0 67483.0 71434.0 66593.0 70032.0 72273.0 57899.0 63055.0 70511.0 73484.0 Sheep and goats 37. 135803.0 143421.0 145333.0 144690.0 148534.0 151232.0 147091.0 145373.0 146611.0 148104.0 Poultry (million birds) 5. 590.3 652.7 686.5 700.0 747.7 792.4 734.4 796.0 882.3 953.2 a 1970 average realized prices; rubles per metric ton. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix B USSR: Average Realized 1970 Prices of Agricultural Commodities Grain The average price received by all producers for all types of grain (103 rubles per ton) is calculated in CIA, GNP 1970, p. 32. Average realized prices for individual types of grain were estimated on the basis of the variation among procurement prices paid to collective farms for each grain in 1970 (table B-1). The ratio of collective farm procurement prices for individual grains to the overall grain price received by collective farms is applied to the average grain price received by all Soviet producers for all grain. Potatoes The average price received by all producers (114 rubles per ton) is reported in CIA, GNP 1970, p. 32. Vegetables The average price received by all producers (163 rubles per ton) is reported in CIA, GNP 1970, p. 32. The relationship between state procurement prices for all vegetables and for individual types of vegetables is used to estimate average prices received by all produc- ers for each vegetable (table B-2). Table B-1 USSR: Derivation of 1970 Average Realized Prices for Individual Types of Grain Total grain Wheat Rye Buckwheat Rice Corn Oats Barley Millet Pulses Other Estimated Average Realized Price (rubles per ton)c Prices Received by Collective Farms (rubles per ton) Ratio of Prices for Individual Grains to Average Price for All Grain 101 a 1.00 103 101 b 1,00 103 114" 1.13 116 300 c 2.97 306 300d 2.97 306 135 c 1.34 138 81 b 0.80 82 80 b 0.79 81 80 b 0.79 81 111 c 1.10 113 60d 0.59 61 a Vop ek, no. 1, 1973, p. 57. b Calculated on the basis of data expressing 1970 procurement prices as a percent of 1965 prices in A. I. Stepanov, Khleb rossii, Moscow, 1973, pp. 275-276 and V.P. Boyev, Zernovoyye i maslichnyye kurtury, no. 7, 1969, p. 9. c Actual 1971 procurement prices received by collective (arms. Since the procurement price for wheat did not change between 1970 and 1971, the 1971 prices for other grains are assumed applicable. The 1971 prices are computed from data in V.P. Boyev, Sovershenstvo- vaniye zakupochnykh tsen na sel'skokhozyaystvennuyu produkt- siya, Moscow, p. 156 and in A. Ye. Kaminsk, Ekonomika zernovogo khozyaystvo, Moscow, 1970, p.188. a List procurement prices are reported in G. V. Kulik et al., Spravochnik economista kolkhoza i sovkhoza, Moscow, 1970, p. 298. c Calculated by multiplying column 2 times 103 rubles per ton. 297 Approved for Release: 2019/07/19 C05210421 Table B-2 USSR: 1970 Average Realized Prices for Vegetables 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV RSFSR Procurement Zone a Share of Procurements (percent) h Zone Procurement Price (rubles per ton) c Weighted Average Procurement Price (rubles per ton) d Ratio of Prices for Individual Vegetables to Average Price for All Vegetables (rubles per ton) c Estimated Average Realized Prices (rubles per ton) f All vegetables 106 163 h Cabbage 61 0.58 95 40 55 II 60 65 Cucumbers 138 1.30 212 60 120 II 40 165 Tomatoes 109 1.03 168 60 90 II 40 137 Table beets 70 0.66 108 40 70 II 60 70 Carrots 100 0.94 153 40 100 II 60 100 Onions 280 2.64 430 40 250 II 60 300 Other 99i a RSFSR zone I and II procurement prices were selected as representative because the RSFSR supplied 43 percent of Soviet vegetable procurements in 1970. Within the RSFSR, Krasnodar Kray (zone I) and the remainder of the North Caucasus (zone II) are the largest vegetable suppliers. h For cabbage, beets, carrots, and onions the price of zones I and II were weighted together by the respective shares of the two zones in total vegetable procurements in the North Caucasus in 1970. The share weights were reversed for tomotoes and cucumbers since the lowest procurement price is usually paid in the zone where procurements are largest. c Prices for late, fresh varieties of the vegetable are from G.V. Kulik et al., Spravochnik ekonomista kolkhoza i sovkhoza, Moscow, 1970, pp. 329335. d Weighted 2,..rage prices for individual vegetables are derived by applying the percentage shares of procurements to the zone procurement prices. Weighted average procurement prices for individual types of vegetables divided by 106 rubles per ton. f Derived by multiplying ratios described in footnote (g) below by 163 rubles per ton. The overall USSR procurement price for all vegetables is derived by summing the ruble value of procurements from state farms, collective farms, and private producers. The total value is divided by total quantity procured to derive an overall weighted average price. Data on total values and quantities procured are from CIA, GNP 1970, p. 32. h CIA, GNP 1970, p. 32. The aggregate vegetable price is dertved independently from the prices for individual types of vegetables. "Other vegetables" are priced at the level needed to result in the overall price of 163 rubles per ton, using the prices for the six types of vegetables listed above. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Approved for Release: 2019/07/19 C05210421 Table B-3 USSR: Quantities of Fruit Procured, 1970 Thousand tons Table B-4 Total a Private Producers b State Farms Collective Farms Total 6,180 872 3,170 2,138 Grapes 3,145 255 1,494(c) 1,396(c) Berries 49 20 1,676(d) 742 (d) Other fruit 2,986 597 a Data for total fruit procurements and for procurements of grapes and other fruits are reported in Narkhoz 1972, p. 299. Berry procurements are derived as a residual by subtracting procurements of grapes and other fruit from total fruit procurements. b G. M. Bogush et al., in Sel'skoye khozyaystvo SSSR, Moscow, 1972, p. 95, show percentage shares of total fruit procurements (6,180 thousand tons) that were obtained from private producers (14.1 percent). G. G. Badiryan, in Ekonomika sotsialisticheskogo sel'skokhozyaystva, Moscow, 1971, p. 377, presents data on procure- ments of berries from the private sector (40 percent) and for other fruits procured from the private sector (20 percent). Grape procure- ments from the private sector are derived as a residual by subtracting private procurements of berries and other fruit from total fruit procurements from the private sector. c Total procurements of grapes from the socialized sector are allocated to state and collective farms according to their respective shares of fruit production. (Badiryan, op. cit., p. 402). d Includes berries and other fruits. Derived by subtracting procure- ments of grapes from total procurements of fruit from these producers. Fruit This category includes berries, grapes, other fruit, and nuts. The weighted average price (282 rubles per ton), however, is based on prices for berries, grapes and other fruit (table B-4). Average procurement prices are used because not enough data are available on fruit prices in collective farm markets, commission trade, and decentralized procurements to calculate average realized prices. The average procurement price is derived by weighting prices paid to collective farms, state farms, and private producers by the quantities obtained from each. Table 133 shows quan- tities of fruit procured in 1970. Table B-4 shows the valuation of procurements and the derivation of the average procurement price. Sugarbeets Sugarbeets are priced at the 1970 price paid to collective farms for beets sold to state procurement organizations (26 rubles per ton). The 1970 price is from Vop ek, no. 1, 1973, p. 57. 299 USSR: 1970 Average Procurement Price for Fruit Procurements Quantities a Prices (thousand tons) Fruits and berries Deliveries of state farms and other state agricultural enterprises 1,676 276b Procured from collective farms 742 246 Delivered by private producers 617 246 Total or average 3,035 263 Grapes Deliveries of state farms and other state agricultural enterprises 1,494 315 b Procured from collective farms 1,396 287 c Delivered by private producers 255 287 c Total or average 3,145 300 Total fruit Deliveries of state farms and other state agricultural enterprises 3,170 294b Procured from collective farms 2,138 273c Delivered by private producers 872 258 c Total or average 6,180 282 a Table B-3 b State farm procurement prices are derived from an index for 1970 of fruit procurement prices (1966-100), Ek selkhoz, no. 7, 1972, p 33. The 1966 prices for fruits, and berries are calculated from Badiryan, op. cit., p. 379, 389. For grapes, the 1965 price was used ( Vop ek, no. 11, 1966, p.38). Because prices received by all farms per unit of delivered product were relatively unchanged from 1965 to 1970 (Narkhoz 1979, pp. 230, 260) little error is introduced. c 0. F. Lopatina and S.V. Frayer, Ekonomika sot sialisticheskogo sel'skogo khozyaystva, Moscow, 1973, p.413. Collective farm procurement prices are assumed to be applicable to private producers. Cotton Procurement prices of state farms in 1970 (517 rubles per ton) and of collective farms (566 rubles per ton) are weighted with quantities sold to procurement organizations to obtain an average price of 555 rubles per ton. The collective farm procurement price is from Vop ek, no. 1, 1973, p. 57. The state farm price is calculated from data in Ek selkhoz, no. 7, 1972, p. 33, and in K.I. Pankova et al., Ekonomiko-statistiches- koye izucheniye sovkhozov, Moscow, 1969, p. 134. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Flax seed 113 245 27,685 Mustard seed 68 250 17,000 Castor beans 71 800 56,800 Other 9 375 3,375 Total 261 402 104,860 Flax fiber, tobacco, and makhorka These commodities are priced at 1970 procurement prices received by collective farms. Data are from O.F. Lopatina and S.V. Frayer, Ekonomika sotsialis- ticheskogo sel'skogo khozaystvo, Moscow, 1973, p. 413. Table B-5 USSR: Derivation of 1970 Average Prices for Other Oilseeds sum of RSFSR procurement prices for peanuts (600 rubles per ton), falseflax (135 rubles per ton) and rape (170 rubles per ton). Prices are weighted arbitrarily assuming a 50 percent share for peanuts, 25 percent for falseflax, and 25 percent for rape (table B-5). Quantity Procurement Value Tea Produced (rubles per ton) (thousand (thousand rubles) Tea is valued at the actual procurement price received tons) by state and collective farms in 1970 (940 rubles per Oil crops The average price for all oil crops (203 rubles per ton) is the weighted sum of prices for individual crops. Sunflower seed The price (187 rubles per ton) is taken from CIA, GNP 1970, p. 32. Soybeans The price (260 rubles per ton) is the RSFSR list procurement price from G.V. Kulik et al., Spravoch- nik ekonomista kolkhoza i sovkhoza, Moscow, 1970, p. 301. Other This category includes flax seed, mustard seed, castor beans, and other minor oilseeds. All prices are RSFSR list procurement prices from Kulik et al., op. cit., p. 301. Prices for flax seed, mustard seed, castor beans and other minor oilseeds are weighted together with 1971 production data from Vest stat, no. 10, 1974, p. 89. Other minor oilseeds include hemp seed, tung nuts, peanuts, falseflax, rape, colza, sesame, and others. The price (402 rubles per ton) is the weighted ton). Data are from Ye.S. Karnaukhova et al., Ekono- mika sotsialisticheskogo sel'skogo khozyaystva, Moscow, 1970, p. 418; and G.G. Badiryan, op. cit., p. 394. Meat, slaughter weight The average realized price for all meat (2351 rubles per ton) is the weighted sum of prices for individual types of meat (table B-6). To calculate prices for slaughter weight quantities, the ruble value of live- weight marketings are divided by slaughter weight quantities. The underlying assumption is that the unusable portions (the weight difference between live weight and slaughter weight) are of zero value. Milk, eggs, and wool Average realized prices for milk, eggs, and wool are from CIA, GNP 1970, p. 32-34. Prices for milk (196 rubles per ton) and eggs (100 rubles per thousand units) apply both to production and to quantities used in production for feed (milk) and hatching eggs. Honey The price (1600 rubles per ton) is the RSFSR procure- ment price from G.V. Kulik et al, Spravochnik ekono- mista kolkhoza i sovkhoza, Moscow, 1970, p. 383. RSFSR procurement prices were used because 70 percent of all honey originates in this region. Silk cocoons Almost half of silk cocoon procurements came from Uzbekistan in 1970. Narkhoz Uzbekskoy SSR 1971, pp. 103, 139-140 shows receipts of collective farms and of private producers from state procurement of silk cocoons in 1970 as well as quantities sold. The average procurement price (5100 rubles per ton) is derived by dividing receipts by quantities sold. 300 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-6 Slaughter weight Table 8-7 USSR: Derivation of 1970 Average Realized Prices for Individual Types of Meat Value of Marketings (million rubles)a Quantities Marketed (thousand tons)b Average Price (rubles per ton)c Total meat 22,101.4 9,400 2,351 Beef 11,083.4 4,517 2,454 Pork 7,433.0 3,300 2,252 Mutton 1,342.4 736 1,824 Poultry 1,551.3 655 2,368 Other 691.3 192 3,601 a CIA, GNP 1970, pp. 32-34 b Quantities of meat in slaughter weight are estimated by multiply- ing liveweight marketings by dressing percentages. Liveweight marketings from the various sales channels are from source a. above, Table A-1, columns C, D, J, and K. The dressing percentages are: beef- 58.3 percent; pork -71.9 percent; mutton -51.2 percent; poultry - 80.0 percent; other meat -50 percent. Dressing percentages for beef, pork, and mutton are from I.Ye. Mampel' and N. Ya. Rayskiy, Spravochnik po priyemke i soderzhaniyu skota na myasokombinatakh, Moscow, 1971, pp. 180-184. Dressing percent- ages for poultry and for other meat (rabbit) are from A.M. Shafran, Tablitsy perescheta zhivogo skota v uboynyy i uboynogo zhivoy, Moscow, 1967, p. 10. � c. Value of marketings divided by quantities sold. - Livestock inventories Average realized prices per ton of meat, liveweight, are converted to a price per head basis using the weight of live anitnals sold to state procurement organizations. The conversion of rubles per ton of live weight to rubles per head is shown in table B-7. Vegetables fed Feed vegetables are priced at the estimated average -realized price for cabbage (95 rubles per ton) which is believed to predominate in vegetables fed. � Potatoes fed Feed potatoepare priced at the seasonally low pro- curement-supply price (63 rubles per ton) which is in effect from September through December. The price used applies to the RSFSR, Belorussia, and the Ukraine where 95 percent of potatoes are produced. Prices are reported in M.K. Vasunin and A.S. Davy- dov, Gosudarstvennye zakupi kolkhoznoy produktsii, Moscow, 1978, p. 85. 301 USSR: Derivation of 1970 Prices for Livestock Inventories Weight of Live Price Price per Animal (rubles per ton) b Animal (tons per head) a (rubles per head), Cattle .309 1,431 442 Hogs .107 1,620 173 Sheep and goats .040 935 37 Poultry (d) .002 1,896 5 Selkhoz 1971, p. 328. b CIA, GNP 1970, pp. 32-34. c Average weight times price per ton. d Live weight per bird is an average of weights for hens and broilers, ducks, geese, and turkeys (S. N. Alekseev, Tovarovedeniye myaso- promyshlennykh zhivotnykh, ptitsy, iproduktov uboya, Moscow, 1972, pp. 99-108). Average weight figures for hens and broilers, ducks, geese, and turkeys are incorporated into a single average weight figure for all poultry using a percentage distribution of mature birds in poultry flocks by type of bird for 1970 (A. V. Gromova et al., Spravochnik: promyshlennoye ptitsevodstvo, Mos- cow, 1971, p. 9). Whole milk fed Whole milk used for feed is priced at the 1970 average realized price described above. Grain fed For 1950-59 annual average prices for grain fed (table B-8) are estimated by weighting average real- ized grain prices (table B-1) with weights derived from grain production statistics. For buckwheat, corn, oats, barley, millet, pulses, and other grain, quantities used for seed and a deduction for waste are subtracted from gross output. The percentage distribution of the remaining net output is used to weight average real- ized prices'. The major food grains, wheat and rye, as well as rice, are excluded from the calculation. For 1960-79, quantities of grain used for seed, food, industrial use, and export are subtracted from total supply of each grain (except rice) to derive a residual quantity available for feed.'" Negative values that indicate deficits (such as for buckwheat) in 1974-77 are excluded from the calculation. The residual quan- tity of each grain is priced at the corresponding average realized price. The weighted average price for all feed grain varies for year to year according to the shifts in availability of each type of grain. " A (ER) 75-68. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table B-8. USSR: Derivation of 1970 Average Prices For Grain Fed Average Realized Prices (rubles per ton) Percentage Distribution of Grain by Type 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 Wheat 103 15.3 20.5 27.7 36.1 Rye 116 8.0 6.2 2.3 2.4 Buckwheat 306 4.0 3.6 3.6 2.4 3.2 2.9 2.8 2.2 1.4 0.9 0.6 0.8 0.7 ' 0.2 0.2 Corn 138 25.5 21.2 21.1 17.8 17.3 33.3 25.6 16.9 27.2 18.4 18.9 31.3 23.2 27.9 13.9 Oats 82 38.2 32.0 35.9 34.6 36.6 26.8 28.0 41.8 29.0 39.2 20.5 14.8 8.1 8.5 5.1 Barley 81 18.1 23.5 24.3 29.4 27.0 2.3 28.8 27.9 30.9 30.4 26.7 17.0 26.0 44.0 27.8 Millet 81 6.2 15.2 9.0 12.6 13.7 8.2 12.3 6.1 7.9 4.6 5.8 3.9 2.5 2.7 2.5 Pulses 113 4.9 3.0 4.5 2.8 1.5 2.6 1.4 3.5 3.0 4.8 3.6 4.8 9.4 16.2 11.7 Other 61 3.1 1.5 1.7 .0.3 0.8 0.8 1.0 1.6 0.7 1.8 0.6 0.7 0.1 0.5 0.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Average price (rubles per ton) 106 102 103 98 99 107 102 97 101 95 101 109 106 103 102 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Wheat 103 21.1 52.6 27.6 38.7 22.2 37.6 37.3 31.9 39.6 19.0 18.3 28.1 29.9 40.5 32.6 Rye 116 12.4 1.0 1.6 4.0 0.5 2.4 2.1 0.7 5.3 2.7 2.7 Buckwheat 306 1.1 0.4 1.0 0.9 0.7 0.2 0.3 0.2 Corn 138 12.7 7.0 12.3 8.7 14.4 7.8 8.6 13.2 10.8 12.3 17.4 12.7 11.7 12.0 18.7 Oats 82 10.6 7.9 15.8 11.8 15.2 12.3 13.9 12.9 9.9 12.0 15.8 10.0 14.2 9.5 11.0 Barley 81 28.8 23.4 30.2 27.0 35.6 32.4 30.8 35.0 32.2 42.9 42.8 40.8 38.7 31.4 35.3 Millet 81 2.2 - 2.1 3.1 1.7 2.9 0.9 0.8 1.0 2.0 1.4 0.9 0.2 0.2 Pulses 113 10.7 5.5 8.3 6.9 8.3 6.3 5.9 5.9 4.4 6.6 5.4 4.5 5.1 3.6 2.3 Other 61 0.4 0.1 0.1 0.3 0.1 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 190.0 100.0 100.0 . 100.0 100.0 100.0 100.0 100.0 Average price (rubles per ton) 103 100 100 100 99 97 97 98 98 96 97 97 96 99 100 302 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix C USSR: Intrasector Use of Agricultural Output A. Estimates of Grain and Potatoes Used for Seed Sown Area. Quantities of grain and potatoes needed for seed are derived by multiplying estimated seeding rates by sown area. Table C-1 shows the area sown to grain and potatoes in 1950-79. Except for winter wheat, winter rye, and winter barley, sown area statistics for grain and potatoes are taken from offi- cial Soviet handbooks as follows: 1979 Vest stat, no. 10, p. 74; Narkhoz 1979, pp. 244- 245. 1978: Narkhoz 1978, pp. 218-219. 1977: Narkhoz 1977, pp. 226-227. 1976 Vest stat, no. 3, 1978, p. 83. 1965, 1970-75: Narkhoz 1975, pp. 347, 353-355. See also Selkhoz 1971, pp. 120-123; Vest stat, no. 4, 1977, p. 84; Vest stat, no. 5, 1976, p. 86; Vest stat, no. 5, 1975, p. 92; Vest stat, no. 10, 1974, p. 87. 1960, 1966-69: Selkhoz 1971, pp. 109-111, 116-123, 127, 133. 1963-64: Narkhoz 1965, pp. 284, 296-297, 299-301, 305; and Selkhoz 1971, p. 109. 1961-62: Narkhoz 1962, pp. 258-260; Selkhoz 1971, pp. 108-109; Narkhoz 1964, p. 284. 1950, 1953-59: Selkhoz 1960, pp. 132-133, presents data for all crops except spring rye. Area sown to corn for silage and green fodder was derived by subtracting the area for fully ripe corn from total area sown to corn. Spring rye data are from Posevnyye ploshchadi SSSR, vol. 1, Moscow, 1957, p. 7. An arbitrary estimate of spring rye production was added to official statistics for winter rye production in 1957 and 1959. 1951-52: Posevnyye ploshchadi SSSR, vol. I, Mos- cow, 1957, pp. 7, 437, 453, 490, 495. See also volume II, p. 192. Figures for rice and corn for silage were interpolated. Official Soviet statistics on area sown to grain ac- tually measure the area occupied by sowings at the completion of spring planting. This definition is more 303 nearly comparable to harvested area than to sown area. The official statistics understate total sown area by the number of hectares that were sown the pre- vious fall but subsequently were lost to winterkill or used for early spring grazing. As a result, official statistics on area sown to winter wheat, winter rye and winter barley must be augmented by estimates of area sown in the fall but not occupied by winter grain at the completion of spring planting. Total area sown in the fall is estimated from information in the Soviet press. Reports of sown area are made at weekly intervals from September through late October."' Area sown as reported by the press is larger than that reported in the handbooks by the number of hectares winterkilled or used for early grazing. Table C-2 shows our estimates of atea sown to winter grain after the adjustment for winterkill and early grazing. Seeding rates. The quantity of grain used for seed is estimated by multiplying the sown area figures shown in table C-1 by seeding rates per.hectare. Seeding rates for the USSR as a whole (table C-3) are weighted averages of seeding rates in each republic. Within republics, seeding rates were compiled for each oblast, and these seeding rates were weighted with 1965 sown area from Soviet statistical hand- books without the adjustment for area lost to winter- kill and early grazing. The seeding fates are for ' sowings of first-class seed, which must meet the criteria of 99 percent purity and 95 percent viability. The seeding rate for potatoes of 19 centners per hectare is reported in S.A. Ekonomika proiz- 1 vodstva kartofelya, Moscow, 1963, pp. 3, 5. 1" For example, Sel'skaya zhizn', 4 October 1979, reported that 37 million hectares had been sown to winter grain crops and that this area amounted to 89 percent of the planned sown area. A week later on 12 October, Sel'skaya zhizn' reported that 38.6 million hectares had been sown, 93 percent of plan. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-1 USSR: Area Sown to Grain and Potatoes Thousand hectares Area sown to: Seeding rate (c/ha) 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Winter wheat 2.20 13647 16890 18602 19351 17704 19872 16283 20172 19811 19023 Spring wheat 2.00 26044 27400 29100 30533 33611 42172 49121 50523 48447 45578 Rye 2.00 25926 25977 24758 22136 23172 20860 23338 19797 19567 18671 Buckwheat 1.00 2953 2700 2500 2653 2765 2761 2676 2450 1689 1318 Rice /40 139 139 138 137 136 142 148 113 106 96 Corn for grain 0.23 4829 4100 3900 3485 4293 6176 6604 3256 4402 3547 Oats /00 16152 17400 16600 15314 15871 14811 15063 14029 14832 14328 Barley 2.00 8607 8133 8640 9638 10728 9908 12040 9230 9771 9756 Millet 030 3767 3300 3500 4081 5453 7683 6369 3570 3729 2698 Pulses 230 3498 2954 2530 2433 2672 2087 2071 1945 2107 2535 Other 1.40 715 621 245 252 290 289 292 220 254 272 Corn for silage 035 0 0 0 0 0 11741 17327 15016 15323 18867 Total grain area 106277 109614 110513 110013 116695 138502 151332 140321 140038 136689 Potatoes 19.00 8534 8449 8207 8307 8709 9091 9197 9778 9525 9540 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Winter wheat 2.20 15299 18865 19744 21847 22582 23784 23933 23955 23256 22176 Spring wheat 2.00 48338 45733 49283 48253 48883 50411 50155 47318 48259 52012 Rye 2.00 20610 18345 18444 20062 19965 19255 16180 15091 15024 14191 Buckwheat 1.00 1418 1891 2287 1824 1383 1794 1844 1723 1703 2043 Rice , 2.40 95 100 100 100 200 217 248 281 312 328 Corn for grain 0.23 5086 7145 7005 6995 5114 3177 3229 3485 3350 4167 Oats 2.00 12842 11500 6900 5700 5700 6628 7162 8688 8998 9300 Barley 2.00 12422 13557 16378 21172 21964 20022 19669 19405 19714 22968 Millet 030 3783 3800 4299 3965 3549 3253 3252 3802 3050 3376 Pukes 230 3321 4345 7200 10830 10643 6759 5927 5460 5052 5187 Other 1.40 223 262 336 432 340 224 208 164 154 155 Cbrn for silage 035 23079 18511 30134 27187 22300 20227 19880 19560 19001 18462 Total grain area 146516 144054 162110 168367 162623 155751 151687 148932 147873 154365 Potatoes 19.00 9144 8900 8700 8500 8500 8612 8392 8331 8301 8100 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Winter wheat 2.20 23100 23717 21441 19361 24270 23820 23594 27674 27636 24370 Spring wheat 2.00 46725 43341 43513 44815 41066 42392 42219 41318 39776 38964 Rye 2.00 12503 10894 11681 7402 12794 9738 12359 8945 9226 8410 Buckwheat 1.00 1879 1768 1720 1648 1589 1459 1431 1743 1773 1662 Rice 2.40 350 390 421 462 495 500 524 546 580 610 Corn for grain 0.23 3353 3332 4012 4031 3955 2652 3303 3362 2535 3931 Oats 2.00 9250 9600 11400 11900 11500 12100 11296 13026 12097 12239 Barley 2.00 21619 21790 27786 29476 31535 32892 34691 35004 32969 38504 Millet 0.30 2691 2397 2724 2850 2970 2774 2998 3048 2924 2784 Pulses 2.30 5070 5178 5855 6083 5780 5670 5153 5195 5058 5508 Other 1.40 121 130 105 210 333 223 300 183 191 200 Corn for silage 0.35 18010 17800 17900 16900 17100 17300 18114 15557 16695 15469 Total grain area 144671 140337 148558 145138 153387 151520 155982 155601 151460 152651 Potatoes 19.00 8064 7894 7894 8017 7983 7912 7087 7067 7042 6970 304 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-2 USSR: Estimated Area Sown to Winter Grain Thousand hectares 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1950 1963 1964 Harvested area of winter grain a 36500 39900 40500 38461 36634 37992 31925 37363 37153 35843 29355 35667 37028 33356 37104 Wheat 12484 15600 17200 17823 15731 18285 12889 18535 18195 17419 12055 17267 18128 16356 19004 Rye Barley 23592 424 23900 22800 20232 20475 19095 18395 18078 17899 17068 16200 16700 16900 15000 16700 400 500 406 428 612 641 750 1059 1356 1100 1700 2000 2000 1400 Area lost to winterkill and spring grazing b 3400 3300 3300 3300 4600 3300 8400 3300 3300 3300 7900 3300 3300 11200 7000 Wheat 1163 1290 1402 1528 1973 1587 3394 1637 1616 1604 3244 1598 1616 5491 3578 Rye 2196 1977 1858 1736 2572 1660 4838 1597 1590 1571 4360 1545 1506 5037 3158 Barley , 41 33 40 36 55 53 168 66 94 125 296 157 178 672 264 Total sown area Winter wheat 13647 16890 18602 19351 17704 19872 16283 20172 19811 19023 15299 18865 19744 21847 22582 VVinterandspingrye 23730 24000 22900 20400 20400 19200 18500 18200 17977 17100 16250 16800 16938 15025 16807 Area lost 2196 1977 1858 1736 2572 1660 4838 1597 1590 1571 4360 1545 1506 5037 3158 Total rye 25926 25977 24758 22136 23172 20860 23338 19797 19567 18671 20610 18345 18444 20062 19965 Winter and spring barley 8566 8100 8600 9602 10673 9855 11872 9164 9679 9631 12126 13400 16200 20500 21700 Area lost ,41 33 40 36 55 53 168 66 94 125 296 157 178 672 264 Total barley 8607 8133 8640 9638 10728 9908 12040 9230 9773 9756 12422 13557 16378 21172 21964 Approved for Release: 2019/07/19 C05210421 Table C-2 Thousand hectares USSR: Estimated Area Sown to Winter Grain (continued) Approved for Release: 2019/07/19 C05210421 1972 1974 1975 1965 1966 1967 1968 1969 1970 1971 1973 1976 1977 1978 1979 Harvested area of winter grain a _ 37194 34863 33408 32772 24514 29805 31494 24339 26952 29920 29203 27453 28868 32271 26687 Wheat 19794 19803 19708 18972 14414 18505 20694 14979 18340 18610 19593 17248 20712 23122 18858 Rye 16000 13560 12400 12200 9200 10000 9500 8160 7012 9810 8010 9035 6697 7719 6499 Barley 1400 1500 1300 1600 900 1300 1300 1200 1600 1500 1600 1170 1459 1430 1330 Area lost to winterkill and and spring grazing b 7500 7000 7200 7400 13200 7400 4600 10500 1500 9100 6300 10100 9700 6300 7800 Wheat 3990 4130 4247 4284 7762 4595 3023 6462 1021 5660 4227 6346 6962 4514 5512 Rye 3225 2597 2673 2755 4954 2483 1387 3521 390 2984 1728 3324 2248 1507 1900 Barley 285 273 280 361 484 322 190 517 89 456 345 430 490 279 388 Total Sown Area Winter wheat C 23784 23933 23955 23256 22176 23100 23717 21441 19361 24270 23820 23594 27674 27636 24370 Winter and spring rye 16030 13583 12418 12269 9237 10020 9507 8160 7012 9810 8010 9035 6697 7719 6510 Area lost 3225 2597 2673 2755 4954 2483 1387 3521 390 2984 1728 3324 2248 1507 1900 Total rye 19255 16180 15091 15024 14191 12503 10894 11681 7402 12794 9738 12359 8945 9226 8410 Winter and spring barley 19737 19396 19125 19353 22484 21297 21600 27269 29387 31079 32547 34261 34514 32690 38116 Area lost 285 273 280 361 484 322 190 517 89 456 345 430 490 279 388 Total barley 20022 19669 19405 19714 22968 21619 21790 27786 29476 31535 32892 34691 35004 32969 38504 a Official Soviet statistics. See the discussion for sources. b Total area lost is allocated to wheat, rye, and barley according to the distribution of harvested area. c Harvested area plus area lost. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The most complete data on grain seeding are available for oblasts of the RSFSR (G. V. Kulik et al., Spra- vochnik ekonomista kolkhoza i sovkhoza, Moscow, 1970, pp. 417-428). Data are also available for Belo- russia (I. M. Kachuro et al., Normativnye materialy po serskomu khozyaystvu, Minsk, 1969, p. 46-50) and for Moldavia (F. Goryachenko, Spravochnik ekonomista po planirovaniyu v kolkhozakh i sovkho- zakh, Kishinev, 1967, p. 189). Seeding rates for all other Soviet republics are estimated from these three sources. Seeding in nonchernozem oblasts of the Ukraine is estimated at the rate for Belorussia while the remaining Ukrainian oblasts are assumed compa- rable to Rostov oblast in the North Caucasus. Kok- chetav and Northern Kazakhstan are equated with Omsk in Western Siberia; all other Kazakhstan ob- lasts are assumed seeded at rates for Orenburg in the Ural region. Belorussian seeding rates are applied to the Baltic republics. The Central Asian republics of Kirgizia, Tadzhikistan, Turkmenistan, and Uzbekis- tan are assumed comparable to the Kalmyk and Dagestan ASSRs. The Dagestan analog is also used for Azerbaydzhan, Armenia, and Georgia. For pulse crops, a weighted seeding rate for each republic was derived by combining sown area with seeding rates for peas, kidney beans, lentils, other pulses, as well as vetch, lupin, and seradella for grain. Belorussian seeding rates for each pulse crop are assumed applicable to the Baltic republics; rates for Moldavia are available from Goryachenko, and all- RSFSR rates were used for remaining republics. Corn for silage and green fodder is assumed sown in all republics at the midpoint of the range 30 to 40 kilograms per hectare, given as the all-USSR seeding rate in S.D. Kosaurov et al, Norrnativnyy spravochnik serskokhozyaystvennogo proizvodstva, Moscow, 1967, p. 17. B. Agricultural Commodities Used for Feed Grain. The basic data for grain fed in 1960-79 are derived from official Soviet statistics on quantities of concentrates fed. The methodology is explained in A (ER) 75-68, p. 33-34, which sets out the calculations for 1960-73. The data since 1970 have been revised slightly' because data on extraction rates for flour� which changed the estimate of millfeed concentrates 307 available�have been updated. The data for 1973-79 are presented in table C-4. To estimate grain fed during 1950-59, an index based on quantities of concentrates required annually to produce livestock products, to increase herd inventories, and to maintain horses was used. This synthetic index agrees generally with an index based on the official series of concen- trates fed in later years. (See ER 79-10057, USSR: Long-Term Outlook for Grain Imports, January 1979, p. 13.) Because the requirements-based index is more consistent with what we believe occurred during the 1950s, we have chosen to use the requirements-based index to estimate quantities of grain fed during 1950- 59, that is, the index was used to move the 1960 estimated quantity of grain fed (the base weight) back to 1950. Estimated quantities of grain fed are reduced by the same type of discount�based on weather conditions and crop size�used to discount grain production (see discussion on pp. 18-19, above.) Potatoes. Data for potatoes fed are taken from official Soviet statistics for 1961-70, published in United States Department of Agriculture, Economic Re- search Service, Foreign 355, (undated), Livestock Feed Balances for the USSR, p. 20. For 1950-60 and 1971-79, quantities of potatoes fed are estimated from an independently constructed balance. We assume, potatoes not used for seed, human consumption, and industrial uses are fed to livestock. Table C-6 presents the basic data from which the balance is derived. Table C-7 shows the estimated quantities of potatoes available for feed. The calculation is as follows: Q = Po - S(I) - where C(o) + l(0) + Co ) 1(1) 2 = residual quantity available for feed = production of current year = seed required for crop of next year human consumption of current year = industrial use of current year human consumption of next year = industrial use of next year, Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-3 USSR: Seeding Rates for Grain, 1970 Centners of first class seed per hectare Corn for grain Pulses Rice Oats Barley Winter Wheat Spring Wheat Rye Millet Buckwheat Other Corn for silage and green fodder USSR 2.2 2.0 2.0 0.3 1.0 0.23 2.3 2.4 2.0 2.0 1.4 0.35 RSFSR 2.4 2.1 2.0 0.3 1.1 0.26 � 2.3 2.4 2.1 2.1 1.1 a 0.35 Ukraine 2.2 1.9 1.8 0.3 0.9 0.22 2.4 2.8 1.5 2.0 0.1 b 0.35 Kazakhstan 1.6 1.9 1.5 0.3 0.9 0.27 2.1 2.4 1.5 1.8 1.0c 0.35 Belorussia 2.3 2.5 2.0 0.3 1.0 0 2.0 0 2.2 2.1 2.1 d 0.35 Estonia 2.3 2.5 2.0 0.3 1.0 0 2.5 0 2.2 2.1 2.1 d 0.35 Latvia 2.3 2.5 2.0 0.3 1.0 0 2.5 0 2.2 2.1 2.1 d 0.35 Lithuania 2.3 2.5 2.0 0.3 1.0 0 2.0 0 2.2 2.1 2.1 d 0.35 Moldavia 1.8 1.9 1.5 0.3 0.9 0.23 2.4 0 1.6 1.4 0.1 b 0.35 Azerbaydzhan 2.3 2.1 1.8 0.3 0 0.25 1.0 2.4 1.7 2.0 1.0c 0.35 Armenia 2.3 2.1 1.8 0.3 0 0.25 1.0 2.4 1.7 2.0 1.0 c 0.35 Georgia 2.3 2.1 1.8 0.3 0 0.25 1.6 2.4 1.7 2.0 1.0c 0.35 Kirgiz 1.7 1.2 1.1 0.3 0 0.25 2.8 2.4 1.7 1.3 1.0 c 0.35 Tadzhikistan 1.7 1.2 1.1 0.3 0 0.25 1.7 2.4 1.7 1.3 0.1 b 0.35 Turkmenistan 1.7 1.2 1.1 0.3 0 0.25 0 2.4 1.7 1.3 0.1 b 0.35 Uzbekistan 1.7 1.2 1.1 0.3 0 0.25 1.9 2.4 1.7 1.3 0.1 b 0.35 a Assumed to be half sorghum for grain sown at the Moldavian rate and half a mixture of oats and barley sown at the rate of 2.1 centners per hectare. b Assumed to be sorghum sown at the Moldavian rate. c Arbitrary estimate. d Assumed to be a mix of oats and barley. The weighted average seeding rate of Belorussia is used. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-4 Million tons USSR: Derivation of Grain Fed to Livestock 1973 Total concentrates a Grain b 117.0 99.10 Milling byproducts 12.10 Oilseed meal Official d NA Calculated 3.73 Alfalfa meal f 2.07 1974 1975 1976 1977 1978 1979 127.9 118.9 117.4 143.0 145.9 146.6 109.62 101.23 99.44 121.91 124.70 125.07 12.07 10.93 9.80 12.51 12.31 12.94 3.31 3.19 NA 3.14 3.48 3.63 3.42 3.55 3.58 2.79 3.60 4.68 4.95 5.58 5.40 a 1979: Narkhoz 1979, p. 284, 1975-78: NarkhozJ978, p. 258, 1973-14: Narkhoz 1975, p. 412. b Total concentrates less milling byproducts, oilseed meal, and alfalfa meal. Table C-5. According to Ek selkhoz, no. 4, 1971, p. 28, 92 percent of milling byproducts are used as feed. d USDA, data supplied under the US-USSR Agriculture Agree- ment. Maslo-zhiroyava promyshlennost', no. 2, 1980. Vest stat, no. 10, 1980, p. 79. According to ibid., 75 percent of total output of oilseed meal is used as feed. c A (ER) 75-68, p. 33-34. The Food and Agriculture Organization of the United Nations, in a massive study, has also calculated the USSR's production of oilseed meals from 1965-75. See A Survey of A comparison of the derived series with the official shows that it understates actual feed use in about half of the years for which the official data are available and overstates by roughly similar quantities in the other half. Thus, error in the series should be offset- ting over time. No serious bias is introduced by the assumption that residual potatoes are fed. Neverthe- less, data for years with drastic inconsistencies, such as 1950 and 1951 have been arbitrarily smoothed. Similarly, for those years when the residual is sub- stantially larger than the usual quantity fed, such as 1973, the statistic has been arbitrarily reduced. Given the possible margin of error already present in the basic data from which the balance is derived , such adjustments do not seem, unreasonable. Data for 1971 forward are rounded to millions because the underly- ing data for the balance, particularly for industrial use, are less certain than those for earlier years. Vegetables. We assume that all vegetables not con- sumed by humans are fed to animals, that-is, produc- tion plus imports less human consumption equals feed. Lack of data precludes adjustments for exports or 309 the Oilseeds, Oils, Fats, and Protein Meal Sector in the Union of Soviet Socialist Republic, CCP:OF 7/C.R.S.1, March. 1977, p. 41. The FAO quantities of oilseed meal produced are higher than our calculations and also higher than the official statistics for the years in which both are available. Estimated at 90 percent of procurements as reported in the central press. g Because the official data have again been made available to the United States through the US-USSR Agriculturat Agreement, or have been published, calculating the quantities of oilseed meal available for feed use is no longer necessary. NOTE: Components may not add to total because of rounding. inventory change. No vegetables are reported to have been exported. Inventory change data-available only in value terms for the retail trade system--groups vegetables with fruits and berries. Because the value of inventories has been fairly constant at 10 percent of retail sales of the same products it seems unlikely that lack of an inventory adjustment seriously biases the vegetables fed series over time. The series for vegeta- bles fed is derived in table C-8. In contrast to feeding of potatoes where some data are available, no data on total vegetables fed could be found. A few, statements on quantities fed on state and collective farms or on collective farms alone were found. These quantities, ranging from 600 thousand tons in 1966 (Plan khoz, no. I, 1967, p. 25) to 3.1 million tons in 1973 (L.T. Dageev, Podsobnyye pro- myshlenniye predpriyatiya v serskorn khozya_vstve, Moscow, 1976, p. 14) were from half to two-thirds of the derived quantity assumed fed. Because the private sector produces nearly a third of total vegetables, it 93-892 0 - 82 - 21 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 C. Eggs for Hatching For the years 1953, 1957-60, and 1965-70, Soviet sources provide data on numbers of young poultry hatched in incubators. These data are used to calcu- late a poultry balance to estimate the number of birds expended per unit of poultry meat. These data, how- ever, probably exclude eggs hatched in the private sector. Table C-5 Million tons USSR: Derivation of Milling Byproducts Available for Livestock Feeding 1973 1974 1975 1976 1977 1978 1979 (est.) Total 13.15 13.12 11.88 10.65 13.60 13.38 14.06 Wheat flour a 9.89 9.78 8.82 7.74 10.31 10.07 10.66 Rye flour a 1.14 1.13 .85 .66 1.00 .98 1.03 Groats b 2.12 2.21 2.21 2.25 2.29 2.33 2.37 a The difference between quantity of flour produced and the quantity of grain required to produce the flour. Data for flour production for 1973-74 are from Narkhoz 1975, p. 297, for 1975-78 are from Narkhoz 1978, p. 184. The share of wheat flour was 83 percent of to- tal flour in 1973-74, 84 percent in 1975-76, and 85 percent in 1977- 78; the remainder is assumed rye flour. The amount of byproducts from production of flour other than wheat and rye is negligible. Extraction rates for wheat flour, for 1973-78 are assumed to be 78.3, 78.1, 80.0, 78.0, 78.0; for rye flour, 86.5, 86.3, 88.8, 91.0, 86.5. The assumptions are guided by official statements concerning changes in shares of sortovaya (graded) flours produced. b The difference between the quantity of groats produced and the quantity of grain required. Data on production of groats are found in the following sources: 1973: Mukomorno-elevatornaya i kombikor- movaya promyshlennost', no. 3, 1974, p.2; 1974: P.A. Lolcshin, Spros proizvodstvo torgovlya, Moscow, 1975, p. 74. 1975, 1979: Vest stat, no 10, 1980, p. 79. 1976-78 are interpolated. The extraction rate for groats is 62.5 percent, the same as rice. The above sources do not always give total groats production; in those cases where the quantity produced above plan is the only indication of production, production for the current year is assumed to be production of the previous year plus the quantity produced above plan. seems likely that private sector feeding of vegetables would be substantial and could be equal to socialized sector feeding in some years. Whole milk. Quantities of whole milk fed to livestock are estimates based on incomplete data for most years. Official statistics for the total quantity of whole milk fed could be found for only one year, 1970. The series is derived in table C-10. The ratios in table C-11 are arbitrarily interpolated and extrapolated to derive estimates of the number of birds expended and lost in other years. The ratios indicate that the average weight of poultry slaugh- tered for meat is dropping which is consistent with increasing emphasis on production of broiler meat. Previously, almost all poultry meat came from culled laying hens, which tend to be heavier than broilers. We use an estimated hatching rate of 65 percent, which compares with 77 percent in the US in recent years."' No allowance has been made for changes in the hatching rate over time. The mortality rate for poultry used to increase flocks is estimated at 20 ' percent.'" Table C12 shows estimates of hatching eggs for all years. 19 Calculations of hatching rates for the US rely on data from USDA, Agricultural Statistics 1978, pp. 403 and 414. Chicks hatched by commercial hatcheries can be compared with statistics on eggs used for hatching. The implied hatching rate is 70-80 percent for 1975-77. The actual hatching rate may be higher since eggs used for hatching include eggs hatched on farms while the figures on chicks hatched are only for commercial hatcheries. 20 Mortality rates for the US can be calculated from ibid., p. 400. The number of chickens produced in the US is shown as the sum of the number raised minus the number lost. The mortality rate is about 15 to 20 percent. We assume this rate is valid for all types of poultry. 310 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-6 USSR: Estimates of Elements of the Potato Balance Million tons Year Production a Seed Use b Industrial Use Food Alcohol e Starch and Syrup d Total e 1950 88.612 16.214 2.240 (.400) (2.640) 43.404 1951 58.754 16.000 1.690 (.400) (2.090) 31.000 1952 69.189 15.601 1.329 (.400) (1.729) 31.000 1953 72.572 15.783 1.453 (.500) (1.953) 30.000 1954 75.021 16.547 1.360 (.500) (1.860) � 30.000 1955 71.751 17.273 1.232 (.600) (1.832) 29.038 1956 96.015 17.474 1.561 (.600) (2.161) (29.556) 1957 87.813 18.578 2.277 (.700) (2.977) 30.277 1958 86.527 18.098 NA (.800) (3.000) 31.020 1959 86.561 18.126 NA NA (3.000) 31.575 1960 84.374 17.374 .696 NA (2.000) 30.645 1961 84.310 16.868 NA NA (2.000) 31.188 1962 69.677 16.503 NA NA (2.000) 31.481 1963 71.834 16.150 .690 NA (2.000) 31.739 1964 93.642 16.184 1.634 NA (3.000) 31.934 1965 88.676 16.362 2.599 1.560 4.159 32.788 1966 87.853 15.945 NA (3.300) 3.300 31.522 1967 95.464 15.829 1.350 1.200 2.550 30.916 1968 102.184 15.772 2.688 - (1.200) 3.888 31.217 1969 91.779 15.390 NA NA (3.600) 31.519 1970 96.783 15.322 2.072 (1.200) (3.272) 31.564 1971 92.655 14.999 NA NA (3.200) 31.373 1972 78.329 15.124 NA NA (3.200) 29.948 1973 108.200 15.232 2.005 (1.300) (3.305) 30.963 1974 81.022 15.168 NA NA (3.300) 30.504 1975 88.703 15.033 2.120 (1.300) (3.420) 30.540 1976 85.102 13.465 NA NA (3.400) 30.559 1977 83.652 13.427 NA NA (3.500) 31.080 197'8 86.124 13.380 (2.000) 1.600 (3.600) 30.572 1979 90.956 13.235 NA NA (3.600) 31.345 a Appendix A. b Sown area times average seeding rate from table C-1. e 1950, 1955, 1960, 1963-64: V.G. Pykov, Ekonomika, organizat- siya, i planirovaniye spirtovogo proizvodstva, Moscow, 1966, p. 26. 1951-54, 1956-57: V.P. Zotov, Pishchevaya promyshalennost' sovetskogo soyuza, Moscow, 1958, p. 111. 1965, 1968, 1970, 1973, 1975: M.T. Kochubeyeva, Ekonomika organizatsiya, i planirovaniye spirtovogo i likerno-vodochnogo proizvodstva, Moscow, 1977, p. 62. 1967: midpoint of range given in N.V. Vinogradov, (ed.), Ekonomika pishchevoy promyshlennosti SSSR, Moscow, 1968, p. 208. 311 d 1950-57: estimated. 1958, 1965: V.P. Zotov, (ed.), Pishchevaya promyshlennost SSSR. Moscow, 1967, p. 360. 1967: N.V. Vinogradov, (ed.), ibid. Moscow, 1968, p. 208. 1978: Sakharnaya promyshlennost', no. 10, 1978, p. 14. e Sum of quantities of potatoes used for alcohol and starch and syrup. Missing years interpolated and indicated by parentheses. f Mid-year population times officially reported per capita consump- tion from Narkhoz 1979, p. 432, and earlier editions. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-7 USSR: Potatoes Used for Feed (Crop Year) Million tons Table C-8 Thousand tons USSR: Derivation of Quantities of Vegetables Available for Feed Production a Imports b Consumption c Available for Feed d Year Available by Calculation a Officially Reported b Series in the Index c Year 1950 33.0 23.0 1950 9,344 47.9 9,185.1 206.8 1951 10.2 20.2 1951 8,836 NA NA NA 1952 21.1 21.1 1952 9,774 NA NA NA 1953 24.1 24.1 1953 11,389 NA NA NA 1954 26.4 26.4 1954 11,918 NA NA NA 1955 23.0 23.0 1955 14,100 74.2 13,537.8 636.4 1956 45.0 30.0 1956 14,298 56.4 12,980.5 1,373.9 1957 36.1 36.1 1957 14,766 125.2 13,411.2 1,480.0 1958 34.1 34.1 1958 14,865 151.1 14,682.8 333.3 1959 35.6 35.6 1959 14,774 225.9 14,103.5 896.4 1960 34.6 38.0 38.0 1960 16,574 240.9 15,001.0 1,813.9 1961 34.5 39.3 39.3 1961 16,151 340.2 14,618.5 1,872.7 1962 19.9 36.9 36.9 1962 15,989 350.1 14,851.0 1,488.1 1963 21.3 32.6 32.6 1963 15,051 418.3 14,214.9 1,254.4 1964 41.3 29.6 29.6 1964 19,467 565.1 16,879.4 3;152.7 1965 36.8 36.1 36.1 1965 17,627 432.5 16,624.8 1,434.7 1966 37.9 41.5 41.5 1966 17,857 521.2 17,045.5 1,332.7 1967 45.4 38.8 38.8 1967 20,534 584.5 18,880.0 2,238.5 1968 51.7 39.4 39.4 1968 19,011 551.9 18,825.7 737.2 1969 41.5 37.6 37.6 1969 18,745 564.1 18,285.6 1,023.5 1970 47.1 36.9 36.9 1970 21,212 612.0 19,909.6 1,914.4 1971 43.7 43 1971 20,840 850.4 20,833.5 856.9 1972 29.4 30 1972 19,941 965.8 19,800.0 1,106.8 1973 59.0 45 1973 25,927 840.8 21,224.5 5,543.3 1974 26.1 26 1974 24,811 865.8 21,932.7 3,744.1 1975 35.3 35 1975 23,351 708.8 22,650.5 1,409.3 1976 37.4 37 1976 24,991 816.3 22,084.8 3,722.5 1977 35.9 36 1977 24,149 888.4 22,792.0 2,245.4 1978 38.3 38 1978 23,902 889.9 24,039.6 752.3 1979 42.8 42 1979 27,215 891.3 25,023.0 3,083.3 a Based on data in table C-6, calculated as explained in text above. b USDA, ERS Foreign 355, Livestock Feed Balances for the USSR, (undated), p. 20, converted to crop year use assuming 2/3 of quantity fed this year is from last year's crop and 1/3 is from this year's. The data are not available for 1950-59 or for 1971-79. c With the exception of 1950-51, which are arbitrarily smoothed, and 1956, which is arbitrarily reduced in order to be more consistent with the given data, the residually-derived data for 1950-59 are accepted. Similarly, with the exception of 1973, which is reduced, the residually-derived data for 1971-79 are accepted. a Appendix table A-2. b Appendix table C-9. c Midyear population times officially reported per capita consump- tion from Narkhoz 1979, p. 432, and earlier editions. d Production plus imports less human consumption. Theoretically, imports and consumption of vegetables should be lagged to balance with crop year production in order to derive a quantity of vegetables available for feed. To lag imports and consumption, we arbitrarily assumed each occurs evenly throughout the year. Quantities imported and quantities consumed in year t and year t+ were averaged. Although the resulting quantities available for feed were somewhat different from those shown above, the difference is so small in value terms that growth in the index of net value of output was changed by less than 0.1 percent in any year. Because the effect is so small, we did not lag imports and consumption. 312 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-9 Thousand tons USSR: Imports of Vegetables Year Fresh Vegetables a Canned Vegetables Total d Pastes and Purees b Converted to Fresh c 1950 47.4 0.3 0.5 47.9 1955 64.3 6.0 9.9 74.2 1956 42.7 8.3 � 13.7 56.4 1957 95.8 17.8 29.4 125.2 1958 116.3 21.1 34.8 151.1 1959 168.0 35.1 57.9 225.9 1960 174.9 40.0 66.0 240.9 1961 189.9 91.1 150.3 340.2 1962 201.8 89.9 148.3 350.1 1963 239.6 108.3 178.7 418.3 1964 303.4 158.6 261.7 565.1 1965 222.0 127.6 210.5 432.5 1966 185.6 203.4 335.6 521.2 1967 151.0 262.7 433.5 584.5 1968 169.4 231.8 382.5 551.9 1969 182.0 231.6 382.1 564.1 1970 163.4 271.9 448.6 612.0 1971 310.0 327.5 540.4 850.4 1972 358.8 367.9 607.0 965.8 1973 235.6 366.8 605.2 840.8 1974 281.5 354.1 584.3 865.8 1975 144.0 342.3 564.8 708.8 1976 185.7 382.2 630.6 816.3 1977 190.5 423.0 697.9 888.4 1978 182.4 428.7 707.4 889.9 1979 147.1 451.0 744.2 891.3 a 1979: Vneshnyaya torgovlya SSSR v /979g., (hereafter Vnesh (org and the year), p. 42. 1977-78: Vnesh torg 1978, pp. 41-42 1975-76: Vnesh torg 1976, P. 43. 1973-74: Vnesh torg 1974, p. 50. 1971-72: Vnesh torg 1972, p. 47. 1969-70: Vnesh torg 1970, p. 45. 1967-68: Vnesh torg 1968, pp. 45-56. 1950, 1955-66: Vnesh torg 1918-1966, pp. 111-113. , b Sum of number of cans of vegetables converted to tons and the quantity of pastes and purees, given in tons, from sources in (a) above. The number of cans of vegetables is converted to tons using the standard Soviet size, 400 grams per can. See, for example, Vnesh torg 1972, p. 47, which presents the data in both number of cans and thousand tons. a Converted to quantities of vegetables required to produce the canned vegetables and pastes and purees using the coefficient, 1.65 tons of vegetables required to produce 1.00 tons of canned vegetables. See L.V. Opatskiy, Razmeshcheniye pishchevoy pro- myshlennosti SSSR, Moscow, 1958, p. 98. d Sum of fresh vegetables and converted vegetables. 313 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-10 Million tons USSR: Derivation of Whole Milk Fed to Livestock Year Total a Total a On Collective and State Farms b Private On Collective and State Farms b Private Year 1950 4.6 1966 9.5 5.5 4.0 d 1951 4.7 1967 10.2 5.9 4.3 d 1952 4.6 1968 10.8 6.3 4.5 d 1953 4.7 1969 11.1 6.6 45d 1954 5.0 1970 11.5 a 6.9 4.6 d 1955 5.6 1971 11.4g 6.7 4�7d 1956 6.4 1972 11.48 6.4 4.9 1957 7.1 1973 11.48 6.5 4.71 1958 7.6 1974 11.4 6.8 4.31 1959 8.0 1975 Plan 10.9 7.0 1960 8.0 1975 Est. 11.4g 1961 8.1 5.2 2.9 c 1976 11.4g 1962 8.4 5.2 3.2 d 1977 11.4 1963 8.0 4.8 3.2d 1978 11.4g 1964 7.5 4.2 33d 1979 11.4 1965 8.7 5.1 3.6 d a 1950-60: assumed 13 percent of total milk production, the average share during 1961-70. 1961-1979: sum of milk fed on collective and state farms and milk fed to private livestock holdings unless otherwise noted. b 1961-70: Selkhoz 1971, p. 332. 1971-73: Nalichiye iraskhodv kolkhozakh i sovkhozakh v 1973 godu, Moscow, 1974, p.6. 1974-1975: Sel'skaya zhizn', 14 September 1975, p. 2. a P.A. Ignatovskiy, Sotsialno-ekonomicheskiye izmeneniya v sovetskoy derevne, Moscow, 1966, p. 383, notes that the titivate sector fed about 10 percent of its production at the beginning of the 1960s. Private sector production of milk in 1960 was 29.1 million tons and in 1961 was 28.5 million tons. (Narkhoz 1978, p. 249 and Narkhoz 1922-72, p. 258.) d According to Molochnaya promyshlennost', no. 1, 1972, p. 6, the private sector fed 15.9 percent of its production in 1971. The share of milk from private sector production being fed to livestock is assumed to increase by 0.54 percent per year during 1960-70 and by 0.5 percent in 1971 for a total increase of 5.9 percent (15.9 percent in 1971 less 10 percent in 1960). Private sector milk production for 1960-64 is from Narkhoz 1965, p. 376; for 1965-71 is from Narkhoz 1975, p. 396. Gosudarstvennyy pyatiletniy plan razvitiya narodnogo khozyayst- va SSSR na 1971-75 gody, Moscow, 1972, p. 175. 1 Total whole milk fed less whole milk fed on collective and state farms. g Plan khoz, no. 11, 1979, p.91, states that "In 1978 more than 12 percent of milk produced was used for (feed)." Because 12 percent of milk produced in 1978 (94.7 million tons) is 11.4 million tons, we assume the planned downturn in feeding of whole milk did not materialize, and hold the quxitity fed constant from 1971 to 1979. (A small downturn probably occurred in the first year of a new five- year plan.) 314 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table C-11 USSR: Poultry Balance, Selected Years Poultry Flocks on 1 January (million) a Young Poultry From Incubators (million) b Birds Available (million) e Poultry Flocks on 31 December (million) a Birds Expended and Lost (million) d Production of Poultry Meat (thousand tons) e 513 Ratio of Meat to Birds! 1.925 1.634 1.497 1.241 1.097 1.157 1.159 1.086 1.058 1.019 0.954 1953 (360.7) 306.2 666.9 400.4 266.5 1957 432.1 375.0 807.1 449.7 357.4 584 1958 449.7 433.9 883.6 482.8 400.8 600 731 766 1959 482.8 620.7 1103.5 514.3 589.2 1960 514.3 699.4 1213.7 515.6 698.1 1965 456.2 636.3 1092.5 490.7 601.8 696 745 764 1966 490.7 668.3 1159.0 516.4 642.6 1967 516.4 715.4 1231.8 528.4 703.4 1968 528.4 790.6 1319.0 546.9 772.1 817 866 1969 546.9 893.3 1440.2 590.3 849.9 1970 590.3 1184.7 1775.0 652.7 1122.3 1071 a Official statistics on poultry flocks are from Narkhoz /960, p. 457; Selkhoz 1960, p. 320; Selkhoz /970, p. 272. b Selkhoz 1960, pp. 324-326; Selkhoz 1971, p. 275. e Column 1 plus column 2. d Column 3 less column 4. e Table A-3. f Column 6 divided by column 5. 315 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 I�, CN Table C-12 USSR: Eggs Used for Hatching. 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 (1.1) 1962 1963 1964 Ratio of meat to birds a (1.9) (1.9) (1.9) 1.9 (1.8) (1.8) (1.7) 1.6 1.5 1.2 1.1 (1.1) (1.1) (1.1) Production of poultry meat (thousand tons) b 278 400 400 513 480 455 475 584 600 731 766 813 822 802 606 Birds expended and lost (million) e 146 210 210 270 266 253 279 365 400 609 696 739 747 729 551 Hatching eggs for meat birds (million) a 225 324 324 415 409 389 429 561 615 937 1071 1137 27 1149 8 1121 �101 848 7 Change in poultry flocks (million) e 29 (32) (36) (40) �10 20 22 12 33 32 1 Hatching eggs for increase in poultry flocks (millions) f 56 (62) (69) (77) �19 38 42 35 63 62 52 15 �194 13 Total hatching eggs (million) g 281 386 393 492 390 427 471 596 678 999 1073 1189 1164 927 861 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Ratio of meat to birds a 1.2 1.2 1.1 1.1 1.0 866 .95 (.95) (.95) (.95) (.95) (.95) (.95) (.95) (.95) (.95) Production of poultry pleat (thousand tons) b 696 745 764 817 1071 1183 1203 1295 1420 1500 1414 1691 1902 2017 Birds expended and lost (million) e 580 621 694 743 866 1127 1245 1266 1363 1495 1579 1488 2289 1780 2002 2123 Hatching eggs for meat birds (million) a 892 955 1068 1143 1332 1734 1915 1948 2097 2300 2429 2738 3080 3266 Change in poultry flocks (million) e 35 26 12 18 43 62 34 14 48 45 �58 62 86 71 34 Hatching eggs for increase in poultry flocks (million) f 67 50 23 35 83 119 65 27 92 86 �111 119 165 136 65 Total hatching eggs (million) g 959 1005 1091 1178 1415 1853 1980 1975 2189 2386 2318 2408 2903 3216 3331 a Table C-11; figures in parentheses are arbitrary estimates based on data in table C-11. b Table A-3. e Production of poultry meat divided by the ratio of meat to birds. d Birds expended and lost divided by a hatching rate of 65 percent. e Calculated from data in table A-3; additional data to complete the series are from Narkhoz 1978, p. 247; Narkhoz 1975, p. 395; Narkhoz 1960, p. 457. f Changes in poultry flocks divided by the 65 percent hatching rate and by an 80 percent survival rate for young birds. g Hatching eggs for meat birds plus those for changes in poultry flocks. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Part IV. AN INDEX OF CONSUMPTION IN THE USSR By Gertrude E. Schroeder and M. Elizabeth Denton 317 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Contents Page List of Standard Citations Introduction Consumption Trends and Patterns Trends in Per Capita Consumption Changes in the Structure of Consumption Description and Evaluation of the Consumption Index The Index in Established Prices General Category Weights Goods Household Services Communal Services Indexes Indexes at Factor Cost and in Adjusted Market Prices Factor Cost Adjusted Market Prices Comparison With Other Indexes Official Soviet Measures Other Western Measures Description and Evaluation of Component Indexes Goods Food, Beverages, and Tobacco Scope and Coverage Weights Indexes Soft Goods Scope and Coverage Weights Indexes Durables and Miscellaneous Goods Scope and Coverage 322 323 325 325 325 328 328 328 330 330 330 330 331 331 331 331 333 333 334 337 337 337 337 339 339 339 339 340 340 341 341 Weights 343 Index 343 319 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Services 343 Household Services 343 Housing 343 Utilities 344 Transportation 346 Communications 346 Repair and Personal Care 347 Recreation 348 Communal Services 349 Education 349 Health 351 Appendixes A. Indexes of Consumption and 1970 Weights 353 B. Data Used in the Derivation of the Index of Food, Beverages, 369 and Tobacco C. Data Used in the Derivation of the Index of Soft Goods 377 D. Data Used in the Derivation of the Index of Durables and 385 Miscellaneous Goods E. Data Used in the Derivation of the Index of Household Services 386 F. Data Used in the Derivation of the Index of Communal Services 394 Tables 1. Average Annual Rates of Growth of Per Capita Consumption and 326 Major Components in Established Prices, 1950-80 2. Structure of Consumption in 326 Established Prices and at Factor Cost, 1950, 1960, 1970, and 1980 3. Indexes of Total Consumption and Major Categories, Selected 329 Years, 1950-80 4. Growth Rates of Total Consumption and Major Categories, Alternative Base Year Weights in Established Prices 329 5. Growth Rates of Total Consumption and Major Categories in 332 Established Prices and at Factor Cost, Selected Years, 1950-80 Comparison of Official and CIA Measures of Soviet Per Capita 335 Consumption 7. Comparisons of CIA Index of Total Consumption With Indexes 336 Constructed by Bergson, Chapman, and Becker 8. Derivation of 1970 Weights for Components of the Index of Food, 338 Beverages, and Tobacco 9. Derivations of 1970 Weights for Components of the Index of 341 Soft Goods 320 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix Tables A-1. Indexes of Total Consumption in Established Prices, by Category, 353 1950-80, and 1970 Category Weights A-2. Per Capita Consumption in Established Prices, by Category, 1950-80 321 365 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 List of Standard Citations Full Citation Abbreviated Citation USSR Central Statistical Administration, Statistical Handbooks Narodnoye khozyaystvo SSSR v 19�godu (National Economy of the USSR in 19�) Narkhoz 19� Promyshlennost' SSSR, 1964 (Industry USSR) Prom 1964 Sel'skoye khozyaystvo SSSR, 1960, (Agriculture USSR) Selkhoz 1960 Sel'skoye khozyaystvo SSSR, 1971, (Agriculture USSR) Selkhoz 1971 Sovetskaya torgovlya (Soviet Trade), Moscow, 1964 Soy torg 1964 Gosudarstvennyy byudzhet SSSR i byudzhety soyuznykh respublik (State Budget of the USSR and Budgets of the Union Republics) 1961-1965 1966-1970 1971-1975 Gosbyudzhet, 1966 Gosbyudzhet, 1972 Gosbyudzhet, 1976 Soviet Periodicals Voprosy ekonomiki (Problems of Economics) Vop ek Vestnik statisiki (Herald of Statistics) Vest stat Ekonomika i organizatsiya promyshlennogo proizvodstva (Economics and Organization of Industrial Production) EKO Ekonomicheskaya gazeta (Economic Gazette) Ekon gaz US Government Publications CIA, USSR: Gross National Product Accounts, 1970 A (ER) 75-76, November 1975 CIA, The Soviet Grain Balance, 1960-73, A (ER) 75-68, September 1975 CIA, A Comparison of Consumption in the USSR and the US. January 1964 Joint Economic Committee, Congress of the United States, Gross National Product of the USSR, 1950-80, 1982 An Index of Industrial Production in the USSR, 1982 An Index of Agricultural Production in the USSR, 1982 An Index of Consumption in the USSR, 1982 Consumption in the USSR: An International Comparison, 1981 Gross National Product of the USSR: An International Comparison, 1982 Soviet Economic Prospects for the Seventies, June 1973 Soviet Economy in a New Perspective, October 1976 Soviet Economy in a Time of Change, October 1979 CIA, GNP 1970 A (ER) 75-68 CIA, A Comparison�, 1964 JEC, GNP, 1950-80 JEC, Industry JEC, Agriculture JEC, Consumption JEC, Consumption Comparison JEC, GNP Comparison JEC, 1973 JEC, 1976 JEC, 1979 Other Publications Irving B. Kravis, Zoltan Kenessey, Alan Heston, and Robert Summers, A System of International Comparisons of Gross Product and Purchasing Power, United Nations International Comparisons Project, Phase I (Baltimore: The Johns Hopkins University Press, 1975) ICP, Phase I Irving B. Kravis, Alan Heston, and Robert Summers, International Comparisons of Real Product and Purchasing Power, United Nations International Comparison Project, Phase II (Baltimore: The Johns Hopkins University Press, 1978) ICP, Phase II Abraham S. Becker, Soviet National Income, 1958-1964, (Berkeley, University of California Press, 1969) Becker, 1969 Abram Bergson, The Real National Income of Soviet Russia Since 1928, (Cambridge, Mass., Harvard University Press, 1961) Bergson, 1961 Abram Bergson, Productivity and the Social System: The USSR and the West, (Cambridge, Mass., Harvard University Press, 1978) Vladimir G. Treml and John P. Hardt, eds., Soviet Economic Statistics, (Durham, N.C., Duke University Press, 1972) Bergson, 1978 Treml and Hardt 322 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 An Index of Consumption in the USSR Introduction The index of consumption described in this paper was developed to provide a measure of real consumption in the Soviet Union in the post-war period that is comparable in concept and methodology to measures available for Western countries. The index defines consumption to include all household expenditures on goods and services for consumption plus government current expenditures on health and education services. In Western national accounts�those of the OECD, for example�this definition is equivalent to "private final consumption expenditures" plus the health and education components of "government final consump- tion expenditures". Although treated separately here, the index is designed as a major component of an index of gross national product (GNP).' Like most of the other components of CIA's reconstruction of Soviet GNP over time, the consumption index is an aggregate of time series, most of them in physical units, weighted by expenditures in rubles in the base year (1970). This approach contrasts with that in Western countries, where the GNP index and its components are usually deflated value measures. In the Soviet case, the resort to physical measures was both necessary and desirable, because of the lack of trustworthy price indexes as well as current expendi- ture data in most cases. A Western-type measure of progress in raising living standards in the USSR is required for two important reasons. First, the measures published by the Soviet government are conceptually unsuitable for compari- sons with those published by Western countries and also are widely believed to have a large upward bias. The official Soviet measures�"real per capita in- comes" and "personal consumption" plus "material expenditures of institutions serving the population"� are couched in the Marxian conceptual framework of net material product; thus, they exclude the labor inputs into personal and oommunal services, and they include depreciation and some other elements not considered to be final consumption expenditures in the West.' The Soviet government publishes neither a cost ' See JEC, GNP, 1950-80. For details, see United Nations, Comparisons of the System of National Accounts and the System of Balances of the National Economy, Part I, Series F, No. 20, New York (1977). 323 of living index, nor a suitable deflator for net material product by end use The official index of retail prices has serious methodblogical and conceptual faults.' Second, progress in raising living standards is a major facet of the challenge that Soviet-style socialism has long posed to Western market-oriented systems. The goal to "overtake and surpass" capitalist rivals was laid down by Stalin in the early 1930s and reiterated with great fanfare by Khrushchev in the early 1960s. Indeed, the Program of the 22nd Party Congress was designed to bring Soviet society to communism "in the main" by 1980, when the Soviet people would have a "standard of living higher than that of any capitalist country." ' Thus, provision of a reliable measure of real gains in living standards is key to an evaluation of the Soviet Union's progress toward its goal.' The CIA index is the only Western-type mea- sure of consumption that has been constructed and kept up to date for the entire period since 1950. The results of its several recent versions have been pub- lished periodically in JEC compendia on the Soviet economy.' The index described i,n this paper is a somewhat revised version of that published in JEC. 1979. Two other Western-type indexes are available for a part of the period�indexes for 1950-58 by Bergson and Chapman ' and an index for 1958-64 by Becker.' These indexes have not been revised to take account of more recent information or extended to later years. The CIA index thus fills a large gap in Western research on trends in levels of living in the Soviet Union in the post-war years. The index is kept continuously under review, with a view to increasing its reliability as new information permits. 'Gertrude E. Schroeder, "An Appraisal of Soviet Wage and Income Statistics" and Morris Bornstein, "Soviet Price Statistics" in Treml and Hardt, pp. 307-312, 370-378. 'Pravda, October 19, 1961. The Soviet achievement is evaluated in a comparative framework in Gertrude E. Schroeder and Imogene Edwards, Consumption in the USSR: An International Comparison, US Congress, Joint Economic Committee, 1981. JEC, 1966, Part II-B, pp. 499-529; JEC, 1973, pp. 376-403; JEC. 1976, pp. 620-660; JEC, 1979, Vol. I, pp. 759-789. ' Janet G. Chapman, "Consumption," in Abram Bergson and Simon Kuznets, eds., Economic Trends in the Soviet Union, Cambridge, Harvard University Press, 1963, pp. 235-282. 'Abraham S. Becker, Soviet National Income, 1958-1964, RAND Berkeley, University of California Press, 1969, pp. 119, 222-227. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 The following section provides a brief discussion of post-war trends in per capita consumption and changes in its structure. Then follows a general description and evaluation of the overall index of Soviet consumption and a comparison with official Soviet measures as well as the two measures devel- oped by Western scholars for part of the period. A final section presents, describes and evaluates the component indexes for major categories of goods and services. Descriptions of indexes and weights and the documentation for their derivation are intentionally quite complete. 324 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Consumption Trends and Patterns Trends in Per Capita Consumption The level of living of the Soviet people has improved rapidly during the past 30 years. During 1950-80, real consumption per capita nearly tripled, rising at an average annual rate of 3.5 percent (Table 1). Gains were much smaller in the 1970s than in the 1960s and 1950s, reflecting a slowdown in overall economic growth. While substantial, the growth rates for per capita consumption are well within the bounds of those found in Western countries in the postwar period, and Soviet living standards remain well below those in the United States, Japan, and most of Europe, both East and West.' Over the pe)-iod as a whole, per capita consumption of goods has risen faster than consumption of services, although this relationship was reversed in the 1970s. Among the three major goods categories, by far the fastest growth took place in consumption of durables, as the Soviet government sought to develop productive capabilities for consumer durables from very low levels. Soft goods, too, have been made available in rapidly growing quantities and improved quality and variety. Although quantitative gains in food supplies have been the slowest of the three goods categories, the quality of the diet has nonetheless improved greatly, shifting toward a pattern of less reliance on bread and potatoes and more reliance on meat and dairy products�a shift typical of other countries as per capita income levels rise. This shift toward a more modern dietary pattern slowed in the 1970s as a result of faltering agricultural progress. Among the services, household services as a group grew considerably faster than communal services. Particularly rapid expansion occurred in the provision of transportation, communications, and utilities. In contrast, per capita availability of housing increased very slowly, with per capita living space in urban areas in 1980 still remaining below the minimum norm for health and decency set by the government in 1928. Repair and personal care services increased even more slowly than did housing until the latter half of the 1960s, when the government began a belated push to expand facilities for providing such services. Recreation services, measured mainly by movie and 9 For a detailed international comparison of relative levels and rates of growth of consumption see Gertrude E. Schroeder and Imogene Edwards, op. cit. 325 theater attendance, expanded rapidly during the 1950s but slowed sharply thereafter, reflecting the rapidly growing use of television and less organized forms of recreation. In contrast to the pre-war period, provision of commu- nal services per capita has increased much less rapidly than provision of goods and personal services. Health services have grown somewhat faster than education services over the period as a whole. Growth rates for both services have been quite uneven among 5-year periods, and there has been a pronounced slowdown in the expansion of both in the 1970s. Nonetheless, educational attainment of the population has risen substantially�from almost 5 years in 1950 to a little over 9 years in 1980.'" Health. services measured by the number of doctors and hospital beds per 10,000 population have more than doubled, although the quality of public health services may be seriously flawed, if one may judge from the significant in- creases in infant mortality rates in the past 10-15 years." The discussion thus far has referred to growth rates given by indexes aggregated with weights in estab- lished prices. As noted below, appreciably lower rates result, when component indexes are aggregated with factor cost weights. Differences occur in the growth rates for total consumption, goods, food, household services, and for services as a whole. When the concern is to indicate the expansion of real resources allocated to consumption, the indexes of consumption at factor cost are preferable. A summary comparison of growth rates for consumption and major categories measured in both sets of prices is given in Table 5 below. Changes in the Structure of Consumption The structure of consumption in the Soviet Union has been remarkably stable since 1950 (Table 2). Whether measured in established prices or at factor cost, the respective shares of goods and of services were about '� CIA, USSR: Trends and Prospects in Educational Attainment, ER 79-10344, June 1979, pp 1, 23. Christopher Davis and Murray Feshbach, Rising Infant Mortal- ity in the USSR in the 1970s, US Department of Commerce Bureau of the Census, International Population Reports, Series P- 95, No. 74, June 1980. 93-892 0 - 82 - 22 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 1 Average Annual Rates of Growth of Per Capita Consumption and Major Components in Established Prices, 1950-80 1976-80 1951-80 1951-55 1956-60 1961-65 1966-70 1971-75 Total 3.5 4.5 4.0 2.4 5.1 2.9 2.2 Goods 3.6 4.9 4.2 2.0 5.4 2.8 2.1 Food 2.6 3.4 3.3 1.8 4.3 1.6 1.0 Soft goods 4.8 8.4 5.5 1.9 7.1 3.0 3.1 Durables 9.3 17.4 10.5 3.9 9.1 10.0 5.3 Services 3.3 2.9 3.0 4.2 4.3 3.0 2.5 Household services 4.2 3.5 3.8 4.4 5.8 4.6 3.4 Housing 2.0 1.1 3.1 2.5 2.0 1.7 1.4 Utilities 5.2 4.1 4.7 7.8 5.7 5.3 3.8 Transportation 7.3 10.1 8.9 8.4 8.0 6.1 2.6 Communications 6.0 6.2 5.2 5.N5 7.8 6.3 4.9 Repair and personal care 3.8 0.3 1.1 1.8 8.4 5.7 5.5 Recreation 2.4 7.1 3.0 2.2 1.6 0.6 0.3 Communal services 2.5 2.6 2.3 4.0 3.0 1.5 1.5 Education 2.4 1.5 1.5 5.2 2.9 1.5 1.7 Health 2.6 4.3 3.5 2.1 3.2 1.4 1.3 Table 2 Structure of Consumption in Established Prices and at Factor Cost, 1950, 1960, 1970, and 1980 a (Percent) 1980 1950 1960 1970 Established Prices Factor Cost _Established Prices Factor Cost Established Prices Factor Cost Established Prices Factor Cost Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Goods 77.1 62.8 79.8 65.4 78.9 64.1 78.4 63.6 Food, beverages and tobacco 59.8 53.6 54.9 51.0 51.1 ' '47.1 45.3 42.4 Soft goods 15.2 7.9 19.6 11.0 21.0 12.5 2'2.1 13.6 Durables 2.2 1.3 5.2 3.3 6.8 4.5 11.0 7.6 Services 22.9 37.2 20.2 , 34.6 21.1 35.9 21.6 36.4 Household 9.6 23.2 9.0 22.0 10.2 22.8 11.8 24.2 Housing 2.3 16.2 1.9 14.2 1.6 13.0 1.5 12.2 Utilities 1.2 1.1 1.2 1.2 1.6 1.8 2.0 2.2 Transportation 1.0 1.1 1.7 2.0 2.6 3.2 3.1 4.0 Communications 0.4 0.5 0.4 0.7 0.6 0.9 0.8 1.3 Repair and personal care 3.2 2.4 2.3 1.8 2.6 2.2 3.5 3.0 Recreation 1.4 1.7 1.5 2.0 1.2 1.8 1.0 1.5 Communal 13.3 14.0 11.2 12.6 10.9 13.1 9.8 12.2 Education 8.6 9.2 6.6 7.6 6.8 8.3 6.2 7.8 Health 4.7 4.8 4.6 5.0 4.1 4.8 3.6 4.4 Derived from ruble values in 1970 prices. Because of rounding, components may not add to the totals shown. 326 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 the same in 1980 as they were in 1950. Essentially the same finding holds true when patterns are compared in current prices. Within the goods category, however, there has been a relatively slow decline (by interna- tional standards) in the share of food, beverages, and tobacco and a concomitant rise in the share of soft goods and especially durables.I2 This direction of change is to be expected from Engel's law concerning the relationship of expenditures on food to total consumption expenditures as incomes rise. Within the services, there has been a small increase in the role of personal services and a moderate drop in the role of communal services. The shares of transportation and communications have risen appreciably, while the share of housing has declined. '2 These matters are explored in more detail in a comparative framework in Schroeder and Edwards, op. cit. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Description and Evaluation of the Consumption Index The Index in Established Prices General The index of total consumption shown in summary form in Table 3 and in detail in Appendix A is a weighted aggregate of separately constructed indexes for three broad categories of goods�food, soft goods, and durables and miscellaneous goods�six categories of personal services�housing, utilities, transporta- tion, communications, repair and personal care, and recreation�and two communal services�education and health. The indexes for major categories, in turn, are weighted aggregates of varying numbers of com- ponent indexes. The aggregate index is a sample index based to a considerable extent on time series in physical units. The sample is large and in one way or another represents more than 90 percent of all consumption expenditures. All important foods, soft goods, and durables are included, as are most personal services and all education and health services. Both the sample categories and the time series selected to represent them were severely constrained by the availability of published Soviet data. Ideally, one would like to have suitable and detailed expenditure time series and corresponding reliable price deflators. In general, the Soviet government publishes neither. Data on retail sales, regularly published in current prices with a disaggregation of several dozen groups, are flawed by the presence of sizeable residual groups of obscure content and by inclusion of sales to enterprises and sale of intermediate and investment goods that do not reflect household consumption. Retail sales data also include sales of so-called "productive" services, such as shoe repair. The data with which to remove or reclassify these various items are not available over time. Official retail price indexes are seriously defec- tive, as already noted, since they reflect official price changes only on a fixed sample of basic products; the index is, in essence, an index of prices on an official price list and not an index of prices paid by consumers for goods actually available for purchase. The Soviet government publishes neither quantities nor values for consumption in kind, a major element in total food consumption. Neither expenditures nor price indexes are available for most personal services. Official data on government outlays for education and health are in current prices, and include transfer payments and some expenditures that belong to investment rather than to consumption. In general, the Soviet Union publishes only a small fraction of the data that are required, ideally, to construct a reliable consumption index; moreover the definitions and methodologies underlying the pub- lished data are seldom available in more than cursory detail. As a result of these problems with the data, the quality of the components of the CIA indexes is uneven. Most satisfactory, perhaps, are those for food, soft goods, transportation, and communications: least satisfactory are those for durables and miscellaneous goods and for recreation. The indexes for housing and for communal services suffer from an inability to reflect improvements in quality; this shortcoming is not unique to the indexes constructed here for the USSR, however. Each of the major component index- es is evaluated below with respect to coverage and quality of the time series data and internal weights within major components. Several sources of possible bias exist. The choice of 1970 as the base year may impart some bias to the index. In general, however, 1970 was a fairly "normal" year for consumers, in the sense that no major crop failure or other unusual event occurred. The matter of the degree of overall equilibrium in consumer goods markets is considered below. To test the effect of the choice of base year, alternative weights for major categories on a comparable basis were constructed for 1960 and 1976. Rates of growth shown by the three sets of weights do not differ much. The use of 1960 weights speeds up the index some- what, while the use of 1976 weights instead of 1970 weights has a negligible impact on the index. Table 4 summarizes the growth rates given by alternative sets of weights for major categories. The use of time series expressed in physical units may bias the index downward because of the inability to allow fully for improvements in quality. This source of bias could be significant, probably, only for footwear, hosiery, and knitwear and perhaps for education and health services. On the other hand, those series that 328 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 3 Indexes of Total Consumption and Major Categories, Selected Years, 1950-80 1970 Weights 1950 1955 1960 1965 1970 1975 1980 (Percent) Total Consumption 100.0 33.8 45.9 60.9 74.0 100.0 120.7 140.4 Goods 78.9 33.1 45.8 61.6 73.2 100.0 120.4 139.5 Food 51.1 39.5 50.9 65.5 77.2 100.i, 113.6 124.5 Soft goods 21.0 24.5 39.8 57.0 67.4 100.0 121.5 147.7 Durables 6.8 10.8 26.3 47.3 61.6 100.0 168.9 227.9 Services 21.1 36.6 46.1 58.3 77.0 100.0 121.7 143.7 Household services 10.2 31.6 40.8 53.7 71.8 100.0 131.2 161.6 Housing 1.6 48.1 55.4 70.6 86.0 100.0 114.1 127.4 Utilities 1.6 25.1 33.4 45.9 72.1 100.0 135.7 170.4 Transportation 2.6 13.6 24.0 40.1 64.8 100.0 141.2 167.6 Communications 0.6 22.4 33.1 46.5 65.4 100.0 142.0 187.9 Repair and personal care 2.6 42.1 46.6 53.8 63.5 100.0 138.1 188.0 Recreation 1.2 37.6 57.6 73.0 87.7 100.0 108.0 114.3 Goods and household services 89.1 32.9 45.3 60.7 73.1 100.0 121.6 142.1 Communal services 10.9 41.4 51.1 62.6 81.9 100.0 112.7 126.9 Education 6.8 42.8 50.3 59.3 82.3 100.0 112.7 127.8 Health 4.1 39.0 52.5 68.0 81.3 100.0 112.6 125.2 Table 4 Growth Rates of Total Consumption and Major Categories, Alternative Base Year Weights in Established Prices 1951-60 1961-70 1971-80 1960 Weights 1970 Weights 1976 Weights 1960 Weights 1970 Weights 1976 Weights 1960 Weights 1970 Weights 1976 Weights Total consumption 6.7 6.1 6.0 5.4 5.1 5.1 3.7 3.5 3.4 Goods 7.2 6.4 6.4 5.3 5.0 5.0 3.6 3.4 3.3 Food 6.1 5.2 5.2 5.0 4.3 4.5 2.4 2.2 2.2 Soft goods 8.8 8.8 8.7 5.3 5.8 5.3 4.3 4.0 3.9 Durables 15.9 15.9 15.9 7.8 7.8 7.8 8.6 8.6 8.8 Services 4.0 4.8 4.7 5.8 5.6 5.5 4.0 3.7 3.6 329 , Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 are based on deflated retail sales or value of produc- tion in "constant" prices may impart an upward bias to the index, because of the dubious reliability of the official price indexes used as deflators. These two sources of bias tend to offset each other. Judging from a mass of anecdotal evidence from the Soviet press concerning the poor quality of consumer goods and hidden price inflation, however, one might conclude that the upward biases are predominant. There is no good way to assess the matter. Category Weights The expenditure weights used to aggregate the 11 major categories of goods and services are those for 1970 estimated in the calculations of GNP by end use in established prices. A full description of the sources and methods of their derivation is given in CIA, GNP 1970. The weights shown there have been revised considerably to fake into account additional or more recent information and an improved understanding of Soviet data; the revisions are described in Appendix D of JEC, GNP, 1950-80. The revisions reduced total consumption by 4 percent and raised the share of goods as opposed to services. A summary description of the revised weights follows: Goods. The weights for food and soft goods are the sum of (1) retail sales reduced to reflect only house- hold purchases for consumption, (2) consumption in kind estimated in physical units valued at average prices realized by producers ("farm gate" prices) and (3) military subsistence estimated by valuing rations in 1970 prices. The weight for durables and miscella- neous goods represents retail sales reduced to reflect only household purchases for consumption. Household services. The weights represent estimated household expenditures on these services based on a wide variety of Soviet sources, mainly studies by individual researchers published in books and journal articles. Communal services. The weights are the sums of estimated expenditures for education and health (1) by households based on a variety of Soviet and other sources and (2) by the government, derived from official data on wages and employment and on budget expenditures for other items, net of investment outlays and stipends. On the whole, the expenditure weights are considered to be quite reliable. Although nominal consumption may be overstated because of inability to remove some non-consumption expenditures from retail sales of goods and services, the total can be reconciled fairly well with official Soviet values for consumption. The total, of course, does not take into account black market prices and other activities carried on in the illegal "second" economy. Such activities are not included in GNP in other countries either. In the Soviet case, moreover, they probably generate mainly price increases and income transfers rather than additions to the supply of real goods and services.'' As for individual category weights, which are based on specific Soviet sources and assumptions, their magni- tudes generally are supported by other information that is available. Also, the revealed expenditure pat- tern agrees well with that given by official statistics based on family budget surveys (Narkhoz 1977, pp. 409-410), and, in general, with what one would expect on the basis of international comparisons for a coun- try at the USSR's level of development as measured by per capita GNP and consumption:4 Data from surveys of the family budgets of urban Jewish emi- grees also support the relationships, when allowance is made for the unrepresentative composition of the sample." The 1970 weights used to aggregate the component indexes, both for major categories and for their sub- categorits, are probably about as accurate as can be obtained with the data base and understanding of its meaning that are available at present. Although a number of estimates and assumptions had to be made in the process of constructing these weights, the impact of any errors cannot be large. If anything, the values for consumption as a whole and for some categories are probably overstated, a tentative conclu- sion stemming from the fact that successive revisions in the weights, based on new information invariably produced lower values. The data underlying the weights for individual sub-categories are of uneven quality, a matter that will be considered in the following section. Many personal services are provided privately, both legally and illegally. The expenditure weights for repair and personal care and health and education services include a substantial allowance for such services, based on a variety of information. ' Data on comparative expenditure patterns are given in Schroeder and Edwards, op. cit.; International Labour Office, Household Income and Expenditure Statistics, No. 3, 1968-1976, Geneva, 1979; V. Cao-Pinna and S. S. Shatalin, Comparison Patterns in Eastern and Western Europe, New York, Pergamon Press, 1979. " Gur Ofer and Aaron Vinokur, Private Sources of Income of the Soviet Urban Household, RAND, R-2359-NA, August 1980, pp. 53-69. 330 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Indexes The indexes of total consumption and major compo- nents provide, it is believed, a reasonably reliable measure of the growth of real consumption in the USSR since 1950. Because the index is designed to measure as closely as possible real consumption of goods and services as measured in the West, this overall judgement lends confidence to international comparisons of relative progress in raising levels of living in the USSR and in other countries. The index is also a better indicator of the growth of consumption in the postwar period than are the Soviet official statistical series intended for that purpose, because the index is more inclusive and because it largely avoids the use of the unreliable official retail price indexes. The index is considered much more reliable for depicting long-run trends than year-to-year changes. Inaccuracy in measuring the latter stems from the limitations of data availability. Absence of data for particular years necessitated interpolation in a num- ber of cases, or resort to estimates based on a variety of evidence in other cases. Also, use of production data to represent some series may distort annual changes in actual consumption, especially for agricul- tural products; however, adjustments for inventory change and net foreign trade were made where avail- able data permitted doing so. The individual time series selected to measure con- sumption of particular categories of goods and serv- ices necessarily were constrained by the availability of data. Every effort was made to scour the literature and to select or construct data series that seemed most suitable as measures of changes in real consumption over time. Some series are based on measures of production or of consumption expressed in physical units (kilograms, square meters, kilowatt-hours and the like); others are based on deflated retail sales, while others are deflated government expenditures. The series are of uneven quality, a point that will be elaborated later for each major component index. Indexes at Factor Cost and in Adjusted Market Prices Factor Cost As Bergson has shown,16 measures of Soviet consump- tion in established prices (prevailing ruble prices) 1' Bergson, 1961, pp. 103-126. require modification to correct for distortions in So- viet prices, which fail to reflect either full resource costs (production potential) or consumers' marginal utilities as they would be expressed in a free market. Where the concern is with production potential (and perhaps also with welfare in terms of planners' prefer- ences), ruble prices need to be adjusted (1) to remove turnover taxes, now levied mainly on soft goods, durables and alcoholic beverages; (2) to add subsidies, now applicable mainly to food and to housing; and (3) to allow for a resource charge for capital. A factor cost adjustment to 1970 ruble values has been made for GNP and its end-use components.'' For consump- tion the procedure resulted in a net reduction in total' consumption of 3.3 billion rubles, or 1.6 percent. Table 5 compares the growth rate of consumption and its major components aggregated (1) with established price weights and (2) with 1970 ruble factor cost weights. The factor cost weights reduce the growth of total consumption by about one-tenth for the period as a whole because the adjustment raises the weight of the relatively slow-growing housing component and reduces the weight of the fast-growing durables com- ponent. Also, the index of food, beverages, and tobac- co grows more slowly when factor cost weights are used, because the factor cost adjustment raises the weight of the relatively slow-growing animal products sub-index and sharply reduces the weight of the very fast growing index of beverages. Meat prices are heavily subsidized, and alcoholic beverages are heav- ily taxed. The adjustment reduces the share of consumption in GNP in 1970 from 55.1 percent to 54.2 percent. The effects on relative shares of major categories within consumption in 1970 are shown in Table 2. Adjusted Market Prices Bergson also considered the question of the extent to which relative prices in consumer goods markets in the USSR conform to his "consumer utility stan- dard."" For retail prices to reflect relative utilities in the Soviet context, consumers must be free to dispose of money incomes as they choose and government price-fixing must succeed, by and large, in limiting demand to supply. Consumption in kind, in turn, should be valued at retail prices that reflect consumer utilities. Similarly, housing rents should reflect the levels that would obtain in an open market. For a description of the procedure, see JEC, GNP, 1950-80. ' Bergson, 1961, pp. 157-172. 331 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 5 Average Annual Percent Growth Rates of Total Consumption and Major Categories in Established Prices and at Factor Cost, Selected Years, 1950-80 1951-60 1961-70 1971-80 Established Prices Factor Cost Established Prices Factor Cost Established Prices Factor Cost 3.1 3.0 2.0 4.0 8.6 3.2 Total consumption 6.1 5.3 5.1 4.5 3.5 3.4 2.2 4.0 8.6 3.7 Goods 6.4 5.7 5.0 4.3 Food 5.2 4.8 4.3 3.7 Soft goods 8.8 8.8 5.8 5.8 Durables 15.9 15.9 7.8 7.8 Services 4.8 4.5 5.6 4.9 How did the situation in markets for consumer goods and services in 1970 conform to this theoretical standard? What adjustments in the 1970 established price weights would be needed, if they were to reflect relative utilities? We consider in turn, retail prices of goods, consumption in kind, and household services, including housing. The overall Market for consumer goods and services in 1970 probably was not seriously in disequilibrium. In that year, the average savings rate was a low 5.2 percent, although the marginal propensity to save jumped sharply.' This change probably reflected con- sumers' reaction to the expected (and actual) rapid increase in the number of new cars made available for purchase by the population. Cash is required for purchase of such high-priced durable goods, and people's expectations of being able to obtain one of these much desired items were greatly heightened. Clearly, however, there were numerous disequilibria in markets for individual goods and services-sur- phises of some items, manifested in Spring clearance sales and price cuts and some "above norm" inventory accumulations-and shortages of other goods, reflect- ed in sporadic queues and reported black markets. With respect to products (mainly food) sold in both types of outlets, prices paid in ex-village collective farm markets (CFMs) exceeded the prices paid in state and cooperative retail outlets by an average of 59 percent. A part of that difference reflects the much superior quality of the products sold in CFMs. We " JEC 1979, p. 766. might assume that half of the differential is a quality premium, leaving the rest to be accounted for by the inability to obtain the fresh foods involved in state stores. If the total quantity supplied were sold on a single market, the uniform price would be above the average state store price, but below the CFM average price adjusted for quality. Since the price and income elasticities of demand, as well as the individual prices and quantities of the products involved are not known, the equilibrium prices cannot be determined. If they were known, the relevant values used as weights in the index theoretically would need to be adjusted to reflect those prices. To provide an idea of the size of the adjustment, we assume that for the products involved (fresh foods) the average state price is 30 ,percent below the average CFM price, taking into account quality differences. Valuing state store sales at that price adds 5.6 billion rubles to consumption. As Bergson notes, consumption in kind theoretically also should be valued at that "equilibrium" price- here assumed to be 30 percent above the state store level-less distribution and processing markups. In 1970, food subsidies paid by the state to food proces- sors to compensate for the difference between pro- curement prices and retail prices for meat and milk amounted to some 11.9 billion rubles. The estimated gross subsidy per ton was 694 rubles for meat and 68.32 rubles for milk." Household consumption in kind can be revalued at the subsidized prices after deducting processing and distribution costs estimated at 10 percent of those values. The results then need to be again revalued to reflect the assumed retail "equi- librium" price of 30 percent above the state price level. For products other than meat and milk, a rough " Constance B. Krueger, ACES Bulletin, Fall, 1974, pp. 66-67. 332 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 allowance of 10 percent was made for processing and distribution costs of state procured products, and the average retail prices so estimated were then raised by 30 percent to bring them to the assumed "equilibri- um" price. The final result is to reduce consumption in kind by 5.6 billion rubles (12.7 compared with 18.3). Military subsistence is assumed to be correctly valued in terms of the consumers utility standard, since the original prices are a combination of retail and CFM prices, more or less. The effects of the two hypothetical adjustments to 1970 valuations cancel out, leaving the value of the goods component of consumption unchanged. Relative prices for housing and some household ser- vices in 1970 clearly did not correspond to the result that would have obtained in an open market. Urban housing was rationed and rents heavily subsidized; the basic rental rate was the same as in 1928. Prices for utilities, public transport, communications and other services also had remained fixed for many years. Following Bergson's approach, we revalue housing and household services in 1970, so that their price is related to that for goods in the ratio that prevailed in the United States in 1976. We use the ruble/dollar ratios given in the paper by Schroeder and Edwards." The result is to more than treble the value of these services, raising it from 21.6 billion rubles to 68.4 billion rubles. Education and health services, mainly government provided and valued at current cost, are re-valued at factor cost, thus increasing their level from 23.0 billion rubles to 27.2 billion rubles. The impact of all these revaluations is shown below: Established Billion Rubles Prices Percent Adjusted Prices Billion Rubles Percent Goods 166.5 78.9 166.5 63.5 Household services 21.6 10.2 68.4 26.1 Education & health 23.0 10.9 27.2 10.4 Total 211.1 100.0 262.0 100.0 When the indexes are reweighted with adjusted price weights, the average annual growth of consumption during 1951-80 is 5.2 percent instead of 4.9 percent. The index is speeded up a little because of the much Gertrude E. Schroeder and Imogene Edwards, op. cit., p. 73. larger weights given to the most rapidly expanding categories-household services, most notably trans- portation, communications and utilities. The structure of Soviet consumption in adjusted prices more closely resembles that of developed market economies, such as Italy, than does the structure in established prices; in those prices, the ratio of goods to all services resembles that of India. It could be argued that in 1970 excess de- mand for housing was relatively much greater than that for household services; indeed, excess demand for such services as public transportation, communications and utilities was not especially evident (i.e., by queues and waiting lists). To consider the effect of this possibility, the above calculation was carried out with a revaluation only for housing among the household services. The result was to slow the index of total consumption somewhat-from an average annual growth of 4.9 percent to 4.5 percent during 1951-80. Comparison With Other Indexes Official Soviet Measures As already noted, the Soviet government does not publish an index of real per capita consumption that can properly be compared with measures available for Western countries. For a number of years before 1976, the government published periodic data on total "personal consumption" and "material expenditures of institutions serving the population" in current rubles. The only published deflator related to final consumption is an index of retail prices in state and cooperative outlets. The index which shows almost no change in the price level since 1955, has been judged seriously unreliable." Indexes of collective farm mar- ket prices in the USSR as a whole have not been published since 1968, although an aggregate index can be calculated indirectly from regularly published data. The Soviet consumption data refer to consumption as a component of national income (net material prod- uct), omitting labor in all services but including some depreciation on housing and on the capital stock in the services sector. For 1961-1975, the only period for which a comparable series in available, the Soviet measure of total consumption per capita deflated by " See articles by Gertrude E. Schroeder and Morris Bornstein in Treml and Hardt, pp. 307-312, 370-376. 333 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 an index of official retail prices (including CFM prices) grows much more rapidly than the CIA index of real per capita consumption. Soviet Measures Current Prices Constant Prices CIA Index Constant Prices 1960 100.0 100.0 100.0 1975 211.1 209.6 166.8 Average annual growth 5.1 5.1 3.5 The Soviet government also gauges progress in raising living standards by a regularly published statistical series labeled "real incomes of the population," ex- pressed per capita. Although the exact nature of this published statistic is something of a puzzle 23 it apparently measures real per capita consumption of goods and material services.' As described in an official source, the \calculation for each year: (1) begins with money incomes from all sources (2) deducts taxes, savings, change in bank loans and cash balances, and payments for services to arrive at money expenditures for the purchase of goods (3) adds incomes in kind, material expenditures (including depreciation) of insti- tutions serving the population�transportation, health, education and others�payments for utilities, the value of cooperative housing constructed, and depreciation on state housing, and (4) deflates current values with an index of the prices of goods. In coverage, it differs from the CIA index of consumption, mainly by inclusion of cooperative housing, depreciation on housing and on the capital stock in services and by exclusion of labor services. As Table 6 shows, the official index grows much more rapidly than the CIA index�almost half again as fast for the period as a whole. The difference is greater in the 1970s than in earlier periods. The reasons for the faster growth of the official index of real incomes are obscure. Neither the structure of that index in current values nor the deflator has been published. Why the official index increases more rapidly compared with the CIA index in some periods than in others also is not evident. Differences in " Gertrude E. Schroeder in Treml and Hardt, pp. 304-307. " The most complete description of how real incomes apparently are calculated is given in USSR Gosplan, Metodicheskiye ukazaniya k razrabotke gosudarstvennogo plana razvitiya narodnogo kho- zyaystva SSSR, Moscow, 1969, pp. 499-505. (Hereafter referred to as Metodicheskiye ukazaniya.) coverage may be part of the explanation, for the CIA index includes personnel services in education, health and other services, which apparently grow more slow- ly than materials used in these sectors. The main reason however, seems to lie in the faulty price index used in the Soviet index to deflate current expendi- tures and imputed depreciation. The CIA index, in contrast, attempts to measure real quantities of goods and services consumed. Comparison of this index with an index in current prices provides an implied mea- sure of price inflation. Other Western Measures Only two Western measures of Soviet real consump- tion are available for comparison with the CIA index- es�one calculated by Janet Chapman " for the peri- od 1950-58 and one calculated by Abraham Becker " for the period 1958-64. The construction of both of these series begins with estimates of consumption constructed in current prices. The sub-categories of consumption are then deflated by price indexes of one kind or another. Both measures follow concepts and methodologies developed by Abram Bergson. The Chapman index for 1955-58 and the Becker index, in effect, employ Soviet official price deflators for goods purchased at retail prices. The Chapman index for 1951-55 uses Bergson's calculations for the period." The implicit Bergson-Chapman deflator gives nearly the same rate of price change for the period as does a weighted index of official indexes of prices in state and cooperative stores and of prices on collective farm markets."'The Bergson-Chapman implicit price index for 1955 (1950=100) is 78.0;" the combined official price index is 77.6 or 76.7, with 1950 and 1955 weights, respectively. With respect to the other components, matters are more complex. In general, the Bergson and Becker indexes (1) value consumption in kind, housing, and personal services in physical quantities in constant sets of prices (2) deflate the wage component of expenditures on health and education by an index of wages and (3) deflate nonlabor expenditures on health and education by composite deflators compiled from various sources (Bergson; Becker elected not to deflate such expenditures.) The Chapman index for 1956-58 Janet G. Chapman, /oc. cit., in 7 'above. " Abraham Becker, /oc. cit., in above. " Bergson, 1961, pp. 307-308. " Narkhoz 1958, pp. 699, 771, 787. " Bergson, 1961, pp. 46, 85. 334 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 6 Comparison of Official and CIA Measures of Soviet Per Capita Consumption Indexes Average Annual (1950=100) Rates of Growth (Percent) Soviet Index CIA Index of Soviet CIA of Real Incomes per Capita a Real Per Capita Consumption b Index Index 1950 100 100 1955 142 125 1951-55 7.3 4.5 1958 173 143 1956-60 5.6 4.0 1960 187 151 1961-65 3.6 2.4 1964 209 163 1966-70 5.9 5.1 1965 223 171 1971-75 4.4 2.9 1966 236 179 1976-80 3.4 2.2 1967 252 189 1968 268 200 1951-60 6.5 4.2 1969 281 210 1961-70 4.7 3.8 1970 297 219 1971-80 3.9 2.5 1971 310 226 1972 323 229 1951-80 5.0 3.5 1973 339 236 1974 352 244 1975 368 252 1976 384 257 1977 397 263 1978 408 269 1979 419 276 1980 435 - 282 a The index was put together from indexes for various periods given in Narkhoz 1965, p. 593; Narkhoz 1967, p. 674; Narkhoz 1970, p. 537; Narkhoz 1975, p. 567; and Narkhoz 1980, p. 380. b Table A-2. Growth rates were calculated from unrounded data. is deflated variously by a cost of living index given in a Soviet source, the official index of state retail prices, and an index of the change in average wages. Table 7 compares the rates of growth given by the Bergson, Chapman, and Becker indexes of total con- sumption with the rates shown by the CIA index. As can be observed, the CIA index increases more slowly than the other Western indexes in all of the periods compared. Many reasons could account for the diver- gence�somewhat different concepts, different treat- ment of some expenditure categories, data availabil- ities, and others. Since none of the indexes has been extended to recent years, there seems little point in trying to measure the impact of these factors. Prob- ably the main reason for the differences is that the CIA index is largely an aggregation of physical measures of consumption weighted by expenditures in 1970 prices, while the other Western indexes employ earlier base-year weights and rely much more heavily on deflated value measures, with the deflators differ- ing little from the official retail price indexes pub- lished by the Soviet government. Also, in constructing the CIA index, use could be made of a considerably larger body of data and information that has become available in the past 15-20 years. 335 ' Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 7 Average Annual Percentage Rates of Growth Comparisons of CIA Index of Total Consumption With Indexes Constructed by Bergson, Chapman, and Becker 1951-55 1956-58 1951-58 1959-64 CIA , 6.3 6.5 6.4 3.9 Bergson b Chap- man c 9.1 (8.1) 7.9 7.4 7.7 Becker d 5.3 a Table A-1. b Consumption is valued at 1950 prevailing prices. (Bergson, 1961, pp. 85, 149). Figure in parenthesis reflects a valuation in 1950 ruble factor cost. c Chapman, /oc. cit., pp. 238, 271. The index for 1951-55 is calculated in adjusted market prices of 1937, taken or derived from data in Bergson, 1961, pp. 128, 134, 165. The extension to 1958 is based on estimated values in current prices and various deflators. Sources are given in Chapman, /oc. cit., p. 272. d Underlyng values are in 1958 established prices. Becker, 1969, p. 526. 336 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Description and Evaluation of Component Indexes Goods The index of goods is the weighted sum of three category indexes�food, soft goods, and durables and miscellaneous goods. The weights are expenditures on the three categories in 1970, derived as explained in detail in CIA, GNP 1970 and in Appendix D of JEC, GNP, 1950-80. The weights for sub-indexes of the three major category indexes are consistent in concept and method of derivation with the major category weights. All weights are shown in ruble values or percentages in Appendix A, along with the indexes. Food, Beverages, and Tobacco Scope and Coverage. The category Food, Beverages and Tobacco comprises (1) household purchases of these items in state and cooperative retail outlets and in collective farm markets, including purchases in restaurants and canteens (2) household consumption in kind of food products, obtained mainly from private farming and (3) military subsistence. The concept coincides with the category "Food and Tobacco" in the personal consumption expenditures in US national accounts. Although the index is a sample index, it covers 94.4 percent of estimated total consumption of the relevant products. Only minor food items, such as salt, spices, and condiments, are not included; all important alcoholic and nonalcoholic beverages, ex- cept kvass and coffee, and all tobacco products are included. The composite index is a weighted aggregate of 18 sub-indexes 15 for foods, two for beverages and one for tobacco. The weights for the sub-indexes represent expenditures in 1970 prices derived to be consistent in concept with the weights for the category as a whole. The weights for the sub-indexes are considered rea- sonably reliable. The sub-indexes are based on phys- ical quantity series except for the indexes for macaro- ni and for tobacco, which represent deflated retail sales. Indexes and weights are shown in Appendix A. Table A-1; underlying data and sources are given in Appendix B. Ten sub-indexes for food products, with 63 percent of the weight, are based on official data on per capita consumption of these products in kilograms or phys- ical units. The consumption data, which have been published regularly since 1965,' are based on a variety of sources, principally on balances of the supply and uses of agricultural products and on periodic family budget surveys. While the latter have been criticized for lack of representativeness, the results they give, according to Soviet statements, are checked against availabilities given by the product balances. Although the absolute levels in any one year must be used with great care in international com- parisons (because of definitional problems), the data are considered reliable in trend. They are reasonably consistent with statistics for production, intermediate uses, changes in inventories, and net imports. The present approach to constructing the food index uses all of the per capita consumption series that are published and replaces an extremely complex method- ology used earlier.' That approach relied on produc- tion data, with numerous adjustments and estimates being required to fill in gaps in information. The physical consumption data are believed to provide an improved measure of year-to-year changes in con- sumption, compared with the production-based series. Four sub-indexes for food products and the two sub- indexes for beverages with a total weight of 34 percent are based on physical production data, adjust- ed where possible for inventory change, net imports, and quality changes. Data availabilities constrained the extent of such adjustments. Such lacunae, along with gaps in the series of data on per capita consump- tion, reduce the reliability of the sub-indexes, espe- cially with respect to year-to-year changes. The two sub-indexes based on deflated retail sales (3 percent of the total weight) employ official retail price indexes as deflators; these indexes probably are not seriously in error for the two products concerned (macaroni and tobacco). They do take account of changes in quality and mix, however. Although such changes are not reflected in the series based on consumption in physical units, this failure is probably not too serious in the case of most food products. " The method of calculating the physical measures of per capita consumption is described in Vest slat. No. 2, 1968, pp. 46-50. This methodology was used to construct the index that was published in JEC, /976, pp. 641-650 and in all versions published earlier. 337 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 8 Derivation of 1970 Weights for Components of the Index of Food, Beverages, and Tobacco Retail Sales for Consumption a (Billion Rubles) Military Subsistence c (Billion Rubles) Consumption in Kind d (Billion Rubles) Total Consumption CFM Sales for Consumption b. (Billion Rubles) (Billion Rubles) (Percent) Total 79.924 3.001 1.970 16.964 101.859 100.00 Meat 11.793 1.024 .690 6.702 20.209 19.84 Fish 2.963 .110 3.073 3.02 .98 Vegetable oil .844 .058 .094 .996 Margarine .621 .621 .61 Milk 4.508 .293 .071 4.148 9.020 8.86 3.20 .71 Butter 2.677 .121 .461 3.259 .723 Cheese .723 Eggs 1.573 .231 .165 1.679 3.648 3.58 Sugar 5.089 .080 5.169 5.07 Confectioneries 5.744 5.744 5.64 Tea .580 .020 .600 .59 Flour and groats 9.295 .130 .377 .309 10.111 9.93 Macaroni .534 .014 .548 .54 Potatoes .718 .753 .072 2.490 4.033 3.96 3.24 Vegetables 2.486 .224 .072 .517 3.299 Fruit 3.130 .346 .120 .564 4.160 4.08 23.43 Alcoholic beverages and soft drinks 23.866 23.866 Tobacco 2.780 2.780 2.73 a Retail sales reported in Narkhoz 1972, pp. 584-585, minus purchases by state enterprises and institutions in small-scale wholesale trade (melkiy opt). Such purchases were deducted, based on their reported shares in 1968-1969 as given in Vest stat, No. 5, 1971, pp. 36-37. No attempt was made to distribute the deduction for business restaurant meals or the reported total value of the markup added to the costs of products sold in restaurants. Collective farm market purchases were distributed by product group on the basis of the following data: (1) a distribution of sales in all CFMs in 1957 (1. D. Ignatov, Puti razvitiya kolkhoznoy torgovli, Moscow, 1959, p. 15; (2) indexes of the physical volume of total CFM sales during 1958-68 (Narkhoz 1959, p. 708 and Narkhoz 1968, p. 654); (3) price indexes for 1958-68 compiled from those for all CFM sales during 1958-63 (Narkhoz 1959, p. 667; and Narkhoz 1968, p. 655); (4) ruble values for 1957 obtained from the shares given in Ignatov and a value of total sales given in Narkhoz 1959, p. 708; (5) extending these values to 1968 with current value indexes dervied from the indexes of physical volume and price; (6) assuming that the relative shares so obtained for 1968 held in 1970. Institutional purchases were deducted, based on information in Vest slat, No. 5, 1971, p. 39. CIA estimates based on information concerning the basic military food ration and its estimated costs. d,ciA, GNP 1970, pp. 32-35. A value for fruit was estimated using the methodology described thefe..The value for butter represents the milk equivalent of 104,000 tons of private production Narkhoz 1970, p. 151) valued at average realized prices. Consumption in kind of sunflower seeds was allocated to vegetable oil. 338 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Weights. The derivation of the 1970 weights for the sub-indexes is shown in Table 8. Essentially, the task was to disaggregate the components of the total weight�retail sales for consumption, collective farm market sales for consumption, military subsistence, and consumption in kind. The distribution of retail sales (the bulk of the total) could be made with considerable confidence, using published retail sales data and the assumption that the distribution of sales to enterprises and institutions was the same in 1970 as in 1968-69. Lack of data precluded allocation of the public catering markup, amounting to 2.4 percent of total retail sales of food and beverages. The distribu- tions of CFM sales and military consumption are far less certain, but probably not grossly wrong. The distribution of consumption in kind is given by the methodology for estimating its total value and is thought to be reasonably accurate. Indexes. The primary data underlying all of the sub- indexes are given in Appendix B. Ten sub-indexes are based on officially published data for per capita consumption expressed in kilograms or units; these data are converted to total consumption using mid- year population data. These sub-indexes are: meat, fish, vegetable oil, milk, eggs, sugar, flour and groats, potatoes, vegetables, and fruit. Consumption so ob- tained for milk was reduced by milk used to produce cheese and butter: consumption of sugar was reduced to remove sugar used to produce confectionery pro- ducts: consumption of flour and groats was reduced to remove flour used in the production of confectioneries and macaroni. The basic data on per capita consump- tion are given for 1950, 1958, 1960, and 1964-65 in Narkhoz 1965, p. 597; for 1966-67 in Narkhoz 1967, p. 697; for each year 1968-80 similar data are pub- lished in the respective year's Narkhoz in similar tables. Data for the years 1951-57 and 1959 were interpolated on the basis of growth rates for produc- tion of each product over the intervening periods. While the results for the period as a whole are reasonably consistent with production data, the rates of growth for 1951-55 and 1956-58 shown by the physical consumption data are subject to considerable and probably varying margins of error. Values for 1961-63 also were obtained by interpolation, by use of production data, or with data on the value of con- sumption in current rubles given in Narkhoz 1964, pp. 580-81. The data required to remove the milk, sugar, and flour used in making those products for which separate sub-indexes are calculated are found in various statistical handbooks and a variety of other Soviet sources, as are the data used to calculate indexes of quality change for confectionery products and for flour and groats. Six of the component indexes are based on production in physical units: margarine, butter, cheese, confec- tioneries, tea, and alcoholic beverages and soft drinks. Where necessary and possible, the production data were adjusted to allow for net imports and net inventory change. The index for beverages is the sum of production in dekaliters of 7 products, combined with 1970 average price weights. Data on imports and exports are regularly published in the annual trade handbooks (Vneshnaya torgovlya SSSR). Data on wholesale and retail inventories were regularly pub- lished in two tables in the annual Narkhozy (e.g. Narkhoz 1972, pp. 591, 593) until 1976; the tables were dropped from the handbooks after 1975, thus introducing some inaccuracies in the indexes for subsequent years. The indexes for confectioneries and flour and groats incorporate indexes of quality to reflect changes in product mix. The indexes for tobaccd. and macaroni are based on deflated retail sales, using official Soviet retail price indexes. Soft Goods Scope and Coverage. The "soft goods- category com- prises (1) household purchases of 16 categories of consumer nondurable goods that are explicitly listed in Soviet retail trade data, plus an estimated share of an unidentified residual in those data; (2) household purchases of similar goods in collective farm mar- kets-----a minor item; (3) military consumption of such goods; and (4) consumption in kind of wool. Over four- fifths of the weight for the category consists of clothing and footwear and related items. Although the index for soft goods is based on a sample, it covers 94 percent of the total estimated consumption of these goods in 1970. The only items separately listed in Soviet retail trade data that are not specifically ,included are fur products and matches. A variety of odds and ends that are included in residual (unidenti- fied) retail sales are also excluded, however; the most important of these are medicines and gasoline. The index for soft goods is a weighted aggregate of 16 sub-indexes. All but 5 of the 16 pertain to clothing, and footwear (including fabrics). The weights for the sub-indexes were derived in a manner consistent with the derivation of the weight for the category as a 339 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 whole. They are considered to be quite reliable. Seven of the indexes with 72 percent of the weight are based on production series, and the rest are based on deflated retail sales, using official retail price indexes. When possible, the indexes based on physical produc- tion data have been adjusted for net foreign trade and inventory change. Three of these indexes can be compared with indexes derived from official Soviet data on per capita consumption in physical units and with deflated retail sales. The comparisons are shown below (1950=100). The CIA indexes agree quite well with those based on Soviet data on per capita consumption. Knitwear Hosiery Leather Footwear ABC A B C A B C 1960 314 274 443 224 204 358 206 206 315 1975 758 809 2,275 331 316 1,235 411 364 901 A�Index derived from Soviet per capita consumption data in physical units, including imports. B�CIA index. C�Indexes derived from official deflated retail sales. But both indexes grow much less rapidly than those based on officially deflated retail sales. No doubt, the physically based measures understate the real growth of consumption of these items because they do not take account of improvements in quality and product assortment. On the other hand, deflated retail sales indexes surely overstate real growth, since the price deflators are known to have a downward bias. There is no way to determine the degree of bias independently because there are no suitable price data. The index for clothing (sewn garments) with a third of the soft goods weight is based on official Soviet data on the value of production in so-called constant (1967) prices. It, too, increases much more slowly than the value of officially deflated retail sales: the respective indexes for 1975 (1950=100) are 608 and 1048. Both indexes, as well as the others discussed above, overstate real growth of consumption to some extent because they do not take into account the shift from home production to factory manufacture. Although both deflated value indexes (production and retail sales) are believed to have unreliable deflators, that for retail sales is considered the least accurate. The comments about the reliability of official retail price indexes apply also to the 6 sub-indexes that are based on deflated retail sales. There are .no alternative data to use in estimating consumption of these items. Because of the familiar faults of official price indexes, the indexes probably have an upward bias. One can hope, but not be certain that the various biases more or less cancel out. However, the composite index of consump- tion derived here clearly is preferable to a measure that relies entirely on official values and price deflators. The CIA indexes for clothing and related items, based on production, do not allow for imports, which come mainly from CEMA countries. Although imports rose rapidly during the 1950s, they were miniscule relative to the value of retail sales. During the 1960s, imports in current prices increased at about the same rate as the value of production in constant prices. Although imports in current prices increased faster than real production in the 1970s, prices of imports evidently increased rapidly also. From this evidence, it appears that the CIA index for clothing is not seriously biased downward by failure to allow for imports. Exports of clothing have been negligible throughout the period. Weights. The derivation of the 1970 expenditure ' weights for the soft goods index is shown in Table 9. Essentially, the task was to disaggregate the principal expenditure categories�retail sales for consumption and military subsistence. The allocation of retail sales to sub-groups can be made with confidence from published retail sales data and assumptions about the distribution of sales to enterprises and institutions. The distribution of the military clothing ration is tenuous but is probably not grossly wrong. Because their content is unknown, purchases of soft goods in collective farm markets, a small sum, were not distributed. The value of consumption in kind of wool was obtained by the methodology used to derive the total of such consumption and is thought to be reasonably reliable; the wool was assumed to be used to produce various items of knitted clothing. Indexes. The data underlying all sub-indexes are given in Appendix C. Six sub-indexes are based on physical production data available in Promyshlennost' SSSR 1964 and in annual Narkhozy. They include: knitted outerwear, knitted underwear, leather foot- wear, rubber footwear, felt footwear, and hosiery. The series for leather footwear was adjusted for net trade and inventory change needed because of rapidly rising imports. These adjustments could not be made for the other categories; imports are known to be 340 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Table 9 Derivations of 1970 Weights for Components of the Index of Soft Goods Retail Sales for Consumption a (Billion Rubles) Military Subsistence b (Billion Rubles) Consumption in Kind' (Billion Rubles) Total Consumption (Billion Rubles) Percent Total 40.370 1.199 .112 41.681 100.0 Cotton fabrics 1.360 1.360 3.3 Wool fabrics 1.003 1.003 2.4 Silk fabrics 1.141 1.141 2.7 Linen fabrics .246 .246 .6 Clothing 13.022 d .932 13.954 33.6 Knit underwear 2.603 .043 2.646 6.3 Knit outerwear 4.127 .071 .112 4.310 10.3 Hosiery 1.691 .020 1.711 4.1 Leather footwear 6.210 .123 6.333 15.2 Rubber footwear .865 .865 2.1 Felt footwear .214 .214 .5 Household soaps and detergents .651 .651 1.6 Toilet soap and cosmetics 1.140 1:140 2.7 Haberdashery and thread 3.623 .010 3.633 8.7 School and office supplies .834 .834 2.0 Publications 1.640 1.640 3.9 a Total retail sales, less institutional purchases, services and commis- sion sales. Retail sales are given in Narkhoz 1972, pp. 584-85. Institutional purchases were distributed on the basis of the shares in last half I968-first half 1969 shown in Vest stat, No. 5, 1971, p. 37. Services were allocated on the basis of data in Narkhoz 1972, p.621. Cloth used in repair and tailoring of clothing and knitwear was allocated to fabrics in accordance with their respective shares in retail trade. Laundry and dry cleaning services were allocated to clothing. b Military subsistence was distributed among groups on the basis of information concerning the basic clothing ration and its cost by item. Wool. d Excluding fur and fur products. negligible for other footwear. One indexclothing- is based on official data on the value of production in constant rubles; the data are given in the above-noted sources. Few interpolations had to be made. Fight indexes are based on deflated retail sales: fabrics (cotton, wool, silk, linen), haberdashery, school and office supplies, household soap and detergents, and toilet soap and cosmetics. Retail sales in current prices are available for nearly all years in the annual Narkhozy (e.g., Narkhoz 1972, pp. 584-585) as are specific indexes of state retail prices (e.g. Narkhoz 1972, p. 603). Price indexes for linen cloth, household soap and detergents, and toilet soap and cosmetics were derived from current values and published index- es of the value of sales in constant prices (e.g., Narkhoz 1972, p. 555). The index for publications is based on retail sales in current prices until 1977; no important price changes are known to have been made for these goods until then, the prices of which are kept low as a matter of social policy. Durables and Miscellaneous Goods Scope and Coverage. The index implicitly covers all goods purchased in state and cooperative retail out- lets, except those covered by the indexes for "food, beverages and tobacco" and for "soft goods." The 341 93-892 0 - 82 - 23 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 index includes furniture, household appliances, radios and TV sets, passenger cars, sports equipment, toys, musical instruments, dishwares, motorcycles and bi- cycles, watches and jewelry, and a variety of odds and ends not specifically identified in the published data on retail sales. The statistics are not detailed enough to permit an accurate matching of the US classifica- tion of goods into consumer durables and consumer nondurables. Nonetheless, the classification used here for the USSR�durables and miscellaneous goods� consists mainly (at least four-fifths) of items classified as durable goods in US national accounts. The index for durables and miscellaneous goods is based on a deflation of total retail sales of such goods; it is not a sample index. Unfortunately, the coverage of the index is not identical with that of the 1970 value weight, which is used to move the index, but this discrepancy is not thought to be serious. With the detail available, it is not possible to provide an exact match. The coverage of the weight and the index overlap by at least 80 percent. The items implicitly covered by the index, but not by the weight, are repair services for autos and household durables, building materials, a variety of goods of unknown composition included in a residual category in Soviet retail sales data, and retail purchases made by state enterprises and organizations. The index based on the deflation of total retail sales of durables and miscellaneous goods employs current price values and an implicit official retail price index as a deflator. Despite the reservations already noted about the reliability of official retail price indexes, no better approach to constructing the index could be devised, given the paucity of data available. The deflated sales approach replaced a method based on a sample of nine product groups, some measured by production or sales in physical units and some based on retail sales. This sample, severely limited by the availability of Soviet data, was seriously unrepresen- tative. It was dominated by a group of goods� furniture, household appliances, radio and TV sets and automobiles�that increased very rapidly from very low levels; these rapidly growing items made up over two-thirds of the weight. Analysis of retail sales data showed that the rest of the goods covered by the weight were increasing much less rapidly. The unre- liability of the sample index also was indicated by the fact that its rate of growth was far higher than an official production series in constant rubles labeled "Proizvodstvo tovarov kul'turno-bytovogo naznachen- iya i khozyaystvennogo ob'ikhoda," (cultural and household goods�hereafter referred to as tovary), which evidently includes most of the goods involved. This value series itself is probably biased upward, because of unreliable price deflators. Lack of data precluded expansion of the sample to make it more representative. The present index based on deflated retail sales, unlike physical value and production based indexes, incorporates imported goods and reflects changes in product mix and quality. On the other hand, it is probably biased upward, because of the flaws in official price indexes. Disguised price inflation may be serious for durable goods, but there is no way to estimate the degree of bias. The index can be com- pared with two other measures with similar (though not identical) coverage. One is the official Soviet series for the production of household durables and related items mentioned above. The series in constant rubles (tovary) is believed to include automobiles and to be distorted by changing coverage." The other index is a composite of the CIA indexes for produc- tion of consumer durables and furniture, weighted by estimated value of retail sales for the two components in 1970. These indexes, components of the CIA index of Soviet industrial production, include passenger cars " The coverage of the tovary series is not entirely clear. The Narkhozy regularly provide data, mainly in physical units, for a list of the "basic" kinds of goods included. Clearly, it includes household appliances, radio and TV sets, musical instruments, motorcycles and bicycles, furniture, household chemicals, dishware and many other products. A key question is whether it includes passenger cars. Although not absolutely certain, the weight of the evidence suggests that it does. It is also probable that the coverage of the series has been expanding. Both conclusions are supported by a lengthy discussion of the tovary complex of goods in R. A. Lokshin, Spros, proizvodstvo torgovlya, Moscow, 1975, pp. 185-216. Other evidence for the belief that automobiles are included is provided by comparisons of growth rates for production of tovary during 1971-75 with (1) growth rates for all components listed as included (Narkhoz 1975, pp. 294-295) and (2) growth rates for retail sales in constant prices of all identified components for which such series are available. Among the production series, all those with large weights increased much less rapidly than tovary as a Whole. A similar situation prevailed for the retail trade series. Finally, retail sales of identified tovary (less furniture) in current prices rose by 44 percent during 1971-75, residual retail sales of non-food goods, which include cars, increased by 128 percent, and production of tovary (including furniture) increased 64.5 percent. From what is known about relative values of the various components, it is hard to account for such a fast growth rate unless cars were included. 342 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 and implicitly, all of the items included in the tovary series except household chemicals. A comparison of the three indexes is shown below (1950 = 100): Index of Consump- tion of Durables and Miscellaneous Goods 1960 449 408 428 1970 979 1,055 1,269 1975 1,660 1,773 2,018 Weighted by estimated retail sales of durables (78.4 percent) and of furniture (21.6 percent) Although the index of consumption grew more slowly than the production-based indexes, the rates of growth shown by the three indexes are not greatly different. A number of factors may account for the differences: (1) differences in coverage, (2) probable price inflation in the tovary series, (3) the fact that the CIA production index reflects the tovary series in part, (4) the production-based series include exports and some non- consumption usage, while the consumption index reflects imports, (5) the production-based series allow for inventory accumulations. Weights. The 1970 weight represents the value of relevant categories of goods identified in Soviet retail sales data plus a share of the residual of unidentified sales, less repair and other applicable services, commis- sion sales, and purchases by state enterprises and organizations. The details are described in Appendix D of J EC, GNP, 1950-80. The category weight is judged to be quite reliable. Index. The index for durables and miscellaneous goods is derived from three sets of regularly published data: (I) value of retail sales by major product category in current prices, found, for example, in Narkhoz 1975, pp. 626-627; (2) indexes of prices in state and cooperat- ive retail trade by majot product group (found, for example in Narkhoz 1975, pp. 645), and (3) for a few categories, indexes of the growth of retail sales in constant prices (found, for example, in Narkhoz 1975, p. 590). From these data it is possible to obtain a series of ruble values of total retail sales of non-food goods in constant 1970 rubles and likewise a series of similar values for tobacco and for 17 categories of soft goods that are included in our indexes for food beverages, and tobacco and for soft goods. The sum of these 18 values for each year was then subtracted from the total value of non-food goods in that year to obtain the residual value in constant 1970 rubles. The residual consists almost entirely of durables and miscellaneous related goods. The procedure, in effect, derives the price deflator for this group of goods that is implicit in the values and indexes in current and constant values published by the Soviet government. This outcome is CIA Index of Index of made possible by the fact that the official indexes of re- Production of Tovary Consumer tail prices are linked indexes employing given year Durables weights (S. G. Stolyarov, 0 tsenakh i tsenoobrazovand and Furniture v S'SSR, Moscow, 1969, p. 103). The values underlying the index of durables and miscellaneous goods are shown in Appendix D. Services The index of services is a weighted average of an index of household services and an index of communal services. The weights are those for 1970 used in GNP by end use. Household Services The index for household services is a weighted aggre- gate of six sub-indexes for major types of services� housing, utilities, transportation, communications, re- pair and personal care, and recreation. The indexes as a group cover all of the major household services; any services omitted would be insignificant in terms of consumer expenditures. The Soviet Union lacks most of the financial and related services that are impor- tant in Western countries. Although some, such as legal services, do exist, there are no data concerning them. The 1970 expenditure weights used to aggre- gate the 6 sub-indexes are those used in GNP by end use; they are described in detail in CIA, GNP 1970 and in JEC, GNP, 1950-80, Appendix D. The data underlying each of the sub-indexes are given in Appendix E. Housing. Scope and Coverage. The index measures the flow of housing services in real terms by the change in the total stock of living space available expressed in square meters. The stock includes all housing, public and private,,urban and rural. About 80 percent of rural housing and 25 percent of all urban housing is privately owned. State housing con- sists mainly of multi-family buildings, where small apartments are rented at heavily subsidized rates. The basic rates have not been changed since they were set in the 1920s. In the US national accounts, housing services as a component of personal consumption are measured by expenditures in current prices, deflated by an index for rents that is a component of the Bureau of Labor Statistics, Consumer Price Index. Value data are not available for the Soviet Union. 343 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Presumably, an index based on housing space alone understates the real gains by failing to capture quali- tative improvements. However, there is little evidence to show that the physical quality of housing construc- tion per se in the USSR has improved much over the years. Although the average size of a dwelling unit increased between 1950 and 1978�by 17 percent for public housing and 77 percent for private housing (Narkhoz 1970, p. 541; Narkhoz 1978, pp. 393, 395), urban housing remains crowded. The number of new dwelling units built, however, has failed to keep up with the number of new families formed. As a consequence, many families and single persons must share living quarters. Morton has estimated that in 1970 there were 1.23 households per dwelling unit, a rough measure of the extent of overcrowding." Also, urban families often must share kitchens and baths with other families�some 30 percent do, according to a recent Soviet source.' While state urban housing has been increasingly provided with amenities� baths, hot water, plumbing and electricity�most rural housing and probably some private urban hous- ing still lack all of them except electricity. Most of this aspect of improvement in housing conditions is captured in the index for utilities. The diverse considerations discussed suggest that no adjustment to the housing index needs to be made for quality change. Probably the largest element in im- provement of housing conditions for the individual under Soviet conditions is simply more space, which the index measures when expressed per capita. Weights. The weight for housing is the sum of (1) cash rents paid by tenants in urban public housing, (2) im- puted rents at the state urban public rate per square meter for owner-occupied urban private and all rural housing, and (3) expenditures by tenants and owners for current repair of housing. The derivation of the weight is described in CIA, GNP 1970, p. 41. The average state rental rate was obtained from a Soviet source: use of that rate for imputation to owner- occupied housing was considered appropriate. Al- though the average quality of private housing con- struction is perhaps lower than for state housing, the average new privately built unit has been appreciably larger than the average state unit since 1960. More- over, the state rental rate covers only about one third of total maintenance costs. " JEC, 1979, p. 797. " A. Andreev, Housing, Moscow, Novosti Press, 1976, pp. 14-15. Index. The index used to measure housing services is an index of total living space, computed as the sum of separate estimates for midyear stocks of urban and rural housing, respectively. The estimates are based on data regularly published in annual statistical hand- books (e.g., Narkhoz 1977, p. 415). Although urban stocks are reported directly, rural stocks are not. They can be estimated quite satisfactorily, however, from a Soviet estimate of the stock in 1959, relevant official data bearing on changes in the stock via new con- struction and transfers to urban stocks, and an as- sumption about retirement rates. The sources and methodology for deriving the total stocks are de- scribed in detail in Willard S. Smith, "Housing in the Soviet Union: Big Plans, Little Action," in JEC, 1973, pp. 419-422. This source gives the estimates for 1950, 1955-71; estimates for 1951-54 were interpolated. Estimates for 1972-80 were obtained by the same methodology with data given in Narkhoz 1975, pp. 570, 576, 578, and for subsequent years in compara- ble tables in the respective annual Narkhozy. Utilities. Scope and Coverage. The sector comprises household public utilities� electricity, gas, and cen- tralized supply of heat and hot water, cold water and sewage disposal. The index, a composite of three series expressed in physical units, is designed to measure household outlays on these services in real terms. The sector is defined in the same way as the Soviet category "communal payments," (Metodiches- kiye ukazaniya, 1969, p. 535) except that outlays on hotels and dormitories, included there, are classified in recreation and in housing in the GNP accounts. As defined here, the sector is essentially the same as the "household utilities" component of the sector "household operations" in US national accounts for personal consumption. The procedure in the US is to measure real consumption of utilities by deflating money expenditures by appropriate price indexes. Lack of data precludes this approach for the USSR However, the Soviets claim that basic utility charges have not changed in recent decades. The coverage of the utilities index is essentially complete. The 1970 weights for the three sub-indexes are based on data given in a Soviet source. Although the sub-indexes are based on physical series (kilowatt-hours of electricity, cubic meters of gas, square meters of state urban public housing stock), they are considered suitable as measures of real consumption trends. Quality changes are not important in this sector. The change in the urban public housing stock was selected to move the expenditure weight for centralized heat, water and 344 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 sewage disposal because separate physical indicators are not available and because the bulk of such services are provided to state-owned housing. Although the share of housing units provided with such amenities evidently has been rising, the data are insufficient to allow for this factor. Weights. The expenditure weights for the three sub- indexes� electricity, gas, and other utilities�repre- sent their respective shares in total household outlays in 1970 and were derived from a table given in Ekonomicheskie nauki, no. 11, 1973, p. 44. The percentage shares are, respectively, 45.1, 9.1 and 45.8. The share allocated to "other utilities" is the sum of the source's categories "water pipes and sewer sys- tems," "heating" and "hot water supply." The latter two, with over four-fifths of the category weight, are supplied as joint products. Index. The index for utilities is a weighted composite of three separate indexes�electricity, gas, and other utilities (heat, water, sewage disposal). Electricity. The index reflects the consumption of electricity by all households, rural and urban, mea- sured in kilowatt-hours. Consistent data are available for only 3 years-1960, 1970 and 1975. Consumption in 1960 is estimated at 17.358 billion kilowatt-hours on the basis of the statement that household use of electricity amounted to 81 kilowatt-hours per person (Energetika SSSR v 1971-75 godakh, Moscow, 1972, p. 61) and a mid-year population of 214.3 million. Consumption in 1970 is given at 41.2 billion kilowatt- hours (Ibid., p. 63). Consumption in 1975 is given as 56.6 billion kilowatt-hours (Energetika SSSR v 1967- 1980 godakh, Moscow, 1977, p. 47). Total household consumption is estimated at 9.251 billion kilowatt- hours in 1950 based on some information with respect to urban use and rural use. Urban household con- sumption in 1950 is reported at 9.412 billion kilowatt- hours (P. S. Neporozhniy (ed.), Elektrifikatsiya SSSR, Moscow, 1970, p. 522). This figure evidently includes electricity used for street lighting, which was estimated at 481 million kilowatt-hours on the basis of the share of street lighting in 1958 (I. T. Novikov, Energetika SSSR, Moscow, 1961, p. 377) and the assumption that the share was the same in 1950. Total use of electricity by rural households in 1950 was estimated at 320 million kilowatt-hours on the basis of some information for 1953. Total consump- tion for all uses by agriculture is reported at 1.538 billion kilowatt-hours in 1950 (Sel'khoz /97/, p. 402). Consumption for nonproductive uses for 1953 can be estimated at 27.7 percent of total consumption in 1953 from data in Serkhoz 1960, pp. 428, 432, 436. This share was assumed to apply to 1950, and the further assumption was made that household use accounts for 75 percent of the total. The Soviets report that 10 percent of collective farm households (2.050 million) had electricity in 1950 (Serkhoz 1971, p. 402). Comparable figures are not available for state farms, but the share probably was higher; they em- ployed 2.425 million workers in 1950. Since commu- nal facilities were scarce in rural areas, household use probably constituted most of the non-productive use of electricity. Estimates for all other years were derived by interpo- lation on the basis of average annual rates of growth. Household consumption in 1976 and thereafter was estimated on the assumption that its share of total production of electricity, regularly reported in Nark- hoz, was the same as in 1975 (5.45 percent). Gas. The index measures gas consumed by households in billion cubic meters. Data on actual consumption are available for 1966-76 (Ekonornika gazovoy pro- m_vshlennosti, No. 2, 1978, p. 7) and for 1960 (Gazo- vaya promyshlennost', No. 4, 1970, p. 55). Consump- tion in all other years was estimated on the assumption that the household share ws 3.75 percent of total production of natural gas in each year. In 1960, the share was 3.97 percent (Ibid.). During 1967- 76, its share fluctuated between 3.49 percent and 4.15 percent; its share was 3.89 percent in 1976. Data on production of natural gas are given as follows: 1950- 62--Prom, 1964, p. 213; 1963�Narkhoz /969, p. 198; 1970-76 Narkhoz za 60 let, p. 205 and in similar tables in Narkhozy for subsequent years. Other Utilities. The measure for this category is an index of the midyear urban public housing stock expressed in m2. Mid-year stocks were calculated from data on end-of-year stocks given as follows: 1950�Narkhoz 1922-1972, p. 367; 1952, 1958-62� Narkhoz 1962, p. 499; 1963-64 Narkhoz 1964, p. 610; 1965-68 Narkhoz 1968, p. 580; 1969--Nark- hoz 1969, p. 568; 1970-75�Narkhoz 1975, p. 576; 1976 and following years similar tables in the re- spective annual Narkhozy. Stocks in 1951 and 1953- 57 were interpolated. 345 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Transportation. Scope and Coverage. The index of transportation is a measure of passenger transporta- tion services in real terms. It is a weighted composite of physical series for 9 modes of transport�rail, sea, river, bus, air, tram, trolleybus, subway, and taxi. The coverage of the index is complete." Both the weights and the physical series are based on officially pub- lished data, and little interpolation or estimation was required. The component indexes use quantitative indicators, mainly passenger kilometers and number of passengers. Quality change does not seem to be a serious problem in this sector although the basic equipment has been modernized over the years, thus probably making transportation physically more com- fortable. However, the degree of crowding likely has not been much reduced. In the US, transportation services as a component of personal consumption in the national accounts are measured by current expenditures deflated by BLS price indexes. Annual expenditure data are not avail- able for the USSR. According to Soviet statements, fares for the various types of passenger transport have not been changed for decades, except for air and taxi fares in the late 1970s. Weights. The weights used to aggregate the 9 sub- indexes are average revenue rates per passenger kilo- meter, per kilometer or per ride. The weights and their sources are as follows: Mode Average Rate Source (kopecks) Rail Sea 0.87 per pass. km. 7.46 per pass. mile Transport i svyoz', 1972, p. 111. Ibid., p. 151. River Bus Air 1.48 per pass. km. Ibid., p. 186. 1.31 per pass. km. Ibid., p. 241. 1.74 per pass. km. N.N. Belenkiy, Ekonomika passazhirskik1rperevozok, 1974, p. 241, with a 25 percent profit markup added. Tram 3.0 per ride N. B. Chestniy, Tardy na kom- munarnyye uslugi,1968, p. 19. Trolleybus 4.0 per ride Ibid. Subway 5.0 per ride A. G. Kreykin (ed.), Passazhirs- kiye tarify na transport SSSR, 1966, p.19 Taxi 11.50 per km. Transport i svyaz', 1972, pp. 247-54. " Although the index covers all passenger transportation both private and business�the 1970 expenditure weight excludes esti- mated business travel outlays. Thus, their share in total outlays is assumed to remain constant. Index. The nature and sources of data for the sub- indexes are summarized below: Mode Physical Measure Sources Rail, river, bus, air Passenger km Transport i svyaz', 1972, p. 19, and similar table in Narkhozy in subsequent years. Sea Passenger miles Transport i svyaz', 1972, p. 139 and similar tables in Narkhozy for subsequent years. Tram, trolley- Passengers bus, subway Transport i svyaz', 1972, pp. 256-57 and similar tables in Narkhozy for other years. Taxi Passenger km. Transport i svyaz',1957, pp. 256-57; Transport i svyaz', 1972, pp. 246-47; similar tables in Narkhozy for other years. Communications. Scope and Coverage. Soviet statisti- cal practice defines the sector to include the postal services, telephone system, telegraph system, radio and television broadcasting, and miscellaneous special services.' The index for the sector is a composite of four physical output series for the major forms of communications�postal, telegraph, telephone, and radio and television; the four series are aggregated with 1970 average revenue (implicit unit price) weights. The coverage of the index evidently is quite complete, only "miscellaneous services" being omit- ted. The sum of the revenues for the four types included in the index comprised 98 percent of the total reported revenue (Transport i svyaz', 1972, p. 302). The data used for revenue weights and indexes refer to total activity of the sector, i.e., services rendered to business firms and government, as well as to private persons. There are no data by type of customers; evidence that the household share has been relatively stable is provided by a comparison of household expenditures on communications in 1960, 1965, 1970 and 1972 " with the total value of output of communi- cations in those years." The household percentage shares are respectively: 38.5, 40.0, 33.3 and 34.2. " Metodicheskiye ukazaniya, 1974, pp. 755-756. " I.M. Schneiderman, Statistika uslug, 1974, p. 62. " Narkhoz 1972, p. 461. 346 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Weights. The weights for the four sub-indexes and for the components of the telephone indexes are the revenues for the various kinds of services provided by the Ministry of Communications (Transport i svyaz', 1972, p. 302). There are no data with which to obtain separate value weights for the individual components of the postal and radio-TV broadcasting sub-indexes. Index. The nature and sources of data for the four sub- indexes are shown below: Sector Nature of Series Sources Postal Sum of the number of letters, newspapers and magazines, par- cels, and money or- ders and pension pay- ments Transport i svyaz', 1972, p. 274 and similar tables in Nark- hozy for subse- quent years Telegraph Number of telegrams Ibid. Telephone Weighted sum of number of inter-ur- ban calls, urban sets, and rural sets Transport i svyaz', 1972, pp. 274, 283, 285 and similar tables in Narkhozy for subsequent years. Radio-TV broadcast- ing Sum of the number of radios, TV sets, and wired loudspeak- ers Transport i svyaz', 1972, p. 292 and similar tables in Nark- hozy for subse- quent years. Repair and Personal Care. Scope and Coverage. As defined here, the sector encompasses a wide variety of personal services, the most important of which are: repair and tailoring of clothing, repair of household appliances and automobiles; shoe repair; barbershops and beauty parlors; public baths; and photographic services. The coverage is nearly identical to that of the Soviet statistical category Bytovoye obsluzhivaniye naseleniya ("everyday servicing of the population"), except that the latter includes housing construction and repair, which is included in "housing" in the GNP accounts. In Soviet practice, these services are classi- fied partly as "productive" and partly as "non- productive," but statistics for both groups combined are now reported regularly in the annual handbooks. The coverage of the sector is described in Metodiches- kiye ukazaniya, 1974, pp. 774-776. In US national accounts these services are classified mainly in "personal services" and "miscellaneous repair services and hand trades." For the most part, the indexes used to measure expenditures in real terms are calculated as the deflated values of outlays in current prices. The index for "repair and personal care" is a weighted composite of separate indexes for state-supplied ser- vices and for privately supplied services. Both purport to represent the value of such services in constant 1970 prices. Although the coverage of the combined index is virtually complete, the underlying data leave much to be desired. The index for state services is based on published values reported for some years in current prices and for other years in various kinds of constant prices. To complete the time series, use was made of growth rates for the RSFSR and various assumptions for years for which no data could be found. The series for private services relies on survey data relative to the RSFSR in 1960-1971 and on assumptions about their growth in other years. The unsatisfactory state of the data is a result of the fact that state-supplied personal services were long neglected and that systematic data are not compiled on privately supplied services. Evalu- ation of the quality of the resulting index is difficult. It relies in part on official price deflators of an unknown character. The index, as a consequence may overstate the growth of state-supplied services. On the other hand, the assumptions (and the data) on trends in private services may understate their growth. Clearly, the total supply of services has been increasing rapidly as incomes have risen. The index reflects this expected result; the degree of accuracy is hard to assess. Weights. Separate values for state and privately sup- plied services were derived for the 1970 GNP weights. The value for state-supplied services was obtained as shown below: The value of private services is estimat- ed in CIA, GNP 1970, p. 42, except that housing repair services are now estimated at 1.071 billion rubles. (See tabulation on next page.) Indexes. State-supplied services. The construction of this sub-index entailed a series of linkages based on diverse data. 1. The procedure described on the following page to obtain the value for 1970 was used to obtain similar values in current prices for 1960 and 1965-1972 and in comparable prices for 1965 and 1970-76. The values of sales to enterprises were estimated from the shares given in Dmitriev, op. cit., p. 98 for 1965, 1970, and 1972. Their share in 1965 was used for all preceding years. Extrapolation for 1973-76 was made on the basis of the average annual rates of growth of their 347 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 State-Supplied Services, 1970 Total services Million Rubles 4,044.4 a Less sales to enterprises 307.4 b Less 95 percent of the housing services sold to enterprises 375.0 b Plus 96 percent of the materials used in tailoring of clothing 1,003.1 c Plus 96 percent of the materials used in tailoring of knitwear 115.4 c Equals consumer purchases of services Narkhoz 1972, p.621. b Estimated on the basis of percentage data given for the RSFSR in V. I. Dmitriev, Metodologicheskiye osnovy prognozirovaniya sprosa na bytovyye uslugi, 1975, p.98 and ruble values in Narkhoz RSFSR 1972, pp. 401-402. c Materials are assumed to constitute half of total sales approximate- ly the ratio for earlier years shown by data in Narkhoz 1968, p. 664 and Narkhoz 1969, p. 660. Enterprise sales are calculated at 4 percent of enterprise purchases of tailoring services, the share that can be derived from Dmitriev's data. 4,480.7 share during 1966-72, using data on total sales given in Narkhoz 1972, p. 621 and similar tables in Narhozy for subsequent years. The share was assumed to remain unchanged after 1976. The share estimated for that year (16.9 percent) accords well with a Soviet statement that the share was almost 18 percent in 1975." Because of a change in the way data were reported, use of this procedure for years after 1976 necessitated adding materials used in repair of dura- bles and of housing to the published totals; these were estimated to be half of the totals, their shares in 1975- 76. 2. These values in current and constant prices are used to splice together an index in constant prices for 1966- , 80. 3. The index for 1960-65 is based on constant price values given in L.A. Bobrov, N.V. Gukov, and K.S. Gulevich, Ekonomika bytovogo obsluzhivaniya nase- leniya, 1971, p. 27. 4. Data in current prices for the RSFSR, cited in Ibid., p. 24 for 1958-62 were used to obtain an index for 1958-60. For 1956-58 the annual growth rate is based on constant price data for the RSFSR, given in L.A. Bobrov, Ekonomicheskiye problemy bytovogo obsluz- hivaniya naseleniya, 1978, p. 58. An annual growth of 10 percent was assumed for 1950-55, the rate reported for 1950-54 in Bobrov, et al, 1971, p. 23. "NV. Gukov, Ekonomika, organizatsiya i planirovaniye mater- ial'no-tekhnicheskogo snabzheniya predpriyatiy bytovogo obsluzhi- vaniya, Moscow, 1977, p. 14. Privately-supplied services. The growth rates of these services during 1959-1970 are based on data for the RSFSR given in V.I. Dmitriev, op. cit., p. 45. For 1950-58, the 1959 value was assumed. The level in 1970 was assumed the same in all following years, on the reasoning that the fast growing supplies of state services would tend to crowd out private services, given the generally hostile official attitude toward them, even though money incomes continued to rise rapidly. There are no other data on the trend in the supply of these services. Recreation. Scope and Coverage. As defined here, the sector encompasses activities providing entertainment and recreation services to the population that are largely paid for out of household incomes. Conceptu- ally, the sector includes both public and private purveyors of entertainment and recreational services, such as movies, theater, ballet, concerts, circuses, sports, vacation resorts, and lodging facilities. There is no direct counterpart of this sector in the Soviet classification of economic activities; rather, the sector encompasses "art", a component of the category "culture and art;" "sanitoria and resorts" and "sports and physical culture organizations," both components of "health and physical culture"; and "hotels," a component of "housing-communal economy and ev- eryday services." (See Metodicheskiye ukazaniya, 1974, pp. 762, 764, 767.) The categories in US national accounts that would be encompassed in "Recreation" are: motion pictures, amusements and recreational services n.e.c., and hotels and other lodg- ing places. The index used to measure the activity of the sector is a weighted aggregate of three sub-indexes: "entertain- ment," "resorts" and "leisure." The first reflects the activities of movies, theaters, sports, and other enter- tainment enterprises. The second represents the ac- tivities of vacation resorts, which are publicly operat- ed and heavily subsidized in the USSR. The third is intended to represent recreation in the form of travel, not yet common in the USSR. Available data do not permit satisfactory measurement of these diverse ac- tivities. Neither expenditure data nor price deflators are available for developing the deflated expenditure series that are employed to measure comparable activities in US national accounts. As a substitute, several physical series were selected to represent the various types of activities and aggregated with 1970 348 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 expenditure weights. Despite reservations concerning both the sub-indexes and weights, the composite index probably reflects real outlays on recreation reasonably well. Its relatively slow growth is consistent with the traditional reluctance of the Soviet government to invest in the provision of recreational facilities and with the impact of rapidly growing availability of television on attendance at movies and similar activities. Weights. The derivation of the 1970 expenditure weights for the three sub-indexes is explained in CIA, GNP 1970, p. 42. Indexes. Entertainment. The index is based on the sum of the numbers of paid admissions to movies and admissions to theaters. These are the only series of data on entertainment that are regularly published. The data are to be found in two tables regularly published in annual handbooks, e.g., Narkhoz 1972, p. 669. Vacation resorts. The index is based on the number of persons staying at "sanatoria, resort polyclinics, rest homes and pensions" in each year; the series excludes visitors to "rest bases" and "tourist bases," which are essentially campgrounds and shelters. There are no other data available to reflect such forms of recrea- -tion. Data for 1950, 1958, 1960-80 are given in tables regularly published in Narkhozy, e.g. Narkhoz 1972, p. 569. Growth rates for other years are interpolated. Leisure. The index is based on manhour employment in hotels. There are no other data available on this form of travel and recreation, which is greatly under- developed in the Soviet Union. Employment in hotels was estimated for 1950-69 in Stephen Rapawy, Com- parison of US and USSR Civilian Employment in Government, 1950-1969, US Bureau of the Census, International Population Reports, P-95, No. 69, April 1972, p. 17. Estimates for subsequent years are based on the assumption that employment in hotels in- creased at the same rate as employment in the housing-communal economy, regularly reported in Narkhoz, e.g., Narkhoz 1977, p. 378. The annual number of manhours worked in hotels is assumed to be the same as that in housing-communal economy. Manhours for 1950-74 are estimated in Stephen Rapawy, Estimates and Projections of Civilian Em- ployment in the USSR, 1950-1990, US Bureau of the Census, Foreign Economic Report No. 10, September 1976, p. 60, and extended to 1980 by him. Communal Services The index of communal services is a weighted aggre- gate of separate indexes for education and for health. The coverage of these services, nearly all state-pro- vided, is virtually complete. The 1970 weights used to combine the indexes are total current expenditures on these services by the population and by the govern- ment. The data underlying the two sub-indexes are shown in Appendix F. Education. Scope and Coverage. The definition of the sector follows Soviet statistical practice and includes (1) kindergartens and all types of general education schools concerned with the education and rearing of children, (2) trade schools (vocational-technical schools), and (3) higher and secondary specialized educational institutions of all kinds (Metodicheskiye ukazaniya, 1974, pp. 755-56). The coverage coincides, mostly, with "private education and research," a component of personal consumption expenditures in the US national accounts, plus government expendi- tures on education. Expenditures on nursery schools and on public libraries in the US are included in education; in the USSR, the former are included in "health" and the latter in "culture." The index of education services is a weighted compos- ite of two sub-indexes personnel services and other current purchases, mainly food, utilities and supplies. The index for personnel is a measure of manhour employment and is used to move wage expenditures in 1970. The result is equivalent to the procedure used by Bergson and Becker and also to that in the US, where total wage expenditures are deflated by an index of average wages. The index for other expendi- tures is a deflated value series, as are similar indexes constructed by Bergson for the USSR for 1928-55 and by the Department of Commerce for the US. Use of manhours as a measure of personnel services makes no allowance either for productivity change or for improvement in the quality of education in general that may have resulted from changing skill mixes and an upgrading of the level of qualification of teaching staffs. Because a suitable measure of productivity in education has yet to be devised and agreed upon, the practice in the US and elsewhere is to measure education services in real terms on the basis of inputs, as is done here for the USSR. In its measure, the US does make some allowance for changes in the quality , of labor inputs (skill mixes). The data required for an - adjustment for rising qualifications and changes in skill mixes are not available for the USSR. 349 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Weights. The weights used to combine the sub- indexes for personnel services and other current ex- penditures are their respective shares in 1970 of total expenditures on education, excluding investment and student stipends. Their derivation, revised from that used in CIA, GNP 1970, is explained in Appendix D of JEC, GNP, 1950-80. Indexes. Personnel services. The index of total man- hours worked in education was obtained as follows: a. Estimates of manhour employment in "education and culture" combined during 1950-74 are presented and the derivation described by Stephen Rapawy, Foreign Economic Report No. 10 (loc. cit.), pp. 50-51 and extended to 1980 by him. b. Estimates of total manhours worked in education alone were obtained by subtracting estimated man- hours in culture from manhours in education and culture combined. Estimates of manhours in culture were obtained by multiplying employment in culture in each year by the number of manhours worked per person. c. Average annual employment in culture is given for 1940, 1965, 1970-75 in Narkhoz 1975, p. 533, for 1966 in Trud v SSSR, 1968, p. 27 and for 1976-80 in Narkhoz 1980, p. 358. Employment in culture in 1965 and 1966 was 8.4 percent of total employment in education and culture; its share was about the same in 1940. Accordingly, employment in culture in 1950-64 was calculated by assuming that its share was 8.4 percent in each year. Estimates for 1967-69 were interpolated. Employment in education is obtained by subtraction for those years in which it is not reported directly. d. Average annual man-hours worked in culture are estimated by a procedure similar to that used by Rapawy (loc. cit). The procedure assumes that hours worked annually per person employed in culture follows the trend derived for industry. The level of annual manhours in culture was calculated by apply- ing to the level for industry in each year the ratio of the scheduled workweek in culture (38.6) to that in industry (40.7), as reported in Vest stat, No. 4, 1978, pp. 94-95. Other current purchases. The index is based on esti- mates of these purchases in current prices, deflated by a price index. (a) Other current purchases in current prices Total purchases in each year are based on estimates made separately for kindergartens, general education schools (including children's homes and boarding schools), higher education (vuzy),and secondary spe- cialized educational institutions (tekhnikums). Expen- ditures for these types of schools make up over 80 percent of total outlays on education. Data for other schools (mainly trade schools, correspondence schools and the like) are not available. The procedure used to estimate other current pur- chases for each type of school was as follows: (1) using the distribution of expenditures in the budget of the union-republics, investment expenditures were first deducted from total expenditures to obtain a series for total non-investment outlays. From this value for each year was then deducted the sum of wages and social insurance, stipends, capital repair, and purchases of equipment. The result is a series of values for other current purchases financed from the budgets of the republics. (2) The values obtained in step (1) were expressed as percentages of total non-investment outlays from re- public budgets. To obtain the values for other current purchases for the USSR as a whole, these percentage shares were multiplied by total non-investment out- lays reported pr calculated for the USSR The proce- dure assumes that the distribution of expenditures for each type of school in the total state budget is the same as that in the sum of republic budgets. The latter accounted for roughly 85 percent of the total in 1975. The distributions of expenditures in both types of budgets were similar in 1950-57, the only years when distributions pertaining to the total budget for the USSR are available. (3) Distribution of expenditures from union-republics budgets by type of school, as well as total expendi- tures for the USSR, are available for the years 1950- 57 and 1960-75 in the following sources: Raskhody po sotsiarno-kulturnyye meropriyatiya po gosudarst- vennomu byudzhetu SSSR, Moscow, 1958, (hereafter. referred to as Raskhody), pp. 11, 12, 38, 49-58, 95, 97. Gosbyudzhet 1966, pp. 23-24, 79, 82, 85-87, 89. Gosbyudzhet 1972, pp. 27-28, 85, 87, 91-94. Gos- byudzhet 1976, pp. 25-26, 82, 85, 88-91. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 In making the calculations, allowance was made for a change in classification in the 1960s. Parental fees were added to total budget expenditures for kindergartens. (4) For the years 1976-80, data on total non-invest- ment expenditures by major kind of school are given in Narkhoz 1980, p. 525. The percentage shares obtained for 1975 in step (1) were used to calculate values of total current purchases for those years. (b) Price index Other current purchases by educational institutions encompass a wide variety of items. The largest cate- gory is food (estimated from budget data at 47 percent of the total in 1970). Other sizeable items are services and miscellaneous outlays (25 percent), bedding and uniforms (9 percent), and numerous items related to utilities, office supplies, and housekeeping expenses (15 percent). No satisfactory price index exists or can be devised to deflate this mix of expenditures. Official industrial wholesale price indexes are too highly ag- gregated for categories other than food, and in any event are of dubious reliability, as are also the official indexes of retail prices.' In the belief that some deflation procedure, however crude, is preferable to none, it was decided to adopt a deflator that is implicit when the CIA index of household consumption of purchased goods in constant prices is compared with an index of retail sales of such goods in current prices that can be calculated from official Soviet data. The justification for employing this "alternative" index is as follows: (1) the need for some kind of deflation is recognized; (2) the implicit index is largely indepen- dent of official price indexes; (3) from a comparison of data in Vest stat, No. 5, 1971, pp. 34, 36 with expenditure data in Gosbyudzhet 1972, p. 94 it is evident that schools, primarily kindergartens, pur- chase nearly all their food in retail outlets, as well as about one-third of all other material purchases.4' The implicit index�shown in Appendix F�declines by 13 percent during 1951-55 and riseNS by 40 percent during 1956-80; in contrast the implicit official price index (state and collective farm market prices com- bined) declines by 25 percent during 1951-55 and '" On this point, see Morris Bornstein in Treml and Hardt, 1972, pp. 355-395. '' Separation of expenditures between material purchases and services follows the approach used in M. R. Eidel'man Afezhotras- remains virtually unchanged thereafter. The interpre- tation and limitations of the "alternative" price index are discussed in JEC 1976, pp. 631, 651. A revised version of the index, along with a description of sources and methodology, is given in JEC, 1979, p. 766. Despite its limitations, the "alternative" index is believed to reflect price changes far more accurately than the official index. Moreover, even the "alterna- tive" index may be biased downward, because the CIA index itself incorporates several sub-indexes based on the value of retail sales in constant prices as measured by official price indexes. The sub-index for "durables and miscellaneous goods" is the most con- spicuous example. Health. Scope and Coverage. The sector is defined in Soviet statistical practice to include all activities concerned with public health�hospitals, clinics, sana- toria, vacation resorts, homes for the aged and dis- abled, and organizations concerned with social securi- ty and physical culture. In constructing the index of health services, expenditures on vacation resorts and sports activities are removed. The definition, then, corresponds, in the main, to the component "medical care and expenses" in the US national accounts for personal consumption expenditures plus government expenditures on health and hospitals and on medical vendor payments. The index for health services is a weighted average of sub-indexes for "personnel services" and for "other current purchases"�mainly food, medical supplies, utilities, and housekeeping and office expenses. The underlying data are given in Appendix F. The nature of the index is the same as that for "education", described above. The discussion there of the limita- tions of such an index applies also to the index for health. In constructing the weights for the index, expenditures on physical culture and vacation resorts were deducted; they are included in the sector "re- creation." Lack of detailed data prevented the re- moval of workers in physical culture from the employ- ment data underlying the indexes. However, their share in total employment is small (5.2 percent in 1966): they are not included in the published outlays for "health," and therefore are omitted from the index of other current purchases. Weights. The sub-indexes are weighted by estimated expenditures in 1970 on personnel services and on materials and the like. The weights, revised from those used in CIA, GNP 1970, are described in levoy balans obshchestvennogo produkta, Moscow, 1966, P. 165. , Appendix D of JEC, GNP, 1950-80. 351 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Indexes. Personnel services. The index for personnel services is based on total manhours worked in "health and physical culture." The manhour series for 1950- 1976 is presented and described in Stephen Rapawy, Foreign Economic Report No. 10, /oc. cit., p. 60, and extended to 1980 by him. It was not possible to remove manhours worked in sports organizations and vacation resorts from the series. There are no data with which to adjust the series either for changes in the educational quality of the labor force or for changes in the skill mix. However, the number of "middle medical personnel"�nurses, feldshers, medi- cal technicians and the like�has increased faster since 1950 then has the number of doctors. Average life expectancy at birth in the USSR did not change between 1960-61 and 1971-72, when the publication of such data was halted. Life expectancy probably has declined since then, because infant mortality rates and death rates for adult males have been rising since 1969." Other current purchases. The index of other current purchases is obtained by a procedure similar to that used for education. The derivation is as follows: (a) Other current purchases in current prices (1) Data on total non-investment outlays for health financed from union republic budgets are available for 1950-57 and 1960-75, with a distribution by type of expenditure. To obtain "other current purchases" in each year, the sum of outlays on wages and social insurance, equipment, and capital repair was deduct- ed from total non-investment outlays, and fees paid by parents were added. The values for "other current purchases" so obtained are then expressed as percent- ages of total non-investment outlays. (2) Almost four-fifths of total expenditures on health is financed from republic budgets. To obtain values for "other current purchases" for the USSR as a whole the percentages derived in step (1) were multi- plied by the values for total non-investment outlays financed from the state budget (union and republic budgets). This step assumes that the distribution of expenditures by object is the same in both types of budgets. The distributions were quite similar in 1950- 57, the only years when such data for both budgets are available. " Christopher Davis and Murray Feshbach, op. cit., pp. 1-8. (3) The data for steps (1) and (2) are found in the following sources for 1950-75: Raskhody, pp. 71-72, 76. Gosbyudzhet 1966, pp. 57, 90, 94. Gosbyudzhet 1972, pp. 62, 95, 99. Gosbyudzhet 1976, pp. 60, 92, 96. For years after 1975, data on total non-investment outlays for health financed from the state budget are given in the annual statistical handbooks, e.g., Nark- hoz 1978, p. 536. The percentage share of "other current purchases" in the total was assumed to remain at the 1975 level: the share changed little in 1966-75. A small amount of current expenditures for health care is known to be financed from sources other than the state budget (funds of enterprises and trade unions, mainly). There are no data with which to take such expenditures into account in constructing the indexes. (b) Price index "Other current purchases" by institutions classified in the health sector encompass a wide variety of items. The most important one is food, which in the expendi- tures in republic budgets made up an estimated 32 percent of the total in 1970; the remainder consisted of medicines (26 percent), bedding and uniforms (8 percent), services and miscellaneous outlays (22 per- cent), and a variety of items related to office and housekeeping expenses (12 percent). The price index used to deflate this mix of expenditures is the same as that used to deflate a similar group of outlays of educational institutions. The considerations leading to this choice are similar to those set forth above in the discussion of the price deflator for other current outlays in education. Like schools and kindergartens, hospitals, rest homes, and children's nurseries pur- chase a substantial part of their supplies at retail outlets, particularly food. According to data in Vest stat, No. 5, 1971, pp. 34, 36, compared with data in Gosbyudzhet 1972, pp. 95, 99, these organizations purchased nearly all of their food from retail outlets and a significant share of other purchases.. The description and sources for the price deflator are given above in the discussion of the index for education. 352 Approved for Release: 2019/07/19 C05210421 Appendix A 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV (.�..) cm L..) Table A-1 Indexes of Total Consumption in Established Prices, by Category, 1950-80, and 1970 Category Weights a 1950 1970 = 100 1970 Weights (Billion Rubles) 1970 Sub-index Weights (Percent) 1951 1952 1953 1954 1955 1956 1957 1958 1959 Consumption 211.083 33.8 34.6 37.1 40.2 43.0 45.9 48.2 51.8 55.4 57.7 Goods 166.478 33.1 33.7 36.5 40.0 42.9 45.8 48.4 52.4 56.2 58.3 Food 107.926 100.0 39.5 39.0 42.3 45.9 47.5 50.9 53.1 57.4 61.3 62.9 Animal products 42.310 38.9 39.6 40.6 42.9 45.0 46.4 50.3 55.3 62.7 65.5 Fish 3.0 33.7 39.9 39.3 40.7 45.6 49.3 50.7 52.2 54.2 55.2 Meat 19.8 40.2 39.4 41.4 44.7 46.9 47.1 51.4 55.8 63.9 68.6 Milk 8.9 46.6 46.1 44.5 44.3 45.3 45.2 48.9 56.1 66.5 65.4 Butter 1.2 17.4 15.0 17.1 18.6 39.5 46.7 52.9 57.6 64.4 66.1 Cheese 0.7 15.3 17.7 19.0 21.4 23.2 27.6 30.8 32.4 35.4 36.8 Eggs 3.6 28.0 32.2 35.1 39.5 42.4 45.9 48.6 55.8 57.9 62.3 Processed foods 13.857 26.0 34.4 38.2 45.9 37.6 46.5 50.7 52.4 54.9 57.5 Sugar 5.1 19.2 32.3 34.5 4,5.5 45.1 45.3 48.6 51.1 51.9 54.4 Vegetable oil 1.0 29.5 35.4 39.1 48.4 55.1 46.3 50.8 54.2 58.9 63.7 Margarine 0.6 25.9 30.1 37.0 45.2 52.4 53.3 54.6 57.7 56.8 57.5 Confectioneries 5.6 31.3 36.7 40.9 45.0 46.6 44.6 51.0 51.0 54.5 57.7 Macaroni 0.5 28.9 33.8 44.4 55.5 65.4 69.8 63.7 71.6 77.0 73.8 Basic foods 22.890 72.4 60.4 68.6 72.6 76.4 79.6 78.2 82.8 83.4 84.1 Potatoes 4.0 137.5 62.1 89.8 97.9 102.1 92.0 93.6 95.9 98.3 100.0 Vegetables 3.2 46.1 43.8 48.1 55.5 58.0 68.0 65.2 67.4 73.7 70.8 Fruit 4.1 23.3 25.1 27.0 28.8 33.5 38.4 32.4 55.5 54.0 55.6 Flour and groats 9.9 75.2 79.6 84.0 86.0 89.8 95.4 95.1 93.9 92.7 93.7 Beverages and tobacco 28.869 20.8 23.3 26.0 29.2 32.9 36.9 38.5 42.6 44.8 44.7 Alcohol and soft drinks 23.4 19.6 22.2 25.0 28.2 31.8 35.9 37.6 42.1 44.2 43.8 Tea 0.6 29.1 32.7 34.2 39.1 40.6 46.7 39.6 45.6 40.6 49.8 49.8 Tobacco 2.7 29.3 31.1 32.9 35.8 40.2 43.2 47.5 49.3 51.2 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-1 (continued) 1970 = 100 1970 Weights (Billion Rubles) 1970 Sub-index Weights (Percent) 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Soft goods 44.294 100.0 24.5 27.7 29.3 32.5 37.8 39.8 43.2 46.1 49.6 52.7 Cotton fabrics 3.3 91.7 95.5 99.4 120.0 144.9 134.8 135.6 123.2 117.4 124.7 Wool fabrics 2.4 56.2 50.0 44.5 53.6 64.6 49.9 66.1 84.0 91.6 92.5 Silk fabrics 2.7 19.7 24.1 29.4 40.2 55.0 56.3 69.0 86.0 88.6 85.0 Linen fabrics 0.6 32.4 30.4 28.6 26.8 28.7 30.7 41.7 54.2 60.6 61.9 Sewn goods 33.5 , 19.5 22.2 24.9 27.8 33.1 36.6 40.3 40.7 44.5 49.2 Hosiery 4.1 35.3 44.7 43.7 45.7 50.4 57.7 60.0 63.1 66.3 69.2 Leather shoes 15.2 29.0 35.0 33.9 33.2 . 35.6 37.8 41.4 46.1 51.8 55.6 Rubber footwear 2.1 64.0 67.0 70.1 73.3 76.6 80.1 83.8 87.1 92.0 96.8 Felt footwear 0.5 70.4 72.0 73.3 74.8 75.8 77.0 76.1 83.0 89.9 97.8 Knitwear � 16.7 . 14.1 18.1 20.4 22.7 26.5 28.9 29.0 31.0 33.1 33.2 Haberdashery 8.7 13.9 15.2 16.5 19.7 23.6 25.9 28.8 34.8 38.4 41.4 School supplies 2.0 13.5 15.1 17.0 20.1 23.9 24.7 27.6 30.3 32.7 35.3 Publications 3.9 19.3 20.2 21.2 23.1 25.1 28.4 31.9 35.4 39.1 43.6 Household soap 1.6 23.1 25.7 27.4 30.6 37.8 36.5 40.3 42.5 45.2 45.6 Toilet soap 2.7 13.4 15.0 16.7 21.7 28.2 31.3 32.7 37.8 40.6 43.1 Durables 14.258 10.8 12.6 14.4 18.8 24.1 26.3 28.8 34.8 38.3 41.8 Consumer services 44.605 36.6 37.8 39.3 41.0 43.4 46.1 47.6 49.5 52.3 55.5 Household services 21.612 31.6 33.0 34.5 36.0 38.1 40.8 42.1 44.1 47.3 51.5 Housing 3.429 100.0 48.1 49.4 50.7 52.1 53.6 55.4 57.3 59.8 63.0 66.7 Urban housing 54.9 33.6 35.0 36.4 38.4 40.9 43.5 46.1 49.2 53.2 57.6 Rural housing 45.1 65.8 67.0 68.2 68.8 69.2 69.8 71.0 72.8 74.9 77.8 Utilities 3.478 100.0 25.1 26.6 28.4 30.0 31.6 33.4 35.3 37.1 39.9 42.9 Electricity 45.1 22.5 24.5 26.9 29.0 30.9 33.2 35.4 36.6 38.7 40.9 Gas 9.1 22.9 23.2 23.2 33.5 33.8 34.6 36.1 39.4 14.2 17.9 Other utilities 45.8 32.0 33.3 34.8 36.3 37.8 39.3 40.9 43.1 46.1 49.9 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Transportation 5.400 100.0 13.6 15.1 16.6 18.6 20.8 24.0 25.7 29.4 32.8 36.0 Rail 19.8 33.2 37.1 40.5 44.6 48.6 53.3 53.7 57.8 59.7 61.9 Sea 1.1 78.1 79.0 78.2 93.1 91.2 92.9 87.1 88.9 86.0 88.0 River 1.4 49.7 53.4 55.3 60.8 64.5 65.7 63.7 70.0 73.4 76.2 Bus 45.7 2.6 3.2 4.1 5.2 7.0 10.3 13.0 16.6 21.0 25.1 Air 11.7 1.5 1.9 2.2 2.7 3.1 3.6 4.0 5.8 8.2 11.6 Tram 4.1 64.8 67.6 70.5 73.5 76.7 80.0 80.6 85.6 90.4 93.6 Trolleybus 4.2 15.4 17.6 20.1 23.0 26.4 30.3 34.0 39.1 43.6 45.8 Subway 2.0 27.4 29.7 32.2 34.9 37.7 40.8 43.4 44.2 46.5 47.6 Taxi 10.0 2.7 3.5 4.7 5.4 7.1 10.1 12.4 16.4 19.3 21.4 Communications 1.200 100.0 22.4 24.5 26.7 28.4 30.8 33.1 35.6 38.4 40.6 43.2 Postal 40.7 20.7 23.4 25.9 27.3 29.8 32.0 34.9 37.1 39.2 41.9 Telegraph 9.8 42.2 45.8 49.6 53.5 55.1 55.7 56.6 62.3 61.2 63.2 Telephone 36.8 23.2 24.4 26.1 27.2 28.8 30.8 32.5 34.5 37.0 39.0 Radio-TV 12.7 10.3 12.0 13.6 16.5 20.8 25.7 30.7 35.2 39.6 44.3 Repair and personal care 5.497 100.0 42.1 42.9 43.7 44.6 45.6 46.6 45.4 45.0 48.0 55.3 State services 83.1 8.9 9.8 10.8 11.8 13.0 14.3 12.9 12.4 16.0 24.8 Private services 16.9 202.5 202.5 202.5 202.5 202.5 202.5 202.5 202.5 202.5 202.5 Recreation 2.608 100.0 37.6 39.9 42.4 44.4 49.6 57.6 60.8 63.6 68.5 70.3 Entertainment 58.8 25.4 30.0 34.3 35.6 42.9 54.2 60.9 66.0 73.0 75.6 Resorts 17.6 36.9 38.3 40.5 42.4 44.4 48.0 47.9 49.2 54.9 57.0 Leisure 23.8 68.7 65.9 64.4 68.2 70.6 74.3 71.3 69.6 69.1 68.4 Goods and household services 188.090 32.9 33.6 36.2 39.6 42.3 45.3 47.7 51.5 55.3 57.6 Communal services 22.993 41.4 42.3 43.8 45.6 48.3 51.1 52.8 54.7 56.9 59.3 Education 14.380 100.0 42.8 43.8 45.1 46.3 48.3 50.3 51.8 53.1 54.7 56.4 Labor 71.3 47.2 48.8 50.4 51.7 54.0 56.2 57.0 58.1 59.5 60.8 Other current purchases 28.7 31.7 31.3 32.0 32.9 33.9 35.6 38.8 40.6 42.6 45.3 Health 8.613 100.0 39.0 39.8 41.7 44.5 48.5 52.5 54.5 57.4 60.6 64.1 Labor 63.1 44.0 45.8 47.6 49.3 52.7 56.0 57.6 60.2 63.4 66.4 Other current purchases 36.9 30.5 29.5 31.5 36.2 41.2 46.3 49.2 52.7 55.7 60.2 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Jl Table A-1 (continued) 1960 1961 1962 1963 1964 1965 1966 1967 1968 1970 = 100 1969 Consumption 60.9 62.7 65.5 68.2 69.8 74.0 78.6 83.8 89.5 95.0 Goods 61.6 63.2 65.8 68.3 69.2 73.2 77.8 83.3 89.2 94.9 Food 65.5 67.0 69.8 73.5 73.5 77.2 80.8 85.8 90.9 96.3 Animal products 69.1 69.7 71.1 78.3 71.6 75.4 81.2 86.4 92.3 97.2 Fish 56.7 58.8 62.5 67.7 74.4 77.8 80.6 83.3 91.1 101.7 Meat 73.6 72.9 75.4 84.2 74.4 81.2 88.2 93.1 98.1 97.0 Milk 67.2 70.7 70.8 79.7 66.0 61.5 67.8 75.4 82.6 98.3 Butter 69.0 70.8 70.2 71.0 75.7 79.5 78.9 82.2 90.5 98.4 Cheese 40.6 42.7 47.5 48.3 57.5 64.9 73.6 76.2 81.6 90.2 Eggs 65.5 62.5 61.2 63.8 66.8 74.2 79.8 84.4 88.9 92.2 Processed foods 61.8 64.7 68.9 71.7 78.4 81.9 82.8 87.6 91.3 96.1 Sugar 64.6 68.3 71.4 76.3 77.6 84.8 90.0 94.4 96.2 96.8 Vegetable oil 68.8 74.0 79.2 84.5 91.2 99.3 89.1 92.9 93.8 96.2 Margarine 65.2 65.2 67.0 75.7 85.7 78.4 78.8 81.5 87.0 96.4 Confectioneries 56.0 58.2 63.2 65.8 74.5 75.7 75.0 80.7 86.9 95.0 Macaroni 80.8 80.7 87.8 63.0 94.5 91.3 90.8 93.6 91.5 100.0 Basic foods 84.1 84.9 86.8 84.7 88.3 90.8 90.5 93.2 96.4 95.2 Potatoes 97.1 98.8 99.7 100.6 101.2 103.9 99.9 97.9 98.9 99.9 Vegetables 75.3 73.4 74.6 71.2 84.8 83.5 85.6 94.8 94.6 91.8 Fruit 55.5 56.2 62.2 65.1 68.0 76.1 74.1 81.8 92.9 85.2 Flour and groats 93.6 94.8 95.7 90.9 92.6 94.1 95.1 95.4 97.4 98.7 Beverages and tobacco 47.0 49.9 55.0 58.6 62.1 66.6 71.6 78.2 84.4 95.8 Alcohol and soft drinks 46.1 49.2 54.7 58.3 61.7 66.4 71.4 78.1 84.3 96.1 Tea 53.5 54.4 62.7 69.5 71.7 66.9 76.7 80.7 80.6 91.0 Tobacco 53.7 55.2 56.2 59.1 63.5 68.7 72.6 79.1 86.2 94.5 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV --.1 73.4 Soft goods 57.0 58.9 60.9 61.2 63.1 67.4 79.9 86.9 93.5 Cotton fabrics 126.2 112.9 107.9 103.4 1(11.3 99.8 105.0 109.4 108.9 107.7 Wool fabrics 109.3 101.5 92.5 84.1 83.2 96.4 97.2 97.8 103.3 104.3 Silk fabrics 87.9 84.3 89.6 89.2 85.0 96.2 103.9 106.8 101.8 98.0 Linen fabrics 66.9 64.0 57.1 55.1 55.6 69.7 82.4 88.1 97.6 101.4 Sewn goods 53.0 56.6 58.7 57.5 56.2 56.1 61.6 70.6 81.3 90.6 Hosiery 72.0 74.8 77.2 83.8 92.4 100.9 107.9 111.0 109.6 104.3 Leather shoes 59.6 63.4 66.9 66.6 69.2 74.1 79.4 84.4 89.9 93.7 Rubber footwear 96.1 94.6 90.9 92.3 95.2 93.1 94.9 97.2 97.5 97.0 Felt footwear 99.1 105.0 106.3 107.9 107.9 104.7 102.5 101.3 101.9 100.0 Knitwear 38.7 40.4 42.9 45.7 52.8 61.4 69.1 76.0 83.7 92.6 Haberdashery 46.6 49.9 54.0 54.8 56.6 62.7 68.7 73.8 81.6 90.3 School supplies 38.5 40.0 41.6 43.7 49.5 54.3 60.2 66.2 75.9 87.7 Publications 46.3 48.4 50.8 54.5 57.7 65.7 73.0 80.0 84.4 94.5 Household soap 50.3 52.4 54.1 60.3 61.8 69.4 76.0 85.8 93.4 96.0 Toilet soap 46.0 48.2 51.7 52.1 56.3 60.9 67.4 74.9 82.3 90.8 Durables 47.3 48.1 50.5 50.4 55.4 61.6 68.9 74.8 83.0 89.5 Consumer services 58.3 60.8 64.2 67.9 72.3 77.0 81.5 85.9 90.9 95.2 Household services 53.7 55.5 58.6 61.9 66.6 71.8 77.0 82.9 89.0 94.2 Housing 70.6 74.1 77.4 80.5 83.3 86.0 88.8 91.6 94.5 97.3 Urban housing 61.8 65.9 69.7 73.5 77.1 .80.7 84.3 88.1 92.1 96.0 Rural housing 81.3 84.2 86.7 88.9 90.8 92.5 94.2 96.0 97.5 98.8 Utilities 45.9 50.4 55.5 60.9 66.5 72.1 77.1 81.9 87.7 93.9 Electricity 42.1 46.9 52.6 58.3 64.5 70.7 75.5 80.9 87.4 93.6 Gas 24.3 29.9 37.3 45.5 55.0 64.7 72.4 74.3 81.1 91.9 Other utilities 53.9 58.0 62.1 66.4 70.7 75.0 79.6 84.4 89.4 94.6 Transportation 40.1 44.0 49.7 54.8 59.3 64.8 72.0 79.1 86.6 93.0 Rail 64.4 66.4 71.3 72.3 73.5 76.0 82.7 88.3 95.7 98.5 Sea 83.7 85.8 83.5 91.0 83.7 92.7 103.3 104.4 110.8 109.7 River 79.1 81.5 85.3 87.0 86.0 90.8 95.0 98.1 100.8 101.7 Bus 30.1 34.2 40.6 47.0 53.2 59.5 67.6 75.6 83.2 90.4 Air 15.5 21.0 26.0 32.4 39.5 48.7 57.7 68.4 79.4 91.4 Tram 98.5 97.7 99.7 101.8 103.3 103.5 102.9 102.1 100.1 98.4 Trolleybus 49.9 51.3 54.8 59.4 64.5 70.2 77.0 82.3 87.1 92.9 Subway 50.0 53.7 56.7 62.8 68.4 72.0 79.4 84.9 90.3 94.8 Taxi 26.5 34.2 43.2 50.6 53.5 59.1 64.4 71.6 81.3 90.8 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-1 (continued) 1960 1961 1962 1970 = 100 1963 1964 1965 1966 1967 1968 1969 Communications 46.5 49.2 52.3 55.3 59.3 65.4 72.3 79.8 85.5 93.0 Postal 45.1 47.7 50.6 54.9 60.8 67.6 75.6 84.0 88.4 94.7 Telegraph 66.1 67.2 69.2 69.8 70.6 74.9 82.2 88.5 92.9 97.9 Telephone 41.9 44.7 47.9 49.9 52.6 59.2 65.4 72.7 79.9 89.7 Radio-TV 48.9 53.3 57.3 61.3 64.9 69.1 74.0 79.8 86.6 93.3 Repair and personal care 53.8 50.1 49.9 51.5 56.5 63.5 70.3 77.7 85.4 91.7 State services 27.5 30.3 33.4 36.9 43.8 53.2 60.6 69.9 , 79.5 90.5 Private services 180.4 146.0 129.7 121.6 118.0 113.0 117.2 115.3 113.8 97.6 Recreation 73.0 75.9 77.8 78.2 84.4 87.7 88.2 93.6 97.6 98.6 Entertainment 77.7 82.8 84.5 83.5 88.7 92.0 90.2 96.6 101.1 100.1 Resorts 61.0 60.7 64.0 65.2 77.7 82.0 86.3 89.7 92.9 97.0 Leisure 71.5 71.6 72.7 75.8 79.5 82.1 84.7 89.3 92.7 96.2 Goods and household services 60.7 62.3 65.0 67.5 68.9 73.1 77.7 83.3 89.2 94.9 Communal services 62.6 65.8 69.4 73.5 77.7 81.9 85.6 88.7 92.7 96.2 Education 59.3 62.9 68.0 72.8 77.8 82.3 86.3 89.6 93.8 97.4 Labor 62.5 65.3 69.9 73.7 78.7 83.3 87.3 90.4 94.2 97.1 Other current purchases 51.2 56.9 63.4 70.4 75.6 79.9 83.8 87.8 92.7 98.0 Health 68.0 70.5 71.7 74.8 77.6 81.3 84.5 87.0 90.8 94.3 Labor 69.4 72.2 75.0 77.2 80.3 83.8 86.9 89.4 93.4 97.1 Other current purchases 65.6 67.6 66.1 70.8 73.1 77.0 80.4 83.0 86.3 89.6 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1970 . 1971 1972 1973 1974 1975 1976 1977 1978 1979 Consumption 100.0 103.9 106.5 110.6 115.5 120.7 124.0 127.9 132.1 136.4 Goods 100.0 103.9 106.2 110.3 115.2 120.4 123.5 127.6 131.5 135.7 Food 100.0 102.2 102.3 105.7 110.0 113.6 114.5 117.0 120.3 123.2 Animal products 100.0 102.1 103.9 109.3 113.5 118.3 118.2 119.7 122.0 125.2 Fish 100.0 97.0 99.9 107.6 111.2 114.3 126.4 118.4 119.5 115.5 Meat 100.0 105.2 108.3 113.6 119.0 124.5 123.4 124.5 127.8 131.1 Milk 100.0 95.9 91.4 88.7 93.5 97.9 96.3 92.2 92.5 97.5 Butter 100.0 97.2 98.5 121.1 113.4 113.6 113.2 130.7 125.3 131.3 Cheese 100.0 96.9 101.0 112.1 118.2 117.6 128.2 137.0 144.6 146.7 Eggs 100.0 110.5 118.6 126.2 133.9 142.4 139.0 148.9 157.0 159.0 Processed foods 100.0 102.3 103.9 110.3 113.5 114.2 119.2 123.6 127.9 130.4 Sugar 100.0 103.5 101.9 108.1 108.9 110.1 113.5 115.2 116.5 117.1 Vegetable oil 100.0 103.9 103.4 110.4 120.6 117.1 119.8 127.1 131.4 134.0 Margarine 100.0 104.7 113.7 128.9 127.5 129.5 140.4 157.7 165.4 171.9 Confectioneries 100.0 100.3 103.3 110.2 115.1 114.9 120.5 126.2 132.8 136.0 Macaroni 100.0 105.9 118.6 110.9 110.7 123.2 134.4 130.2 135.7 143.5 Basic foods Potatoes 100.0 103.6 99.4 103.3 102.5 102.8 101.0 106.4 108.0 107.1 100.0 99.4 94.9 98.1 96.6 96.8 96.8 98.5 96.9 91.8 Vegetables 100.0 104.6 99.4 106.6 110.2 113.8 110.9 114.5 120.7 127.0 Fruit 100.0 112.5 104.8 117.6 109.8 116.8 117.9 125.0 126.1 117.8 Flour and groats 100.0 101.3 98.9 98.5 99.3 95.8 92.6 99.2 100.8 102.4 Beverages and tobacco 100.0 101.3 101.4 100.0 109.2 114.8 117.6 118.2 124.1 129.7 Alcohol and soft drinks 100.0 100.7 100.1 97.8 107.4 112.5 114.9 114.6 120.6 125.8 Tea 100.0 99.1 104.7 102.4 114.9 126.7 132.9 149.7 153.0 162.6 Tobacco Soft goods 100.0 106.3 104.7 112.3 118.6 123.8 132.4 137.0 142.3 148.5 156.1 100.0 107.8 111.2 115.2 121.5 127.2 131.4 135.2 140.9 Cotton fabrics 100.0 96.8 92.2 96.3 88.0 86.1 88.0 86.6 87.9 94.6 Wool fabrics 100.0 103.3 116.4 127.1 139.8 152.9 151.3 147.2 163.2 172.6 Silk fabrics 100.0. 98.3 114.5 122.9 130.1 182.8 207.3 208.9 182.3 197.9 Linen fabrics 100.0 105.9 110.8 110.5 109.4 99.5 104.4 114.4 119.4 107.4 Sewn goods 100.0 106.3 107.5 109.4 112.5 118.7 123.7 130.8 135.9 141.6 Hosiery 100.0 97.8 99.9 105.4 109.8 111.7 115.1 116.9 119.3 122.3 Leather shoes 100.0 100.0 99.1 100.4 104.5 105.5 109.3 112.5 112.8 112.1 Rubber footwear 100.0 103.5 104.0 112.1 118.5 118.5 117.3 113.9 112.7 112.1 Felt footwear 100.0 99.1 97.2 96.9 95.9 94.7 91.8 89.9 87.4 82.7 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Approved for Release: 2019/07/19 C05210421 Table A-1 (continued) 1970 = 100 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Soft goods (continued) Knitwear 100.0 105.2 106.7 110.7 113.0 114.1 116.7 119.2 121.2 123.2 Haberdashery 100.0 110.8 121.2 125.3 131.5 142.9 152.2 164.2 171.3 182.4 School supplies 100.0 111.0 122.4 127.3 137.9 146.6 152.1 162.2 168.6 177.7 Publications 100.0 106.0 112.5 118.7 125.0 134.0 139.8 135.5 144.7 155.2 Household soap 100.0 108.6 119.6 118.6 123.8 136.7 135.8 140.7 147.9 170.5 Toilet soap 100.0 109.9 120.2 129.4 138.8 154.5 169.9 188.0 215.2 243.3 Durables 100.0 113.5 131.0 142.1 154.0 168.9 180.1 196.7 205.0 213.5 Consumer services 100.0 104.1 107.8 112.0 116.9 121.7 126.0 129.1 134.2 138.9 Household services 100.0 105.6 111.6 117.6 124.4 131.2 137.5 141.0 147.6 154.5 Housing 100.0 102.7 105.5 108.4 111.2 114.1 116.8 119.5 122.2 124.8 Urban housing 100.0 104.2 108.6 113.1 117.7 122.3 126.7 131.2 135.8 140.2 Rural housing 100.0 101.0 101.9 102.6 103.3 104.0 104.7 105.2 105.7 106.0 Utilities 100.0 106.8 113.8 120.8 128.2 135.7 143.8 149.5 156.6 163.0 Electricity 100.0 107.6 114.8 122.0 129.6 137.4 147.0 152.1 159.0 163.8 Gas 100.0 108.1 120.3 132.4 144.6 156.8 168.9 175.3 188.6 206.0 Other utilities 100.0 105.7 111.5 117.4 123.6 129.8 135.7 141.7 147.8 153.8 Transportation 100.0 106.9 114.8 121.5 131.2 141.2 149.5 148.8 154.6 161.4 Rail 100.0 103.5 107.7 111.8 115.4 117.7 118.7 121.4 125.1 126.3 Sea 100.0 108.0 117.8 122.0 131.2 134.2 152.0 165.9 147.3 154.4 River 100.0 105.0 105.0 108.7 112.4 116.1 110.6 103.2 106.9 106.9 Bus 100.0 106.6 116.4 125.4 137.8 149.9 160.7 170.1 178.6 185.7 Air 100.0 113.6 122.6 126.3 139.1 156.8 167.3 163.0 179.2 193.1 Tram 100.0 100.2 99.9 100.4 101.4 103.4 105.0 105.1 105.3 104.2 Trolleybus 100.0 107.6 113.9 119.2 124.8 130.1 136.5 141.0 143.9 146.1 Subway 100.0 106.5 113.0 118.9 123.6 129.5 140.7 146.3 153.2 160.2 Taxi 100.0 110.4 120.6 129.3 141.9 156.1 169.7 115.4 107.5 121.6 Approved for Release: 2019/07/19 C05210421 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Communications 100.0 107.3 115.2 123.5 132.4 142.0 151.1 159.6 168.4 177.9 Postal 100.0 105.2 110.0 113.7 117.1 121.2 122.7 124.0 124.5 126.6 Telegraph 100.0 102.0 105.6 110.8 115.5 121.5 125.6 130.8 134.7 140.2 Telephone 100.0 110.9 123.1 137.8 154.6 172.1 191.9 210.3 230.5 250.4 Radio-TV 100.0 107.4 116.3 123.0 130.1 137.1 143.2 149.3 155.2 160.7 Repair and personal care 100.0 106.4 113.8 122.0 130.1 138.1 146.3 153.5 164.5 175.9 State services 100.0 107.8 116.7 126.6 136.4 146.0 155.9 164.6 177.8 191.7 Private services 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Recreation 100.0 102.3 103.4 105.4 107.0 108.0 106.3 106.7 109.5 111.4 Entertainment 100.0 100.1 98.3 98.6 - 98.3 96.9 90.9 88.1 89.7 89.7 Resorts 100.0 104.5 109.2 113.6 117.2 121.8 127.0 131.9 135.0 139.6 Leisure 100.0 105.9 111.1 115.2 120.0 124.4 127.4 132.0 137.6 141.9 Goods and household services 100.0 104.0 106.8 111.1 116.2 121.6 125.1 129.2 133.4 137.8 Communal services 100.0 102.7 104.4 106.7 109.9 112.7 115.2 117.8 121.5 124.3 Education 100.0 102.9 104.2 106.5 109.7 112.7 115.3 118.1 121.7 124.3 Labor 100.0 102.9 105.2 107.1 109.5 111.7 113.8 115.8 119.2 121.7 Other current purchases 100.0 102.9 101.8 105.1 110.0 115.1 118.9 123.5 128.1 130.9 Health 100.0 102.3 104.5 107.0 110.2 112.6 114.9 117.6 121.3 124.3 Labor 100.0 103.4 106.2 108.5 111.3 113.4 115.6 117.1 118.5 121.7 Other current purchases 100.0 100.4 101.6 104.4 108.2 111.2 113.8 118.3 126.1 128.8 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-1 (continued) 1970 = 100 1980 Consumption 140.4 Goods 139.5 Food 124.5 Animal products 125.3 Fish 120.7 Meat 129.9 Milk 98.6 Butter 128.3 Cheese 141.4 Eggs 163.7 Processed foods 131.8 Sugar 115.4 Vegetable oil 138.3 CI\ Margarine 170.5 ts.) Confectioneries 139.9 Macaroni 146.0 Basic foods 105.3 Potatoes 94.2 Vegetables 124.0 Fruit 106.2 Flour and groats 103.2 Beverages and tobacco 135.3 Alcohol and soft drinks 130.9 Tea 183.3 Tobacco 162.6 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Soft goods 147.7 Cotton fabrics 94.6 Wool fabrics 170.6 Silk fabrics 233.9 Linen fabrics 109.4 Sewn goods 149.9 Hosiery 124.5 Leather shoes 113.8 Rubber footwear 112.1 Felt footwear 78.6 Knitwear 124.8 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Haberdashery 194.0 School supplies 186.5 Publications 165.7 Household soap 181.8 Toilet soap 266.5 Durables 227.9 Consumer services 143.7 Cr\ Household services 161.6 Housing 127.4 Urban housing 144.6 Rural housing 106.5 Utilities 170.4 Electricity 171.3 Gas 220.4 Other utilities 159.6 Transportation 167.6 Rail 124.8 Sea 157.2 River 110.6 Bus 192.5 Air 205.4 Tram 103.7 Trolleybus 147.6 Subway 166.6 Taxi 138.7 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-1 (continued) 1970 = 100 1980 Communications 187.9 Postal 129.0 Telegraph 145.6 Telephone 271.3 Radio-TV 166.9 Repair and personal care 188.0 State services 206.3 Private services 100.0 Recreation 114.3 Entertainment 91.7 Resorts 143.5 Leisure 146.0 Goods and household services 142.1 Communal services 126.9 Education 127.8 Labor 126.1 Other current purchases 132.3 t Health 125.2 i Labor 122.8 1 Other current purchases 129.4 a Because of rounding, components may not add to totals shown. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-2 Per Capita Consumption in Established Prices, by Category, 1950-80 1970 = 100 ta C, 1_,�1 1950 1951 1952 1953 1954 1955 1956 1957, 1958 1959 Consumption 45.6 45.9 48.4 51.4 54.1 56.8 58.6 61.9 65.0 66.6 Goods 44.6 44.7 47.6 51.1 54.0 56.7 58.8 62.7 66.0 67.3 Food 53.3 51.7 55.3 , 58.7 59.7 63.0 64.6 68.6 72.0 72.5 Animal products 52.5 52.5 53.0 54.8 56.6 57.4 61.1 66.1 73.6 75.6 Processed foods 35.1 45.7 49.8 58.7 47.4 57.5 61.7 62.7 64.4 66.4 Basic foods 97.6 80.1 89.6 92.7 96.1 98.5 95.0 99.0 97.9 97.0 Beverages and tobacco 28.1 30.9 34.0 37.4 41.4 45.7 46.8 50.9 52.6 51.6 Soft goods 33.0 36.8 38.3 41.5 47.6 49.3 52.5 55.0 58.2 60.8 Durables 14.6 16.7 18.8 24.1 30.3 32.5 35.0 41.6 45.0 48.2 Consumer services 49.4 50.1 51.3 52.4 54.6 57.1 57.9 59.2 61.4 64.0 Household services 42.6 43.8 45.0 46.0 47.9 50.5 51.2 52.6 55.6 59.3 Housing 64.9 65.5 66.2 66.6 67.5 68.5 69.7 71.5 74.0 77.0 Utilities 33.8 35.3 37.0 38.3 39.8 41.3 42.9 44.3 46.8 49.5 Transportation 18.3 20.1 21.7 23.8 26.2 29.7 31.3 35.1 38.5 41.5 Communications 30.3 32.5 34.9 36.3 38.7 40.9 43.3 45.8 47.7 49.8 Repair and personal care 56.8 56.9 57.0 57.0 57.3 57.7 55.3 53.8 56.4 63.8 Recreation 50.7 52.9 55.4 56.8 62.4 - 71.3 73.9 75.9 80.5 81.1 Goods and household services 44.3 44.6 47.3 50.6 53.3 56.0 57.9 61.5 64.8 66.4 Communal services 55.8 56.1 57.2 58.3 60.8 63.3 64.2 65.4 66.8 68.4 Education 57.7 58.1 58.9 59.2 60.7 62.3 62.9 63.4 64.2 65.0 Health 52.6 52.8 54.4 56.9 61.0 64.9 66.3 68.6 71.1 73.9 Population Million people 180.1 183.0 186.0 190.0 193.0 196.2 199.7 203.2 206.8 210.5 Index, 1970=100 74.2 75.4 76.6 78.3 79.5 80.8 82.2 83.7 85.2 86.7 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Approved for Release: 2019/07/19 C05210421 Table A-2 (continued) 1970 = 100 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Consumption 69.0 69.8 71.7 73.6 74.3 77.8 81.7 863 91.2 959. Goods 69.8 70.4 72.1 73.6 73.6 77.0 80.9 85.7 90.9 95.8 Food 74.2 74.5 76.5 79.3 78.2 81.1 84.1 88.3 92.7 97.2 Animal products 78.3 77.5 77.9 84.5 76.2 79.3 84.4 88.9 94.1 98.1 Processed foods 70.1 72.0 75.4 77.4 83.4 86.1 86.1 90.1 93.0 97.0 Basic foods 95.3 94.5 95.0 91.4 94.0 95.5 94.1 95.9 98.2 96.1 Beverages and tobacco 53.2 55.5 60.2 63.2 66.1 70.0 74.5 80.5 86.0 96.7 Soft goods 64.5 65.6 66.7 66.0 67.2 70.9 76.3 82.2 88.6 94.3 Durables 53.6 53.6 55.3 54.3 58.9 64.7 71.6 76.9 84.5 90.3 Consumer services 66.0 67.7 70.3 73.2 77.0 81.0 84.7 88.4 92.6 96.1 Household services 60.8 61.8 64.2 66.7 70.9 75.5 80.1 85.3 90.7 95.0 Housing 80.0 82.5 84.8 86.8 88.7 90.4 92.3 94.3 96.3 98.2 Utilities 52.0 56.1 60.8 65.7 70.7 75.9 80.2 84.3 89.4 94.8 Transportation 45.5 49.0 54.4 59.1 63.1 68.1 74.8 81.3 88.2 93.9 Communications 52.7 54.8 57.2 59.7 63.1 68.8 75.2 82.1 87.1 93.8 Repair and personal care 60.9 55.8 54.7 55.5 60.2 66.8 73.1 79.9 87.0 92.6 Recreation 82.7 84.5 85.2 84.3 89.9 92.3 91.7 96.3 99.4 99.5 Goods and household services 68.8 69.4 71.2 72.9 73.3 76.8 80.8 85.6 90.9 95.7 Communal services 70.9 73.2 76.0 79.3 82.7 86.1 89.1 91.2 94.4 97.1 Education 67.2 70.0 74.5 78.5 82.8 86.5 89.7 92.2 95.5 98.3 Health 77.1 78.5 78.5 80.7 82.6 85.5 87.9 89.5 92.5 95.2 Population Million people 214.3 218.1 221.7 225.1 228.1 230.9 233.5 236.0 238.3 240.6 Index, 1970=100 88.3 89.8 91.3 92.7 93.9 95.1 96.2 97.2 98.1 99.1 Approved for Release: 2019/07/19 C05210421 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-2 (continued) 1970 = 100 1971 1975 1976 1979 1970 1972 1973 1974 1977 1978 Consumption 100.0 102.9 104.5 107.5 111.3 115.1 117.3 119.9 122.8 125.7 Goods 100.0 102.9 104.2 107.2 102.7 110.9 114.9 116.8 119.6 122.2 125.1 Food 100.0 101.3 100.3 106.0 108.3 108.3 109.6 111.8 113.6 Animal products 100.0 101.2 101.9 106.2 109.3 112.9 111.7 112.2 113.3 115.4 Processed foods 100.0 101.3 101.9 107.2 109.3 109.0 112.7 115.9 118.8 120.2 Basic foods 100.0 102.6 97.5 100.4 98.7 98.1 95.5 99.7 100.3 98.8 Beverages and tobacco 100.0 100.3 99.5 97.2 105.2 109.5 111.1 110.8 115.3 119.6 Soft goods 100.0 103.7 105.8 108.1 110.9 115.9 120.3 123.2 125.6 129.9 Durables 100.0 112.4 128.5 138.1 148.3 161.2 170.3 184.4 190.5 196.8 Consumer services 100.0 103.1 105.8 109.4 112.6 116.1 119.1 121.0 127.2 128.1 Household services 100.0 104.6 109.4 114.3 119.8 125.2 130.0 132.2 137.2 142.4 Housing 100.0 101.8 103.5 105.3 107.1 108.8 110.4 112.0 113.5 115.1 Utilities 100.0 105.8 111.6 117.5 123.5 1294 136.0 140.1 145.5 150.3 Transportation 100.0 105.9 112.6 118.1 126.3 134.7 141.4 139.5 143.7 148.8 Communications 100.0 106.3 113.0 120.0 127.5 135.4 142.8 149.7 156.5 163.9 Repair and personal care 100.0 105.4 111.7 118.6 125.3 131.7 138.3 143.9 152.8 162.2 Recreation 100.0 101.4 101.4 102.4 103.0 103.1 100.5 100.1 101.8 102.7 Goods and household services 100.0 103.1 104.8 108.0 111.9 116.1 118.3 121.1 124.0 127.0 Communal services 100.0 101.7 102.4 103.7 105.8 107.5 108.9 110.5 112.9 114.6 Education 100.0 101.9 102.3 103.6 105.6 107.5 109.0 110.7 113.1 114.6 Health 100.0 101.4 102.5 104.0 106.1 107.4 108.7 110.2 112.7 114.6 Population Million people 242.8 245.5 247.5 249.8 252.1 254.5 256.8 259.0 261.3 263.4 Index, 1970= 100 100.0 100.9 101.9 102.9 103.8 104,8 105.8 106.7 107.6 108.5 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Table A-2 (continued) 1980 1970 = 100 Consumption 128.4 Goods 127.6 Food 113.9 Animal products 114.6 Processed foods 120.5 Basic foods 96.3 Beverages and tobacco 123.7 Soft goods 135.0 Durables 208.5 Consumer services 131.4 Household services 147.8 Housing 116.5 Utilities 155.9 Transportation 153.3 Communications 171.8 Repair and personal care 171.9 Recreation 104.5 Goods and household services 129.9 Communal services 116.0 Education 116.9 Health 114.5 Population Million people 265.5 Index, 1970=100 109.3 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix B Data Used in the Derivation of the Index of Food, Beverages, and Tobacco 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Meat-kg per capita 26. 25. 26. 27. 28. 28. 30. 32. 36. 38. Fish-kg per capita 7.0 8.1 7.9 8.0 8.8 9.4 9.5 9.6 9.8 9.8 Vegetable oil-kg per capita 2.7 3.2 3.5 4.2 4.7 3.9 4.2 4.4 4.7 5.0 Margarine-production (thousand tons) 192. 226. 277. 338. 392. 399. 437. 449. 395. 452. Margarine-wholesale inventories (thousand tons) 3.3 3.8 4.3 4.9 5.6 6.4 7.0 8.2 6.2 11.8 Margarine-retail inventories (thousand tons) 38.6 41.0 43.6 46.4 49.4 52.5 84.7 105.0 81.5 101.8 Margarine-consumption (thousand tons) 192. 223. 274. 335. 388. 395. 404. 427. 421. 426. Milk-kg per capita 172. 171. 167. 166. 167. 175. 193. 216. 238. 239. Milk-total consumption (million tons) 30.977 31.365 31.147 31.485 32.236 34.335 38.542 43.891 49.218 50.309 Milk-used for butter (million tons) 9.379 9.862 10.270 10.550 10.728 12.611 14.984 17.040 17.583 19.097 Milk-used for cheese (million tons) 0.934 1.084 1.164 1.307 1.420 1.690 1.882 1.984 2.163 2.253 Milk-net consumption (million tons) 20.664 20.418 19.713 19.629 20.089 20.035 21.677 24.867 29.472 28.960 t.....) Butter-production (thousand tons) 415. 436. 454. 467. 475. 558. 663. - 754. 778. 845. CA VD Butter-wholesale inventories (thousand tons) 15.1 15.9 16.7 17.6 18.5 19.5 � 18.6 31.4 44.4 31.9 Butter-retail inventories (thousand tons) 17.0 17.3 17.6 17.9 18.2 18.6 31.5 44.8 42.6 44.8 Butter-exports (thousand tons) 33.4 22.9 15.7 10.8 7.4 5.1 26.4 49.1 24.7 80.3 Butter-imports (thousand tons) 4.5 4.7 4.9 5.1 5.4 5.6 5.8 8.2 25.2 13.6 Butter-consumption (thousand tons) 386.1 417.1 442.4 459.9 471.4 557.2 630.3 687.0 767.8 788.5 Cheese-production (thousand tons) 73. 85. 91. 102. III. 132. 147. 155. 169. 176. Eggs-number per capita 60. 68. 73. 80. 85. 90. 94. 106. 108. 114. Sugar-kg per capita 11.6 17.4 18.5 22.9 12.6 22.0 23.5 24.0 24.2 25.0 Sugar-total consumption (million tons) 2.089 3.190 3.433 4.346 2.424 4.316 4.693 4.877 5.005 5.262 Sugar-used for confectioneries (million tons) 0.645 0.753 0.836 0.916 0.947 0.903 1.028 1.024 1.089 1.162 Sugar-net consumption (million tons) 1.444 2.438 2.597 3.429 1.477 3.414 3.665 3.853 3.915 4.101 Confectioneries-production (thousand tons) 993. 1,158. 1,286. 1,410. 1,457. 1,389. 1,582. 1,575. 1,676. 1,787. Confectioneries-index of quality (1970=100) 91.4 91.7 92.0 92.4 92.7 93.0 93.3 93.7 94.1 93.5 Confectioneries-adjusted production index 31.3 36.7 40.9 45.0 46.6 44.6 51.0 51.0 54.5 57.7 (1970=100) Tea-production (thousand tons) 84.9 94.9 97.7 110.0 110.2 121.0 110.0 112.4 138.2 145.7 Tea-net imports (thousand tons) 3.2 3.4 3.7 3.9 4.2 4.5 9.6 15.3 21.4 25.1 Tea-inventory change (thousand tons) -1.0 -1.8 -3.1 -5.5 -9.8 -17.3 -1.4 3.6 7.5 18.7 Tea-consumption (thousand tons) 89.1 100.1 104.5 119.5 124.2 142.8 121.0 124.1 152.1 152.1 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix B (continued) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1950 1951 1952 1954 1955 1956 1957 1958 1959 1953 Flour-kg per capita 172. 176. 180. 179. 183. 189. 184. 178. 172. 169. Flour-total consumption (million tons) 30.977 32.198 53.419 34.029 35.250 37.082 36.745 36.170 35.570 35.574 Flour-used in macaroni (million tons) 0.450 0.507 0.631 0.757 0.870 0.980 0.882 0.979 0.972 0.984 Flour-used in confectioneries (million tons) 0.348 0.405 0.450 0.493 0.510 0.486 0.554 0.551 0.587 0.625 Flour-net consumption (million tons) 30.180 31.285 32.338 32.779 33.871 35.616 35.309 34.639 34.011 33.965 Flour-index of quality (1970=100) 84.6 86.4 88.2 89.1 90.0 90.9 91.4 92.0 92.5 93.7 Flour-adjusted index of consumption (1970 = 100) 75.2 79.6 84.0 86.0 89.8 95.4 95.1 93.9 92.7 93.7 Macaroni-deflated retail sales (million 1970 rubles) 157. 184. 241. 301. 355. 379. 346. 389. 418. 401. Potatoes-kg per capita 241. 107. 152. 163. 167. 148. 148. 149. 150. 150. Vegetables-kg per capita 51. 48. 51. 58. 60. 69. 65. 66. 71. 67. Fruits and berries-kg per capita 11. 12. 12. 13. 15. 17. 14. 23. 22. 22. Vodka and liquor-consumption (million dekaliters) 62.8 71.1 80.5 91.2 103.2 116.9 122.9 140.2 145.4 137.3 Cognac-consumption (million dekaliters) 0.4 0.5 0.7 1.0 1.3 1.7 1.6 1.2 1.2 1.4 Rum-consumption (million dekaliters) Wine-consumption (million dekaliters) 30.4 34.8 39.7 45.4 52.0 59.4 64.6 69.1 78.7 85.4 Champagne-consumption (million dekaliters) 1.1 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 Beer-consumption (million dekaliters) 131.0 140.3 150.3 161.0 172.4 184.7 180.7 196.5 199.1 231.9 Nonalcoholic beverages-consumption (million dekaliters) 71.9 82.0 78.9 87.8 104.7 97.8 97.2 115.2 120.1 134.6 Tobacco-deflated retail sales (million 1970 rubles) 814. 864. 915. 996. 1,118. 1,200. 1,268. 1,321. 1,370. 1,423. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI penaidd\of 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Meat-kg per capita 40. 39. 40. 44. 38. 41. 44. 46. 48. 47. Fish-kg per capita 9.9 10.1 10.5 11.2 12.2 12.6 12.9 13.2 14.3 15.8 Vegetable oil-kg per capita 5.3 5.6 5.9 6.2 6.6 7.1 6.3 6.5 6.5 6.6 Margarine-production (thousand tons) 431. 476. 516. 566. 606. 670. 599. 624. 652. 691. Margarine-wholesale inventories (thousand tons) 7.3 9.8 9.2 9.4 7.3 16.0 19.6 32.4 35.4 25.2 Margarine-retail inventories (thousand tons) 54.7 45.0 65.4 70.7 43.9 124.3 136.1 143.6 147.9 135.0 Margarine-consumption (thousand tons) 483. 483. 496. 560. 635. 581. 584. 604. 645. 714. Milk-kg per capita 240. 248. 250. 259. 238. 251. 260. 274. 285. 304. Milk-total consumption (million tons) 51.432 54.160 55.510 58.230 54.288 57.956 60.710 64.664 67.915 73.142 Milk-used for butter (million tons) 19.165 20.204 21.244 19.978 21.515 26.758 26.148 26.600 26.329 24.069 > -0 Milk-used for cheese (million tons) 2.483 2.611 2.906 2.957 3.520 3.968 4.659 4.992 5.517 4.506 7 Milk-net consumption (million tons) 29.784 31.344 31.360 35.295 29.253 27.229 30.056 33.405 36.595 43.557 0 < Butter-production (thousand tons) 848. 894. 940. 884. 952. 1,184. 1,157. 1,177. 1,165. 1,065. ('D 0- Butter-wholesale inventories (thousand tons) 35.1 40.8 45.7 32.4 61.8 174.1 388.8 532.7 537.2 333.5 0 -s Butter-retail inventories (thousand tons) 33.4 29.6 60.9 49.7 48.5 135.5 85.5 77.5 86.4 109.5 7:1 ('D f.,..) ---.1 .--) Butter-exports (thousand tons) 37.2 55.6 69.7 65.0 2.8 846.3 25.3 43.0 5.8 947.5 54.1 2.3 940.5 63.4 2.2 75.6 2.4 1,078.4 74.3 2.0 1,173.3 (T) sl� (,) ('D " iv Butter-imports (thousand tons) 4.0 7.8 3.3 837.4 4.2 Butter-consumption (thousand tons) 823.0 844.3 '402.7 979.9 Cheese-production (thousand tons) 194. 204. 227. 231. 275. 310. 352. 364. 390. 431. c) Eggs-number per capita 118. 28.0 III. 107. 109. 113. 124. 132. 35.3 138. 36.7 144. 37.4 148. 37.8 co c) --.) Sugar-kg per capita 29.0 30.0 31.5 32.2 34.2 Sugar-total consumption (million tons) 6.000 6.325 6.651 7.091 7.345 7.897 8.243 8.661 8.912 9.095 co Sugar-used for confectioneries (million tons) 1.134 1.174 1.267 1.340 1.499 1.505 1.455 1.543 1.658 1.979 0 c) Sugar-net consumption (million tons) 5.751 7.297 _ 4.867 5.151 5.383 5.846 6.392 6.788 7.118 7.254 C71 n) Confectioneries-production (thousand tons) 1,744. 1,806. 1,950. 2,061. 2,306. 2,315. 2,238. 2,374. 2,551. 2,765. -8 Confectioneries-index of quality (1970=100) 93.0 56.0 93.4 58.2 93.8 63.2 92.5 65.8 93.6 74.5 94.7 75.7 97.0 75.0 98.4 80.7 98.6 86.9 _ 99.5 95.0 -P� n) _. Confectioneries-adjusted production index (1970=100) Tea-production (thousand tons) 163.7 161.6 178.9 195.6 193.7 197.0 238.2 234.4 229.0 244.6 Tea-net imports (thousand tons) 17.3 9.2 8.6 14.4 23.7 25.2 9.4 12.8 9.1 15.2 Tea-inventory change (thousand tons) 17.3 4.5 -4.1 -.2.4 -1.9 17.8 13.2 0.4 -8.4 - 18.5 Tea-consumption (thousand tons) 163.7 166.3 191.6 212.4 219.3 204.4 234.4 246.8 246.5 278.3 Appendix B (continued) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1960 1961 163. 1962 1963 1964 1965 1966 1967 1968 1969 Flour-kg per capita 164. 162. 161. 159. 156. 153. 150. 149. 149. Flour-total consumption (million tons) 35.145 35.550 35.915 36.241 36.268 36.020 35.725 35.400 35.507 35.849 Flour-used in macaroni (million tons) 1.030 1.022 1.078 1.160 1.293 1.280 1.123 1.181 1.087 1.199 Flour-used in confectioneries (million tons) 0.610 0.632 0.682 0.721 0.807 0.810 0.783 0.831 0.893 0.968 Flour-net consumption (million tons) 33.505 33.896 34.155 34.360 34.168 33.930 33.819 33.389 33.526 33.683 Flour-index of quality (1970=100) 94.9 95.0 95.1 89.8 92.0 94.1 95.5 97.0 98.7 99.4 Flour-adjusted index of consumption (1970=100) 93.6 94.8 95.7 90.9 92.6 94.1 95.1 95.4 97.4 98.7 Macaroni-deflated retail sales (million 1970 rubles) 439. 438. 477. 342. 513. 496. 493. 508. 497. 543. Potatoes-kg per capita 143. 143. 142. 141. 140. 142. 135. 131. 131. 131. Vegetables-kg per capita 70. 67. 67. 63. 74. 72. 73. 80. 79. 76. Fruits and berries-kg per capita 22. 22. 24. 25. 25. 28. 27. 29. 33. 30. Vodka and liquor-consumption (million dekaliters) 137.8 145.3 161.5 168.5 176.8 188.7 197.2 211.6 224.8 236.4 Cognac-consumption (million dekaliters) 1.7 2.0 2.2 2.5 2.7 3.2 4.0 4.9 5.8 6.7 Rum-consumption (million dekaliters) 0.0 0.6 0.3 0.3 0.4 0.6 0.3 0.4 0.8 0.7 Wine-consumption (million dekaliters) 102.9 111.7 129.4 151.0 165.7 177.9 202.9 232.0 257.2 351.7 Champagne-consumption (million dekaliters) 3.0 3.2 3.5 3.7 4.1 4.5 4.9 5.4 5.8 6.4 Beer-consumption (million dekaliters) 252.1 269.3 284.3 282.4 284.7 318.8 346.6 364.1 385.4 399.0 Nonalcoholic beverages-consumption (million dekaliters) 141.5 142.8 149.0 155.0 161.9 168.8 184.0 200.6 218.7 238.3 Tobacco-deflated retail sales (million 1970 rubles) 1,492. 1,534. 1,563. 1,642. 1,764. 1,909. 2,019. 2,198. 2,397. 2,627. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Meat-kg per capita 48. 50. 51. 53. 55. 57. 56. 56. 57. 58. Fish-kg per capita 15.4 14.8 15.1 16.1 16.5 16.8 18.4 17.1 17.1 16.4 Vegetable oil-kg per capita 6.8 7.0 6.9 7.3 7.9 7.6 7.7 8.1 8.3 8.4 Margarine-production (thousand tons) 762. 850. 850. 883. 997. 999. 1,040. 1,168. 1,225. 1,273. Margarine-wholesale inventories (thousand tons) 28.3 56.4 31.0 26.7 52.9 49.7 49.7 49.7 49.7 49.7 Margarine-retail inventories (thousand tons) 153.3 199.3 232.6 165.0 191.8 234.7 234.7 234.7 , 234.7 234.7 Margarine-consumption (thousand tons) 741. 776. 842. 955. 944. 959. 1,040. 1,168. 1,225. 1,273. Milk-kg per capita 307. 301. 296. 307. 315. 316. 316. 321. 318. 319. Milk-total consumption (million tons) 74.540 73.775 73.260 76.689 79.411 80.422 81.149 83.139 83.093 84.025 Milk-used for butter (million tons) 24.114 25.357 26.578 30.510 30.736 29.832 30.646 33.900 33.267 31.843 Milk-used for cheese (million tons) 6.118 5.926 6.182 6.861 7.232 7.194 7.846 8.384 8.845 8.973 Milk-net consumption (million tons) 44.307 42.491 40.500 39.318 41.443 43.396 42.657 40.855 40.981 43.208 Butter-production (thousand tons) 1,067. 1,122. 1,176. 1,350. 1,360. 1,320. 1,356. 1,500. 1,472. 1,409. Butter-wholesale inventories (thousand tons) 134.8 97.5 114.4 192.2 181.8 165.6 165.6 165.6 165.6 165.6 Butter-retail inventories (thousand tons) 112.3 91.2 66.1 106.3 118.0 91.4 91.4 91.4 91.4 91.4 Butter-exports (thousand tons) 73.0 24.3 16.3 17.5 18.3 20.0 16.5 17.8 17.6 17.9 Butter-imports (thousand tons) 2.2 2.2 6.2 229.7 10.9 11.6 9.6 75.7 38.9 174.2 La --.1 Butter-consumption (thousand tons) 1,192.1 1,158.3 1,174.0 1,444.2 1,351.4 1,354.3 1,349.1 1,557.9 1,493.3 1,565.3 Cheese-production (thousand tons) 478. 463. 483. 565. 562. 613. 655. 691. 701. t.....)� 536. Eggs-number per capita 159. 174. 185. 195. 205. 216. 209. 222. 232. 233. Sugar-kg per capita 38.8 39.5 38.8 40.8 41.0 40.9 41.9 42.4 42.8 42.8 Sugar-total consumption (million tons) 9.421 9.681 9.603 10.192 10.336 10.409 10.760 10.982 11.184 11.274 Sugar-used for confectioneries (million tons) 1.882 1.878 1.925 2.044 2.124 2.111 2.202 2.295 2.403 2.450 Sugar-net consumption (million tons) 7.538 7.803 7.678 8.148 8.213 8.298 8.558 8.686 8.781 8.824 Confectioneries-production (thousand tons) 2,896. 2,890. 2,961. 3,144. 3,267. 3,247. 3,387. 3,531. 3,697. 3,769. Confectioneries-index of quality (1970=100) 100.0 100.5 101.0 101.5 102.0 102.5 103.0 103.5 104.0 104.5 Confectioneries-adjusted production index 100.0 100.3 103.3 110.2 115.1 114.9 120.5 126.2 132.8 136.0 (1970=100) Tea-production (thousand tons) 272.7 280.2 291.1 305.4 329.9 352.3 375.4 434.2 453.8 480.1 Tea-net imports (thousand tons) 19.3 31.6 35.9 24.8 35.3 49.8 45.9 38.5 28.8 32.1 Tea-inventory change (thousand tons) -13.7 8.7 7.0' 17.3 13.8 14.8 15.0 15.0 15.0 15.0 Tea-consumption (thousand tons) 305.7 303.1 320.0 , . 312.9 351.4 387.3 406.3 457.7 467.6 497.2 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix B (continued) Approved for Release: 2019/07/19 C05210421 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Flour-kg per capita 149. 149. 145. 143. 142. 141. 141. 139. 140. 139. Flour-total consumption (million tons) 36.177 36.520 35.887 35.721 35.798 35.884 36.209 36.001 36.582 36.613 Flour-used in macaroni (million tons) 1.211 1.218 1.359 1.373 1.252 1.368 1.510 1.525 1.487 1.533 Flour-used in confectioneries (million tons) 1.014 1.011 1.036 1.100 1.143 1.136 1.185 1.236 1.294 1.319 Flour-net consumption (million tons) 33.952 34.290 33.493 33.248 33.403 33.380 33.513 33.240 33.801 33.760 Flour-index of quality (1970=100) 100.0 100.3 100.3 100.5 100.9 97.5 93.8 101.3 101.3 103.0 Flour-adjusted index of consumption (1970 = 100) 100.0 101.3 98.9 98.5 99.3 95.8 92.6 99.2 100.8 102.4 Macaroni-deflated retail sales (million 1970 rubles) 543. 575. 644. 602. 601. 669. 730. 707. 737. 779. Potatoes-kg per capita 130. 128. 121. 124. 121. 120. 119. 120. 117. 110. Vegetables-kg per capita 82. 85. 80. 85. 87. 89. 86. 88. 92. 96. Fruits and berries-kg per capita 35. 39. 36. 40. 37. 39. 39. 41. 41. 38. Vodka and liquor-consumption (million dekaliters) 237.9 230.7 217.1 244.4 257.7 261.4 265.1 269.6 283.7 296.0 Cognac-consumption (million dekaliters) 7.5 7.6 7.7 7.8 7.9 8.1 7.6 7.7 8.1 8.5 Rum-consumption (million dekaliters) 0.4 0.9 2.0 1.4 1.1 1.2 1.2 1.3 1.4 1.4 Wine-consumption (million dekaliters) 382.0 400.1 413.9 314.4 382.3 421.7 436.1 413.3 434.9 453.8 Champagne-consumption (million dekaliters) 6.9 7.2 7.4 7.7 7.9 8.2 8.5 8.8 9.3 9.7 Beer-consumption (million dekaliters) 421.2 443.5 472.4 511.0 543.4 575.1 597.8 626.4 659.2 687.8 Nonalcoholic beverages-consumption (million dekaliters) 259.8 267.0 275.0 283.0 291.5 300.2 309.2 318.5 335.2 . 349.7 Tobacco-deflated retail sales (million 1970 rubles) 2,780. 2,954. 3,122. 3,296. 3,441. 3,681. 3,808. 3,957. 4,127. 4,339. Approved for Release: 2019/07/19 C05210421 1980 Meat�kg per capita 57. Fish�kg per capita 17.0 Vegetable oil�kg per capita 8.6 Margarine�production (thousand tons) 1,263. Margarine�wholesale inventories (thousand tons) 49.7 Margarine�retail inventories (thousand tons) 234.7 Margarine�consumption (thousand tons) 1,263. Milk�kg per capita 314. Milk�total consumption (million tons) 83.367 Milk�used for butter (million tons) 31.030 Approved for Release: 2019/07/19 C05210421 Milk�used for cheese (million tons) Milk�net consumption (million tons) Butter�production (thousand tons) Butter�wholesale inventories (thousand tons) 8.653 43.684 1,373. 165.6 Butter�retail inventories (thousand tons) 91.4 Butter�exports (thousand tons) 17.9 Butter�imports (thousand tons) 174.2 Butter�consumption (thousand tons) 1,529.3 Cheese�production (thousand tons) 676. Eggs�number per capita 238. Sugar�kg per capita 42.2 Sugar�total consumption (million tons) 11.204 Sugar�used for confectioneries (million tons) 2.508 Sugar�net consumption (million tons) 8.696 Confectioneries�production (thousand tons) 3,859. Confectioneries�index of quality (1970=100) 105.0 Confectioneries�adjusted production index 139.9 (1970=100) Tea�production (thousand tons) 530.5 Tea�net imports (thousand tons) 40.0 Tea�inventory change (thousand tons) 10.0 Tea�consumption (thousand tons) 560.5 Flour�kg per capita 139. Flour�total consumption (million tons) 36.904 Flour�used in macaroni (million tons) 1.534 Flour�used in confectioneries (million tons) 1.351 Flour�net consumption (million tons) 34.019 Approved for Release: 2019/07/19 C05210421 Appendix B (continued) 1980 Flour�index of quality (1970=100) 103.0 Flour�adjusted index of consumption 103.2 (1970=100) Macaroni�deflated retail sales (million 1970 793. rubles) Approved for Release: 2019/07/19 C05210421 Potatoes�kg per capita 112. Vegetables�kg per capita 93. Fruits and berries�kg per capita 34. Vodka and liquor�consumption (million dekaliters) Cognac�consumption (million dekaliters) Rum�consumption (million dekaliters) Wine�consumption (million dekaliters) 285.0 Champagne�consumption (million dekaliters) Beer�consumption (million dekaliters) 650.0 Nonalcoholic beverages�consumption (million dekaliters) Tobacco�deflated retail sales (million 1970 4,521. rubles) Approved for Release: 2019/07/19 C05210421 Appendix C Data Used in the Derivation of the Index of Soft Goods Approved for Release: 2019/07/19 C05210421 L..) -4 ---11 1952 1955 1957 1950 1951 1953 1954 1956 1958 1959 Cotton textiles-retail sales (million rubles) 2,477. 2,487. 2,589. 2,753. 2,827. 2,543. 2,558. 2,324. 2,215. 2,353. Cotton textiles-price index (1940=100) 249. 243. 243. 214. 182. 176. 176. 176. 176. 176. Cotton textiles-deflated retail sales (million 1970 rubles) 1,247. 1,298. 1,351. 1,632. 1,970. 1,833. 1,844. 1,675. 1,596. 1,696. Wool textiles-retail sales (million rubles) 921. 798. 706. 814. 969. 744. 986. 1,253. 1,366. 1,380. Wool textiles-price index (1940=100) 190. 185. 184. 176. 174. 173. 173. 173. 173. 173. Wool textiles-deflated retail sales (million 1970 rubles) 564. 502. 447. 538. 648. 581. 663. 843. 919. 928. Silk textiles-retail sales (million rubles) 446. 538. 657. 860. 1,143. 1,162. 1,416. 1,754. 1,808. 1,735. Silk textiles-price index (1970=100) 186. 184. 184. 176. 171. 170. 169. 168. 168. 168. Silk textiles-deflated retail sales (million 1970 rubles) 225. 275. 336. 459. 628. 643. 788. 982. 1,612. 971. Linen textiles-retail sales (million rubles) 136. 127. 119. 111. 118. 117. 159. 207. 230. 235. Linen textiles-price index (1970=100) 127.6 127.1 126.6 125.8 125.0 116.0 116.0 116.0 115.3 115.3 Linen textiles-deflated retail sales (million 1970 rubles) 80. 75. 70. 66. 70. 75. 102. 133. 149. 152. Sewn goods-production index (1970=100) 19.5 22.2 24.9 27.8 33.1 36.6 40.3 40.7 44.5 49.2 Hosiery-production (million pair) 472.7 597.8 584.9 611.9 674.8 772.2 803.2 844.7 887.7 926.1 Leather shoes-production (million pair) 203.0 248.1 241.2 237.5 255.5 271.2 287.0 317.3 356.4 389.9 Leather shoes-wholesale inventory change (million pair) 1.0 1.0 1.0 1.0 1.0 1.0 0.5 -1.3 1.4 1.5 Leather shoes-retail inventory change (million pair) 1.0 1.0 1.0 1.0 1.0 1.0 1.6 0.7 9.1 17.0 Leather shoes-net imports (million pair) 6.6 4.4 3.0 2.0 1.3 0.9 11.4 11.8 24.5 26.1 Leather shoes-consumption (million pair) 207.6 250.5 242.2 237.5 254.8 270.1 296.3 329.7 370.4 397.5 Rubber footwear-production (million pair) 110.8 115.9 121.2 126.8 132.6 138.6 145.0 150.7 159.2 167.4 Felt footwear-production (million pair) 22.4 22.9 23.3 23.8 24.1 24.5 24.2 26.4 28.6 31.1 Knit underwear-production (million units) 150.4 198.3 234.9 274.7 327.1 346.5 348.5 374.7 398.1 399.3 Knit outerwear-production (million units) 47.1 58.9 63.5 66.0 75.5 85.2 85.4 90.2 97.1 97.2 Haberdashery-retail sales (million rubles) 640. 684. 741. 813. 943. 1,035. 1,150. 1,381. 1,523. 1,643. Haberdashery-price index (1940=100) 153. 150. 149. 137. 133. 133. 133. 132. 132. 132. Haberdashery-deflated retail sales (million 1970 rubles) 505. 551. 601. 717. 857. 940. 1,045. 1,264. 1,394. 1,504. Approved for Release: 2019/07/19 C05210421 Appendix C (continued) Approved for Release: 2019/07/19 C05210421 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 School and office supplies-retail sales (million rubles) 199. 217. 243. 260. 273. 275. 307. 337. 363. 392. School and office supplies-price index (1940=100) 138. 134. .134. 121. 107. 104. 104. 104. 104. 104. School and office supplies-deflated retail sales (million 1970 rubles) 113. 126. 142. 168. 199. 206. 230. 253. 272. 294. Publications-retail sales (million rubles) 316. 332. 348. 378. 411. 466. 524. 581. 641. 715. Household soap-retail sales (million rubles) 294. 289. 273. 263. 280. 263. 290. 306. 326. 328. Household soap-price index (1970=100) 182.3 161.5 143.0 123.3 106.3 103.3 103.1 103.4 103.4 103.1 Household soap-deflated retail sales (million 1970 rubles) 151. 167. 178. 199. 246. 238. 263. 276. 294. 297. Toilet soap-retail sales (million rubles) , 320. 312. 352. 373. 389. 449. 483. 514. Toilet soap-price index (1970=100) 202.5 159.2 - 106.2 101.3 101.3 100.9 101.3 101.3 Toilet soap-deflated retail sales (million 1970 rubles) 153. 170. 190. 247. 321. 357. 372. 431. 462. 492. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 1964 1965 1966 1960 1961 1962 1963 1967 1968 1969 Cotton textiles-retail sales (million rubles) 2,380. 2,130. 2,036. 1,950. 1,911. 1,871. 1,914. 1,993. 1,985. 1,963. Cotton textiles-price index (1940=100) 176. 176. 176. 176. 176. 175' i 170. 170. 170. 170. Cotton textiles-deflated retail sales (million 1970 rubles) 1,715. 1,535. 1,467. 1,405. 1,377. 1,356. 1,428. 1,487. 1,481. 1,465. Wool textiles-retail sales (million rubles) 1,630. 1,488. 1,356. 1,233. 1,220. 1,330. 1,307. 1,316. 1,389. 1,403. Wool textiles-price index (1940=100) 173. 170. 170. 170. 170. 160. 156. 156. 156. 156. Wool textiles--deflated retail sales (million 1970 rubles) 1,097. 1,019. 928. 844. 835. 968. 975. 982. 1,036. 1,047. Silk textiles-retail sales (million rubles) 1,718. 1,597. 1,622. 1,559. 1,487. 1,542. 1,589. 1,634. 1,557. 1,499. Silk textiles-price index (1940=100) 161. 156. 149. 144. 144. 132. 126. 126. 126. 126. Silk textiles-deflated retail sales (million 1970 rubles) 1,003. 962. 1,023. 1,018. 971. 1,098. 1,186. 1,219. 1,162. 1,118. Linen textiles-retail sales (million rubles) 254. 243. 217. 210. 212. 240. 271. 290. 321. 334. Linen textiles-price index (1970=100) 115.4 115.4 115.4 115.9 115.9 104.7 100.0 100.0 100.0 100.1 Linen textiles-deflated retail sales (million 1970 rubles) 164. 157. 140. 135. 136. 171. 202. 216. 239. 249. Sewn goods-production index (1970=100) 53.0 56.6 58.7 57.5 56.2 56.1 61.6 70.6 81.2 90.6 Hosiery-production (million pair) 964.1 1,000.5 1,032.8 1.121.6 1,236.0 1,350.0 1,444.3 1,485.9 1,466.4 1,395.9 Leather shoes-production (million pair) 419.3 443.2 456.3 462.7 474.7 486.0 523.2 563.2 600.0 638.4 -Leather shoes-wholesale inventory change (million pair) 5.4 1.5 1.5 2.9 0.1 -3.2 -1.0 1.9 -0.2 3.1 Leather shoes-retail inventory change (million pair) 17.3 13.1 1.8 9.2 4.4 -12.8 -10.1 6.7 11.6 21.1 Leather shoes-net imports (million pair) 29.7 25.1 25.2 25.6 25.1 27.9 33.7 48.9 54.6 56.2 Leather shoes-consumption (million pair) 426.3 453.7 478.2 476.2 495.3 529.9 568.0 603.5 643.2 670.4 Rubber footwear-production (million pair) 166.2 163.6 157.2 159.6 164.7 161.0 164.2 168.2 168.6 167.8 Felt footwear-production (million pair) 31.5 33.4 33.8 34.3 34.3 33.3 32.6 32.2 32.4 31.8 Knit underwear-production (million units) 471.6 487.7 519.4 554.5 639.8 714.8 770.4 811.8 825.0 821.6 Knit outerwear-production (million units) 111.7 117.8 124.9 132.9 153.4 187.9 222.1 255.4 302.7 363.4 Haberdashery-retail sales (million rubles) 1,724. 1,830. 1,982. 2,009. 2,077. 2,281. 2,500. 2,686. 2,967. 3,284. Haberdashery-price index (1940=100) 123. 122. 122. 122. 122. 121. 121. 121. 121. 121. Haberdashery-deflated retail sales (million 1970 rubles) 1,694. 1,813. 1,963. 1,990. 2,057. 2,278. 2,497. 2,682. 2,963. 3,279. Approved for Release: 2019/07/19 C05210421 Appendix C (continued) Approved for Release: 2019/07/19 C05210421 t....) oo 0 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 School and office supplies-retail sales (million rubles) 424. 436. 453. 476. 539. 592. 656. 721. 827. 956. School and office supplies-price index (1940=100) 103. 102. 102. 102. 102. 102. 102. 102. 102. 102. School and office supplies-deflated retail sales (million 1970 rubles) 321. 334. 347. 364. 412. 453. 502. 552. 633. 732. Publications-retail sales (million rubles) 759. 794. 832. 894. 947. 1,078. 1,197. 1,312. 1,385. 1,550. Household soap-retail sales (million rubles) 351. 368. 380. 423. 433. 487. 533. 602. 655. 674. Household soap-price index (1970=100) 100.1 100.7 100.7 100.6 100.6 100.6 100.6 100.7 100.6 100.8 Household soap-deflated retail sales (million 1970 rubles) 328. 341. 352. 393. 402. 452. 495. 558. 608. 625. Toilet soap-retail sales (million rubles) 535. 566. 605. 613. 658. 716. 792. 880. 965. 1,069. Toilet soap-price index (1970=100) 98.9 99.9 99.5 100.0 99.5 100.0 100.0 99.9 99.7 100.1 Toilet soap-deflated retail sales (million 1970 rubles) 525. 549. 589. 594. 641. 694. 768. 854. 939. 1,035. Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Cotton textiles-retail sales (million rubles) 1,822. 1,763. 1,679. 1,755. 1,604. 1,568. 1,604. 1,578. 1,601. 1,723. Cotton textiles-price index (1940=100) 170. 170. 170. 170. 170. 170. 170. 170. 170. 170. Cotton textiles-deflated retail sales (million 1970 rubles) 1,359. 1,315. 1,253. 1,309. 1,197. 1,170. 1,197. 1,177. 1,195. 1,286. Wool textiles-retail sales (million rubles) 1,345. 1,389. 1,565. 1,710. 1,880. 2,056. 2,035. 1,980. 2,195. 2,321. Wool textiles-price index (1940=100) 156. 156. 156. 156. 156. 156. 156. 156. 156. 156. Wool textiles-deflated retail sales (million 1970 rubles) 1,004. 1,036. ,1,168. 1,276. 1,403. 1,534. 1,518. 1,477. 1,638. 1,732. Silk textiles-retail sales (million rubles) 1,530. 1,504. 1,752. 1,881. 1,990. 2,797. 3,171. 3,247. 2,833. 3,076. Silk texiiles-price index (1940=100) 126. 126. 126. 126. 126. 126. 126. 128. 128. 128. Silk textiles-deflated retail sales (million 1970 rubles) 1,142., 1,122. 1,307. 1,403. 1,485. 2,087. 2,366. 2,385. 2,081. 2,259. Linen textiles-retail sales (million rubles) 329. 349. 365. 364. 360. 327. 345. 379. 396. 357. Linen textiles-price index (1970=100) 100.0 100.1 100.1 100.2 100.0 99.9 100.4 100.7 100.8 101.0 Linen textiles-deflated retail sales (million 1970 rubles) 245. 260. 272. 271. 269. 244. 256. 281. 293. 264. Sewn goods-production index (1970=100) 100.0 106.2 107.5 109.4 112.5 118.7 125.7 130.8 135.9 141.6 Hosiery-production (million pair) 1,338.1 1,309.1 1,336.9 1,411.0 1,469.0 1,495.0 1,540.0 1,564.0 1,596.0 1,636.0 Leather shoes-production (million pair) 678.9 681.9 647.4 666.2 684.0 698.0 724.0 736.0 740.0 740.0 Leather shoes-wholesale inventory change (million pair) 5.2 7.1 -2.0 0.4 -1.1 2.9 Leather shoes-retail inventory change (million pair) 18.1 21.6 0.2 6.8 1.4 8.4 10.0 Leather shoes-net imports (million pair) 59.7 62.2 59.6 59.3 63.9 67.6 67.7 69.0 66.8 61.6 Leather shoes-consumption (million pair) 715.3 715.4 708.8 718.3 747.6 754.3 781.7 805.0 806.8 801.6 Rubber footwear-production (million pair) 173.0 179.0 180.0 194.0 205.0 205.0 203.0 197.0 195.0 194.0 Felt footwear-production (million pair) 31.8 31.5 30.9 30.8 30.5 30.1 29.2 28.6 27.8 26.3 Knit underwear-production (million units) 814.4 828.8 842.9 900.4 920.0 955.0 990.0 1,038.0 1,080.0 1,111.0 Knit outerwear-production (million units) 415.2 445.4 450.9 459.7 469.0 466.0 472.0 474.0 474.0 478.0 Haberdashery-retail sales (million rubles) 3,638. 4,031. 4,410. 4,557. 4,785. 5,197. 5,537. 5,975. 6,231. 6,637. Haberdashery-price index (1940=100) 121. 121. 121. 121. 121. 121. 121. 121. 121. 121. Haberdashery-deflated retail sales (million 1970 rubles) 3,633. 4,025. 4,404. 4,551. 4,778. 5,190. 5,529. 5,967. 6,222. 6,628. Approved for Release: 2019/07/19 C05210421 Appendix C (continued) Approved for Release: 2019/07/19 C05210421 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 School and office supplies-retail sales (million rubles) 1,015. 1,032. 1,125. 1,170. 1,238. 1,316. 1,365. 1,456. 1,513. 1,595. School and office supplies-price index (1940=100) 95. 87. 86. 86. 84. 84. 84. 84. 84. 84. School and office supplies-deflated retail sales (million 1970 rubles) 834. 926. 1,021. 1,062. 1,150. 1,223. 1,268. 1,353. 1,406. 1,482. Publications-retail sales (million rubles) 1,640. 1,738. 1,845. 1,947. 2,050. 2,197. 2,294. 2,223. 2,374. 2,546. Household soap-retail sales (million rubles) 697. 753. 827. 820. 857. 946. 940. 974. 1,008. 1,153. Household soap-price index (1970=100) 100.0 99.5 99.2 99.2 99.3 99.3 99.3 99.3 97.8 97.0 Household soap-deflated retail sales (million 1970 rubles) 651. 707. 779. 772. 806. 890. 884. 916. 963. 1,110. Toilet soap-retail sales (million rubles) 1,176. 1,292. 1,411. 1,520. 1,632. 1,807. 1,983. 2,199. 2,529. 2,844. Toilet soap-price index (1970=100) 100.0 100.0 99.8 99.9 100.0 99.4 99.3 99.5 99.9 99. Toilet soap-deflated retail sales (million 1970 rubles) 1,140. 1,253. 1,371. 1,475. 1,582. 1,762. 1,937. 2,143. 2,453. 2,774. Approved for Release: 2019/07/19 C05210421 1980 Approved for Release: 2019/07/19 C05210421 Cotton textiles--retail sales (million rubles) Cotton textiles�price index (1940=100) Cotton textiles�deflated retail sales (million 1970 rubles) 1,723 170 1,286 Wool textiles�retail sales (million rubles) 2,294 Wool textiles�price index (1940=100) 156 Wool textiles�deflated retail sales 1,712 (million 1970 rubles) Silk textiles�retail sales (million rubles) 3,636 Silk textiles�price index (1940=100) 128 Silk textiles�deflated retail sales 2,671 (million 1970 rubles) Linen textiles�retail sales (million rubles) 363 Linen textiles�price index (1970=100) 100.8 Linen textiles�deflated retail sales 269 (million 1970 rubles) Sewn goods�production index (1970=100) 149.9 Hosiery�production (million pair) 1,666.0 Leather shoes�production (million pair) 744.0 Leather shoes�wholesale inventory change 0.0 (million pair) Leather shoes�retail inventory change 0.0 (million pair) Leather shoes�net imports (million pair) Leather shoes�consumption (million pair) 70.0 814.0 Rubber footwear�production (million pair) Felt footwear�production (million pair) 194.0 25.0 Knit underwear�production (million units) 1,144.0 Knit outerwear�production (million units) 478.0 Haberdashery�retail sales (million rubles) 7,057. Haberdashery�price index (1940=100) 121. Haberdashery�deflated retail sales 7,047. (million 1970 rubles) Approved for Release: 2019/07/19 C05210421 Appendix C (continued) 1980 School and office supplies�retail sales 1,674 1million rubles) School and office supplies�price index 84 (1940=100) School and office supplies�deflated retail sales 1,556.0 (million 1970 rubles) Approved for Release: 2019/07/19 C05210421 Publications�retail sales (million rubles) 2,717.0 Household soap�retail sales (million rubles) 1,227 Household soap�price index (1970=100) 96.9 Household soap�deflated retail sales 1,183 (million 1970 rubles) Toilet soap�retail sales (million rubles) 3,124 Toilet soap�price index (1970=100) 99.7 Toilet soap�deflated retail sales 3,038 (million 1970 rubles) Approved for Release: 2019/07/19 C05210421 Appendix D Data Used in the Derivation of the Index of Durables and Miscellaneous Goods Approved for Release: 2019/07/19 C05210421 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 Nonfood goods-retail sales (million rubles) 14,960. 15,517. 16,807. 19,194. 21,794. 22,660. 24,807. 28,721. 30,762. 32,661. Nonfood goods-price index (1940=100) 165. 157. 156. 145. 134. 134. 133. 133. 133. 132. Nonfood goods-retail sales (million 1970 rubles) 11,243. 12,255. 13,359. 16,414. 20,168. 20,969. 23,128. 26,777. 28,680. 30,682. Soft goods-retail sales (million rubles) 11,931. 12,029. 13,190. 14,372. 16,508. 16,601. 18,395. 20,978. 22,241. 23,503. Soft goods-price index (1970=100) 133. 126. 128. 116. 110. 108. 108. 108. 108. 108. Soft goods-retail sales (million 1970 rubles) , 8,947. 9,584. 10,306. 12,428. 15,074 15,402. 17,039. 19,401. 20,574. 21,833. Durables and miscellaneous goods (million 1970 rubles) 2,295. 2,672. 3,053. 3,986. 5,094. 5,567. 6,089. 7,377. 8,107. 8,848. 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Nonfood goods-retail sales (million rubles) 35,800. 36,216. 38,242. 38,596. 40,322. 44,310. 48,101. 53,165. 58,693. 63,742. Nonfood goods-price index (1940=100) 130. 129. 129. 129. 128. 126. 124. 124. 124. 124. Nonfood goods-retail sales (million 1970 rubles) 34,148. 34,812. 36,760. 37,100. 39,062. 43,607. 48,101. 53,165. 58,693. 63,742. Soft goods-retail sales (million rubles) 25,708. 25,988. 27,411. 27,687. 28,615. 31,168. 33,720. 37,563. 41,386. 44,967. Soft goods-price index (1970=100) 107. 106. 105. 105. 105. 102. 101. 101. 101. 100. Soft goods-retail sales (million 1970 Rubles) 24,135. 24,630. 26,062. 26,441. 27,345. 30,574. 33,524. 37,336. 41,133\ 44,794. Durables and miscellaneous goods (million 1970 rubles) 10,012. 10.182. 10,697 10,659. 11,717. 13,033. 14,577. 15,829. 17,560. 18,948. - 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 Nonfood goods-retail sales (million rubles) 69,040. 74,117. 79,921. 84,500. 90,043. 97,660. 103,037. 109,378. 115,456. 122,932. Nonfood goods-price index (1940=100) 124. 123. 122. 122. 122. 122. 122. 122. 123. 125. Nonfood goods-retail sales (million 1970 rubles) 69,040. 74,720. 81,231. 85,885. 91,519. 99,261. 104,726. 111,171. 116,395. 121,949. Soft goods-retail sales (million rubles) 47,872. 50,539. 53,317. 55,416. 58,186. 62,709. 65,776. 69,099. 72,006. 75,870. Soft goods-price index (1970=100) 100. 100. 100. 99. 99. 99. 99. 99. 99. 99. Soft goods-retail sales (million 1970 rubles) 47,872. 50,696. 53,500. 27,731. 55,811. 58,920. 63,503. 66,603. 69,534. 72,994. 76,751. Durables and miscellaneous goods (million 1970 rubles) 21,168. 24,024. 30,074. 32,599. 35,758. 38,124. 41,637. 43,401. 45,197. 1980 Nonfood goods-retail sales (million rubles) 131,033. Nonfood goods-price index (1940=100) 125. Nonfood goods-retail sales (million 1970 rubles) 129,985. Soft goods-retail sales (million rubles) 80,794. Soft goods-price index (1970=100) 99. Soft goods-retail sales (million 1970 rubles) 81,735. Durables and miscellaneous goods (million 1970 rubles) 48,250. Approved for Release: 2019/07/19 C05210421 Appendix E Data Used in the Derivation of the Index of Household Services Approved for Release: 2019/07/19 C05210421 1955 1950 1951 1952 1953 1954 1956 1957 � 1958 1959 Housing Urban housing Endyear stock-useful space (million square meters) 513.0 535.1 557.0 593.9 632.6 672.0 711.0 763.5 832.0 896.0 Endyear stock-living space (million square meters) 342.0 356.7 371.3 395.9 421.7 448.0 474.0 509.0 554.7 597.3 Midyear stock-living space (million square meters) 336.0 349.4 364.0 383.6 408.8 434.9 461.0 491.5 531.8 576.0 Rural housing Endyear stock-useful space (million square meters) 725.9 739.8 752.4 754.2 759.8 769.1 784.4 808.4 831.8 872.0 Construction (million square meters) 19.7 20.0 18.9 20.0 23.9 27.9 32.0 45.9 48.2 55.7 Transfers of rural housing to urban housing (million square meters) 0.0 2.5 2.6 14.4 14.6 14.8 12.8 18.0 20.8 11.3 Retirements (million square meters) 0.0 3.6 3.7 3.8 3.8 3.8 3.8 3.9 4.0 4.2 Endyear stock-living space (million square meters) 544.5 554.9 564.3 565.7 569.8 576.8 588.3 606.3 623.8 654.0 Midyear stock-living space (million square meters) 540.0 549.7 559.6 565.0 567.8 573.3 582.6 597.3 615.1 638.9 Total housing Midyear stock-living space (million square meters) 876.0 899.0 923.6 948.6 976.6 1,008.2 1,043.6 1,088.8 1,146.9 1,214.9 Utilities Household use of electricity (billion kilowatt-hours) 9.251 10.112 11.078 11.928 12.749 13.686 14.603 15.096 15.955 16.859 Household use of natural gas (billion cubic meters) 0.216 0.234 0.239 0.258 0.282 0.337 0.453 0.697 1.053 1.327 Urban public housing Midyear stock-living space (million square meters) 222.7 231.4 242.7 252.4 262.7 273.0 284.3 299.4 320.8 347.0 Repair and personal care State-provided services RSFSR sales (million 1955 rubles) 443.2 398.8 384.1 494.7 RSFSR sales (million rubles) . 392.5 609.8 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 State-provided services (continued) � USSR sales-constant prices (million rubles) USSR sales current prices (million rubles) USSR sales-comparable prices (million rubles) USSR sales (million 1976 rubles) Privately-provided services Total sales (million rubles) 3,268. 3,268. 3,268. 3,268. 3,268. 3,268. 3,268. 3,268. 3,268. 3,268. Housing services (million rubles) 1,387. 1,387. 1,387. 1,387. 1,387. 1,387. 1,387. 1,387. 1,387. 1,387. Recreation Movie admissions (million) 1,144. 1,360. 1,562. 1,625. 1,967. 2,505. 2,824. 3,065. 3,392. 3,512. Theater admissions (million) 68. 69. 70. 71. 77. 78. 77. 79. 83. 89. Resort visitors (thousand) 3,745. 3,884. 4,102. 4,299. 4,505. 4,866. 4,859. 4,991. 5,564. 5,780. Hotel employment (thousand) 53. 51. 50. 53. 55. 58. 57. 57. 57. 58. Hotel employment (million manhours) 115. 110. 108. 114. 118. 124. 119. 116. 115. 114. Transportation Rail (billion passenger-kilometers) 88.0 98.5 107.4 118.3 129.1 141.4 142.4 153.4 158.4 164.4 Sea (billion passenger-miles) 671.0 679.0 672.0 800.0 783.0 798.0 748.0 764.0 739.0 756.0 River (billion passenger-kilometers) 2.7 2.9 3.0 3.3 3.5 3.6 3.5 3.8 4.0 4.1 Bus (billion passenger-kilometers) 5.2 6.5 8.4 10.5 14.1 20.9 26.4 33.7 42.6 50.8 Air (billion passenger-kilometers) 1.2 1.5 1.7 2.1 2.4 2.8 3.1 4.5 6.4 9.1 Tram (million passengers) 5,157.0 5,379.7 5,612.0 5,853.2 6,104.7 6,367.0 6,416.0 6,812.0 7,195.0 7,450.0 Trolleybus (million passengers) 945.0 1,077.7 1,229.0 1,410.5 1,618.9 1,858.0 2,082.0 2,392.0 2,672.0 2,805.0 Subway (million passengers) 629.0 681.8 739.0 799.9 865.7 937.0 996.0 1,015.0 1,068.0 1,093.0 'Taxi (million paid kilometers) 160.1 210.9 277.9 323.5 424.8 600.3 739.0 978.1 1,148.1 1,275.1 Communications 13,459.4 15,604.0 Postal-number of items (million) 8,732.2 9,856.0 10,885.0 11,471.0 12,533.5 14,695.0 16,486.8 17,623.6 Telephone-long distance calls (million) 103.4 108.0 115.0 119.0 126.0 135.2 143.1 152.0 3,145.0 413.0 163.1 3,360.0 171.7 Telephone-urban telephones (thousand) 2,092.0 2,231.0 2,422.0 2,548.0 2,698.0 2,839.0 2,983.0 383.0 3,520.0 Telephone-rural telephones (thousand) 221.0 244.0 264.0 289.0 326.0 351.0 450.0 503.0 Telegraph-number'of telegrams (million) 153.9 167.0 181.0 195.0 201.0 10.0 0.4 16.4 203.2 13.0 0.8 19.5 206.2 16.2 1.3 22.2 227.0 19.1 1.8 24.8 223.2 230.0 Radio and TV-number of radios (million) 3.6 4.8 5.8 0.1 11.7 7.3 0.2 13.8 21.7 2.5 27.1 24.7 Radio and TV-number of TV sets (million) 0.0 0.1 3.6 29.2 Radio and TV-number of radio relay facilities (million) 9.7 10.6 Approved for Release: 2019/07/19 C05210421 Appendix E (continued) Approved for Release: 2019/07/19 C05210421 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Housing Urban housing Endyear stock-useful space (million square meters) 612.0 1,017.0 1,074.0 1,130.0 1,182.0 1,238.0 1,290.0 1,350.0 1,410.0 1,469.0 Endyear stock-living space (million square meters) 638.7 678.0 716.0 753.3 788.0 825.3 860.0 900.0 940.0 979.3 Midyear stock-living space (million square meters) 618.0 658.3 697.0 734.7 770.7 806.7 842.7 880.0 920.0 959.7 Rural housing Endyear stock-useful space (million square meters) 907.0 936.7 962.1 984.8 1,003.6 1,020.6 1,041.1 1,059.7 1,073.9 1,088.4 Construction (million square meters) 50.6 46.6 41.1 39.2 35.2 36.9 38.7 38.4 36.0 35.2 Transfers of rural housing to urban housing (million square meters) 9.1 7.8 5.4 5.0 3.6 5.9 2.9 3.1 3.8 1.4 Retirements (million square meters) 6.5 9.1 10.3 11.5 12.8 14.1 15.3 16.7 18.0 19.7 Endyear stock-living space (million square meters 680.2 702.5 721.6 738.6 752.7 765.4 780.8 794.8 805.5 816.3 Midyear stock-living space (million square meters) 667.1 691.4 712.0 730.1 745.6 759.1 773.1 787.8 800.1 810.9 Total housing Midyear stock-living space (million square meters) 1,285.1 1,349.7 1,409.0 1,464.7 1,516.3 1,565.7 1,615.8 1,667.8 1,720.1 1,770.6 Utilities Household use of electricity (billion kilowatt-hours) 17.358 19.333 21.652 24.025 26.559 29.133 31.105 33.347 35.997 38.576 Household use of natural gas (billion cubic meters) 1.800 2.212 2.757 3.369 4.071 4.787 5.361 5.500 6.000 6.800 Urban public housing 586.7 Midyear stock-living space (million square meters) 374.7 403.0 432.0 462.0 491.7 521.7 553.3 621.7 657.7 - Repair and personal care State-provided services RSFSR sales (million 1955 rubles) RSFSR sales (million rubles) 676.1 719.5 861.4 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 State-provided services (continued) USSR sales-constant prices 1,054.2 1,158.2 1,277.3 1,413.7 1,677.3 2,038.3 2,375.0 2,827.3 - (Million rubles) USSR sales current prices (million rubles) 1,375.6 - 2,357.5 2,688.9 3,108.3 3,544.4 4,045.0 USSR sales-comparable prices (million rubles) 2,346.9 2,670.5 3,079.7 3,503.4 3,988.8 USSR sales (million 1976 rubles) Privately-provided services Total sales (million rubles) 2,716. 2,284. 2,062. 1,997. 2,069. 2,056. 2,170. 2,111. 2,036. 1,859. Housing services (million rubles) 1,040. 928. 857. 867. 973. 1,006. 1,081. 1,040. 979. 952. Recreation Movie admissions (Onion) 3,611. 3,859. 3,926. 3,877. 4,123. 4,279. 4,192. 4,495. 4,705. 4,656. Theater admissions (million) 91. 94. 98. 101. 102. 101. 106. 106. III. 110. Resort visitors (thousand) 6,182. 6,153. 6,492. 6,609. 7,881. 8,310. 8,748. 9,098. 9,417. 9,831. Hotel employment (thousand) 63. 66. 67. 70. 73. 76. 78. 82. 85. 88. Hotel employment (million manhours) 119. 120. 121. 127. 133. 137. 141. 149. 155. 161. Transportation ._ Rail (billion passenger-kilometers) 170.8 176.3 189.3 192.0 195.1 201.6 219.4 234.4 254.1 261.3 Sea (billion passenger-miles) 719.0 737.0 717.0 782.0 719.0 796.0 887.0 897.0 952.0 942.0 River (billion passenger-kilometers) 4.3 4.4 4.6 4.7 4.7 4.9 5.2 5.3 5.5 5.5 Bus (billion passenger-kilometers) 61.0 69.3 82.2 95.2 107.7 120.5 137.0 153.0 168.5 183.0 Air (billion passenger-kilometers) 12.1 16.4 201 25.3 10.9 38.1 45.1 53.5 62.1 71.5 Tram (million passengers) 7,842.1 7,780.0 7,937.0 8,103.0 8,221.0 8,241.8 8,192.6 8,130.6 7,971.3 7,831.5 Trolleybus (million passengers) 3,054.6 3,139.0 3,353.0 3,638.0 3,947.0 4,298.0 4,712.8 5,039.3 5,330.6 5,689.4 Subway (million passengers) 1,148.3 1,233.0 1,301.0 1,441.0 1,569.0 1,652.4 1,822.2 1,947.3 2,072.0 2,176.2 Taxi (million paid kilometers) 1,576.0 2,038.0 2,569.3 3,012.0 3185.0 3,515.0 3,832.7 4,258.9 4,835.6 5,402.9 Communications Postal-number of items (million) 18,991.3 20,071.4 21,301.7 23,109.4 25,598.3 28,461.9 31,837.9 35,358.9 37,225.3 39,842.8 Telephone-long distance calls (million) 185.0 196.9 210.0 218.2 226.9 256.5 283.0 313.9 342.8 385.7 Telephone-urban telephones (thousand) 3,753.0 4,021.0 4,350.0 4,475.0 4,864.0 5,490.0 6,129.0 _ 6,867.0 7,677.0 8,570.0 Telephone-rural telephones (thousand) 548.0 598.0 650.0 814.0 893.0 909.0 986.0 1,075.0 1,192.0 1,324.0 Telegraph-number of telegrams (million) 240.9 245.0 252.2 254.5 257.3 273.2 299.8 322.8 338.6 356.9 Radio and TV-number of radios 30.5 32.8 35.2 36.7 38.2 39.8 41.8 44.5 46.7 (million) 27.8 Radio and TV-number of TV sets (million) 4.8 6.5 8.3 10.5 12.8 15.7 19.0 22.7 26.8 30.7 Radio and TV-number of radio relay facilities (million) 30.8 32.1 33.1 33.8 34.6 35.6 37.0 38.9 41.0 43.4 Approved for Release: 2019/07/19 C05210421 Appendix E (continued) Approved for Release: 2019/07/19 C05210421 1970 1971 1972 1973 1974 1974 1976 1977 1978 1979 Housing Urban housing Endyear stock-useful space (million square meters) 1,529.0 1,594.0 1,661.0 1,730.0 1,800.0 1,867.0 1,932.0 2,001.0 2,070.0 2,134.0 Endyear stock-living space (million square meters) 1,019.3 1,062.7 1,107.3 1,153.3 1,200.0 1,244.7 1,288.0 1,334.0 1,380.0 1,422.7 Midye.ar stock-living space (million square meters) 999.3 1,041.0 1,085.0 1,130.3 1,176.7 1,222.3 1,266.3 1,311.0 1,357.0 1,401.3 Rural Housing Endyear stock-useful space , (million square meters) 1,100.9 1,110.8 1,119.2 1,127.1 1,134.2 1,143.2 1,148.6 1,154.5 1,158.7 1,163.4 Construction (million square meters) 34.7 34.7 33.2 32.9 33.0 33.6 30.3 30.6 30.2 29.4 Transfers of rural housing to urban housing (million square meters 1.6 2.8 2.5 2.7 3.3 1.9 2.1 1.7 2.9 1.6 Retirements (million square meters) 20.7 22.0 22.2 22.4 22.5 22.7 22.9 23.0 23.1 23.2 Endyear stock-living space (million square meters 825.7 833.1 839.4 845.3 850.6 857.4 861.4 865.9 869.0 872.5 Midyear stock-living space (million square meters) 821.0 829.4 836.3 842.4 848.0 854.0 859.4 863.7 867.5 870.8 Total housing Midyear stock-living space (million square meters) 1,820.3 1,870.4 1,921.3 1,972.7 2,024.6 2,076.3 2,125.7 2,174.7 2,224.5 2,272.1 Utilities Household use of electricity (billion kilowatt-hours) 41.200 44.327 47.298 50.249 53.391 56.600 60.568 62.675 65.499 67.477 Household use of natural gas (billion cubic meters) 7.400 8.000 8.900 9.800 10.700 11.600 12.500 12.975 13.957 15.247 Urban public housing Midyear stock-living space (million square meters) 695.3 734.7 775.0 816.7 859.7 902.3 943.7 985.3 1,028.0 1,069.3 Repair and personal Care State-provided services RSFSR sales (million 1955 rubles) RSFSR sales (million rubles) Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 State-provided services (continued) USSR sales-constant prices (million rubles) USSR sales-current prices (million rubles) 4,480.7 4,838.8 5,159.6 USSR sales-comparable prices (million rubles) 4,408.1 4,750.0 5,144.9 5,579.6 6,011.6 6,433.9 6,817.8 USSR sales (million 1976 rubles) 6,243.2 6,666.5 7,039.7 7,607.1 8,199. Privately-provided services Total sales (million rubles) 2,000. 2,000. 2,000. 2,000. 2,000. 2,000. 2,000. 2,000. 2,000. 2,000. Housing services (million rubles) 1,071. 1,071. 1,071. 1,071. 1,071. 1,071. 1,071. 1,071. 1,071. 1,071. Recreation Movie admissions (million) 4,652. 4,656. 4,569. 4,583. 4,567. 4,497. 4,211. 4,080. 4,155. 4,151. Theater admissions (million) 111. 114. 114. 115. 116. 117. 117. 116. 118. 119. Resort visitors (thousand) 10,138. 10,594. 11,069. 11,517. 11,882. 12,344. 12,875. 13,373. 13,682. 14,154. Hotel employment (thousand) 92. 96. 101. 106. 110. 114. 117. 127. 127. 131. Hotel employment (million manhours) 167. 177. 185. 192. 200. 208. 213. 220. 230. 237. Transportation Rail (billion passenger-kilometers) 265.4 274.6 285.8 296.6 306.3 312.5 315.1 322.2 332.1 335.3 Sea (billion passenger-miles) 859.0 928.0 1,012.0 1,048.0 1.127.0 1.153.0 1,106.0 1,475.0 1,/65.0 1,326.0 River (billion passenger-kilometers) 5.4 5.7 5.7 5.9 6.1 6.3 6.0 5.6 5.8 5.8 Bus (billion passenger-kilometers) 202.5 215.8 235.6 253.9 279.1 303.6 325.3 344.5 361.5 376.0 Air (billion passenger-kilometers) 78.2 88.8 , 95.9 98.8 108.8 122.6 130.8 127.5 140.1 151.0 Tram (million passengers) 7,962.1 7,975.1 7,951.7 7,997.5 8,074.2 8,235.4 8,358.0 8,371.5 8,384.1 8,296.4 Trolleybus (million passengers) 6,122.2 6,587.8 6,973.9 7,298.3 7,638.5 7,963.3 8,355.0 8,634.1 8,810.8 8,945.4 Subway (million passengers) 2,294.4 2,443.3 2,591.7 2,727.0 2,836.3 2,972.0 3,228.6 3,355.6 3,515.0 3,675.3 Taxi (million paid kilometers) 5,951.0 6,570.4 7,179.5 7,694.7 8,443.9 9,291.1 10,097.0 6,870.0 6,395.0 7,239.0 Communications Postal-number of items (million) 42,092.7 44,288.0 46,298.0 47,872.0 49,280.0 51,008.0 51,661.0 52,174.0 52,385.0 53,296.0 Telephone-long distance calls (million) 430.5 479.0 535.0 604.0 684.0 768.0 868.0 960.0 1,061.0 1,160.0 Telephone-urban telephones (thousand) 9,504.0 10,436.0 11,380.0 12,450.0 13,589.0 14,694.0 15,712.0 16,690.0 17,752.0 18,855.0 Telephone-rural telephones (thousand) 1,483.0 1,642.0 1,819.0 2,013.0 2,236.0 2,473.0 2,710.0 2,948.0 3,192.0 3,440.0 Telegraph-number of telegrams (million) 364.6 372.0 385.0 404.0 421.0 443.0 458.0 477.0 491.0 511.0 Radio and TV-number of radios (million) 48.6 50.8 53.2 54.8 57.1 59.8 61.5 63.3 64.7 66.2 Radio and TV-number of TV sets (million) 34.8 39.3 45.4 49.2 52.5 55.2 57.6 59.9 62.5 64.3 Radio and TV-number of radio relay facilities (million) 46.2 49.1 52.1 55.5 59.0 62.7 66.4 70.2 74.0 77.8 Approved for Release: 2019/07/19 C05210421 Approved for Release: 2019/07/19 C05210421 Appendix E (continued) 1980 1970 = 100 Housing Urban housing Endyear stock�useful space 2,200.0 (million square meters) Endyear stock�living space 1,466.7 (million square meters) Midyear stock�living space 1,444.7 (million square meters) Rural housing Endyear stock�useful space 1,168.6 (million square meters) Construction (million square meters) 30.0 Transfers of rural housing to urban housing 1.5 (million square meters) Retirements (million square meters) 23.3 Endyear stock�living space 876.4 (million square meters) Midyear stock�living space 874.5 (million square meters) Total housing Midyear stock�living space 2,319.1 (million square meters) Utilities Household use of electricity 70.572 (billion kilowatt-hours) Household use of natural gas 16.313 (billion cubic meters) Urban public housing Midyear stock living space 1,110.0 (million square meters) Repair and personal care State-provided services RSFSR sales (million 1955 rubles) RSFSR sales (million rubles) Approved for Release: 2019/07/19 C05210421 State-provided services (continued) USSR sales�constant prices (million rubles) USSR sales�current prices (million rubles) USSR sales (million 1976 rubles) 8,822.9 Privately-provided services Total sales (million rubles) 2,000. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Housing services (million rubles) 1,071. Recreation Movie admissions (million) 4,244. Theater admissions (million) 122. Resort visitors (thousand) 14,546. Hotel employment (thousand) 134. Hotel employment (million manhours) 244. Transportation Rail (billion passenger-kilometers) 331.2 Sea (billion passenger-miles) 1,350.0 River (billion passenger-kilometers) 6.0 Bus (billion passenger-kilometers) 389.8 Air (billion passenger-kilometers) 160.6 Tram (million passengers) 8,255.0 Trolleybus (million passeners) 9,035.0 Subway (million passengers) 3,823.0 Taxi (million paid kilometers) 8,252.5 Communications Postal�number of items (million) 54,307.0 Telephone�long distance calls (million) 1,264.0 Telephone�urban telephones (thousand) 20,043.0 Telephone�rural telephones (thousand) 3,657.0 Telegraph�number of telegrams (million) 531.0 Radio and TV�number of radios 67.7 (million) Radio and TV�number of TV sets 66.6 (million) Radio and TV�number of radio relay 81.6 facilities (million) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix F Data Used in the Derivation of the Index of Communal Services 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV co -P. 1959 1950 1951 1952 1953 1954 1954 1956 1957 1958 Education Personnel services Education and culture-employment (thousands) 3,315. 3,434. 3,553. 3,647. 3,817. 3,977. 4,103. 4,250. 4,378. 4,556. Culture-employment (thousands) 279. 289. 299. 307. 322. 335. 346. 358. 369. 384. Education-employment (thousands) 3,036. 3,145. 3,254. 3,340. 3,495. 3,642. 3,757. 3,892. 4,009. 4,172. Education and culture-manhours (million) 5,467.9 5,653.0 5,837.2 5,983.8 6,256.4 6,510.0 6,597.8 6,720.6 6,889.6 7,033.0 Culture-manhours (million) 584.8 604.5 624.0 639.5 668.1 694.6 701.6 712.3 729.9 739.0 Education-manhours (million) 4,883.1 5,048.4 5,213.2 5,344.2 5,588.3 5,815.4 5,896.2 6,008.4 6,159.8 6,293.0 Other current outlays Kindergartens Outlays net of investment (million rubles) 332.1 316.7 310.3 301.6 312.1 355.9 392.3 457.8 512.9 577.7 Other current outlays as a percent of total outlays 72.6 72.5 71.3 68.4 67.8 68.2 68.1 66.8 66.6 66.4 Other current outlays (million rubles) 294.0 280.2 280.2 269.6 282.1 317.1 351.1 401.6 451.0 514.4 General education Republic budget non-investment outlays (million rubles) 2,359.0 2,446.5 2,469.6 2,508.2 2,515.8 2,525.3 3,555.0 3,733.3 2,829.2 3,032.0 Republic budget other current outlays (million rubles) 529.2 496.3 447.1 520.2 399.1 407.9 425.0 476.7 501.3 596.8 Republic budget other current outlays as a percent of total outlays 22.4 20.3 18.1 16.8 15.9 16.2 16.6 17.4 17.7 19.7 USSR outlays, less kindergartens (million rubles) 3,040.0 3,129.2 3,165.1 3,223.4 3,272.8 3,354.2 3,452.7 3,762.3 3,868.0 4,435.2 USSR investment outlays, less kindergartens (million rubles) 42.2 40.8 37.7 55.1 74.8 80.3 87.0 123.8 157.2 307.7 USSR outlays net of investment, less � kindergartens (million rubles) 2,997.8 3,088.4 3,127.4 3,168.3 3,198.0 3,273.9 3,365.7 3,638.5 3,821.8 4,127.5 USSR other current outlays (million rubles) 598.0 562.3 510.0 480.3 457.8 471.3 494.6 544.7 586.3 698.7 Higher education (Vuzy) Republic budget outlays net of investment and stipends (million rubles) 158.9 157.2 160.3 166.5 175.8 251.7 269.0 285.7 200.3 672.2 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Higher education (continued) Republic budget other current outlays (million rubles) 28.4 28.6 28.1 29.1 30.0 44.1 48.0 51.9 55.1 132.1 Republic budget other current outlays as a percent of total outlays 17.9 18.2 17.5 17.5 17.1 17.5 17.8 18.2 18.4 19.7 Specialized education (tekhnikums) Republic budget outlays net of investment and stipends (million rubles) 153.0 153.0 159.4 1,164.3 181.6 186.5 234.6 316.2 303.4 316.3 Republic budget other current outlays (million rubles) 38.6 38.7 41.5 43.1 46.4 51.0 70.9 92.9 87.3 91.4 Republic budget other current outlays as a percent of total outlays 25.2 25.3 26.0 26.2 25.6 27.3 30.2 29.4 28.8 28.9 Cadre preparation- Vuzy, technikums and trade schools USSR total outlays (million rubles) 1,807.1 1,747.2 1,799.4 1,911.7 2,237.6 2,307.9 2,401.0 2,396.0 2,333.3 2,371.2 Investment (million rubles) 35.0 30.6 36.8 42.8 78.9 88.0 81.2 91.7 97.0 98.2 Outlays net of investment (million rubles) 1,772.1 1,716.6 1,762.6 1,868.9 2,158.7 2,219.9 2,319.8 2,304.3 2,236.3 2,273.0 Stipends (million rubles) 187.0 - 295.2 317.7 363.1 341.2 584.0 Outlays net of investment and stipends (million rubles) 1,586.5 1,649.0 1,714.0 1,781.5 2,851.7 1,925.1 2,002.7 1,941.8 1,895.5 1,689.6 Republic budget other current outlays (million rubles) 67.0 67.3 69.6 72.2 76.4 95.1 118.9 144.8 142.4 223.5 Republic budget outlays net of investment and stipends (million rubles) 311.9 310.2 319.7 330.8 357.4 438.2 503.6 601.9 602.7 988.5 Republic budget other current outlays as a percent of total 21.5 21.7 21.8 21.8 21.4 21.7 23.6 24.1 23.6 22.6 USSR other current outlays (million rubles) 340.8 372.4 383.7 407.9 461.5 417.8 472.8 467.1 447.9 382.0 All education-total Other current outlays (million rubles) 1,232.8 1,214.9 1,173.9 1,157.8 1,201.4 1,206.2 1,318.5 1,423.5 1,491.1 1,595.1 Price index for material expenditures (1970=100) 103.3 103.3 97.6 93.5 94.2 90.1 90.5 93.2 93.1 93.6 Other current outlays (million 1970 rubles) 1,267.2 1,248.5 1,277.0 1,315.0 1,354.6 1,421.9 1,547.9 1,621.8 1,701.6 1,808.9 Health Employment-thousands 2,051. 2,139. 2,226. 2,308. 2,468. 2,627. 2,736. 2,892. 3,059. 5,602.1 3,245. 5,860.0 Manhours-million 3,886.8 4,047.7 4,206.1 4,356.9 4,655.5 4,950.7 5,098.6 5,314.8 Republic budget outlays net of investment (million rubles) 1,909.1 1,929.8 1,977.4 2,130.6 2,215.3 2,433.9 2,871.1 3,182.5 3,456.4 3,740.3 Republic budget other current outlays (million rubles) 825.4 799.6 803.1 881.6 882.6 962.5 1,057.4 1,203.6 1,286.0 37.9 1,395.4 38.3 Republic budget other current outlays as percent of total outlays 43.0 2,144. 41.1 2,170. 40.3 41.1 2,410. 39.7 39.6 37.0 38.1 USSR outlays net of investment (million rubles) 2,232. 2,857. 3,078. 3,517. 3,770. 3,998. 4,297. USSR other current outlays (million rubles) 922.0 103.3 892.9 900.0 991.1 1,135.1 1,220.3 1,302.3 1,436.5 1,515.3 1,647.4 Price index for material expenditures (1970=100) 103.3 97.6 979.0 93.5 94.2 90.1 90.5 93.2 93.1 93.6 Other current outlays (million 1970 rubles) 947.8 917.6 1,125.7 1,279.9 1,438.6 1,528.8 1,636.7 1,729.2 1,868.2 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix F (continued) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 Education Personnel Services Education and culture-employment (thousands) 4,803. 5,165. 5,521. 5,835. 6,235. 6,600. 6,902. 7,187. 7,531. 7,811. Culture-employment (thousands) 405. 435. 465. 492. 523. 556. 580. 636. 699. 759. Education-employment (thousands) 4,398. 4,730. 5,056. 5,343. 5,681. 6,044. 6,322. 6,551. 6,832. 7,052. Education and culture-manhours (million) 7,200.8 7,534.2 8,053.5 8,498.7 9,066.7 9,595.0 10,057.7 10,481.3 10,987.3 11,399.0 Culture-manhours (million) 752.0 776.0 825.7 870.5 929.5 981.4 1,028.4 1,131.0 1,245.7 1,355.0 Education-manhours (million) 6,468.8 6,758.2 7,227.7 7,628.2 8,137.2 8,613.6 9,029.3 9,350.3 9,741.6 10,044.0 Other current outlays Kindergartens Total outlays net of investment (million rubles) 659.8 781.9 946.5 1,124.1 1,333.8 1,694.6 1,883.2 2,034.6 2,295.6 2,494.8 Other current outlays as a percent of total outlays 66.9 65.9 66.4 66.9 65.3 58.9 57.8 57.1 53.0 53.4. Other current outlays (million rubles) 621.5 700.0 850.9 1,012.2 1,189.1 1,317.1 1,424.5 1,509.8 1,584.0 1,714.4 General education Republic budget non-investment outlays (million rubles) 3,314.5 3,688.7 4,-0.1 4,280.6 5,650.4 5,637.8 5,813.4 5,982.1 6,421.1 6,638.5 Republic budget other current outlays (million rubles) 699.2 799.4 894.1 966.3 1,022.8 1,077.3 1,061.2 1,106.7 1,173.1 1,208.6 Republic budget other current outlays as a percent of total outlays 21.1 21.7 22.4 22.6 22.0 19.1 18.3 18.5 18.3 18.2 USSR outlays, less kindergartens (million rubles) 5,-2.2 5,614.2 6,207.9 6,730.3 7,374.7 8,935.6 USSR investment outlays, less kindergartens (million rubles) 421.0 512.8 573.3 596.7 585.3 621.3 USSR outlays net of investment, less kindergartens (million rubles) 4,581.2 5,101.4 5,634.6 6,133.6 6,789.4 8,314.3 8,750.8 9,125.2 9,894.3 10,364.9 USSR other current outlays (million rubles) 827.2 936.1 1,047.9 1,130.8 1,199.9 1,264.9 1,253.6 1,311.8 1,388.2 1,432.8 Higher education (Vuzy) Republic budget outlays net of investment and stipends (million rubles) 702.0 743.0 8-.9 755.5 795.2 877.5 931.9 875.6 965.8 1,039.8 Republic budget other current outlays (million rubles) 137.4 145.9 154.8 143.0 151.0 159.3 168.4 154.8 170.6 183.6 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Higher education (continued) Republic budget other current outlays as a percent of total outlays 19.6 19.6 19.3 18.9 19.0 18.2 18.1 17.7 17.7 17.5 Specialized education (tekhnikums) Republic budget outlays net of investment and stipends (million rubles) 320.7 335.6 357.8 383.5 415.0 516.9 449.1 466.2 514.5 544.5 Republic budget other current outlays (million rubles) 90.1 90.0 94.5 98.9 102.7 111.3 101.4 96.6 106.6 112.3 Republic budget other current outlays as a percent of total outlays 28.1 26.8 26.4 25.8 24.7 21.5 22.6 20.7 20.7 20.6 Cadre preparation-Vuzy, tekhnikums and trade schools USSR total outlays (million rubles) 2,402.5 2,513.6 2,723.2 2,888.5 3,081.9 3,451.8 Investment (million rubles) 114.7 115.0 124.4 152.4 157.2 - - - - Outlays net of investment (million rubles) 2,287.8 2,398.6 2,598.8 2,736.1 2,924.7 3,251.1 3,562.1 3,948.4 4,290.5 4,597.7 Stipends (million rubles) 550.9 554.2 602.2 581.7 623.4 683.8 618.5 634.9 680.5 736.5 Outlays net of investment and stipends (million rubles) 1,737.5 1,845.2 2,005.4 2,163.8 2,309.9 2,573.9 2,950.0 3,322.5 3,617.0 3,866.5 Republic budget other current outlays (million rubles) 227.5 235.9 249.3 241.9 253.7 270.6 269.8 251.4 277.2 295.8 Republic budget outlays net of investment and stipends (million rubles) 1,022.7 1,078.6 1,158.7 1,139.0 1,210.2 1,394.4 1,381.0 1,341.8 1,480.3 1,584.3 Republic budget other current outlays as a percent of total 22.2 21.9 21.5 21.2 21.0 19.4 19.5 18.7 18.7 18.7 USSR other current outlays (million rubles) 386.5 403.6 431.5 459.5 484.2 499.5 576.3 622.5 677.3 721.9 All education-total Other current outlays (million rubles) 1,835.2 2,039.7 2,330.3 2,602.6 2,873.2 3,081.5 3,254.5 3,444.1 3,649.6 3,869.1 Price index for material expenditures (1970 = 100) 95.3 95.4 97.7 98.3 101.1 102.6 103.2 104.3 104.7 105.0 Other current outlays (million 1970 rubles) 2,045.4 2,269.9 2,532.2 2,810.4 3,017.0 3,189.6 3,347.8 3,505.3 3,702.8 3,912.7 Health Employment-thousands ^ 3,461. 3,677. 3,818. 3,933. 4,082. 4,277. 4,427. 4,545. 4,747. 4,927. Manhours-million 6,133.7 6,378.3 6,622.9 6,815.1 7,090.2 7,401.4 7,679.2 7,894.3 8,254.0 8,576.0 Republic budget outlays net of investment (million rubles) 4,076.9 4,381.8 4,642 4,937.9 5,321.5 6,281.1 6,609.9 6,940.8 7,607.0 8,002.1 Republic budget other current outlays (million rubles) 1,567.8 1,680.3 1,810.7 1,949.1 2,073.0 2,212.3 2,293.7 2,392.5 2,500.4 2,603.6 Republic budget other current outlays as percent of total outlays 39.4 39.1 39.7 40.2 39.7 36.0 35.5 35.4 33.8 33.6 USSR other current outlays (million rubles) 1,827.6 1,886.4 1,890.2 2,036.2 2,162.9 2,311.2 2,427.7 2,533.7 2,642.7 2,751.6 Price index for material expenditures (1970 = 100) 95.3 95.4 97.7 98.3 101.1 102.6 103.2 104.3 104.7 105.0 Other current outlays (million 1970 rubles) 2,036.9 2,099.4 2,054.0 2,198.8 2,271.2 2,392.2 2,497.4 2,578.7 2,681.2 2,782.6 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix F (continued) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV t..a VZ. Co 1970 1971 1972 1973 1974 1974 1976 1977 1978 1979 Education Personnel Services Education and culture-employment (thousands). 8,070. 8,309. 8,531. 8,759. 8,977. 9,191. 9,392. 9,622. 9,915. 10,128. Culture-employment (thousands) 824. 876. 915. 964. 1,014. 1,056. 1,097. 1,161. 1,209. 1,235. Education-employment (thousands) 7,246. 7,433. 7,616. 7,795. 7,963. 8,135. 8,295. 8,461. 8,706. 8,893. Education and culture--manhours (million) 11,811.2 12,211.3 12,519.7 12,794.0 13,135.4 13,931.5 13,725.7 14,040.8 14,468.3 14,778.0 Culture-manhours (million) 1,467.3 1,568.7 1,635.3 1,711.9 1,304.6 1,376.4 1,949.2 2,058.6 2,143.4 2,189.0 Education-manhours (million) 10,344.0 10,642.6 10,884.4 11,082.1 11,330.9 11,555.1 11,776.5 11,982.2 12,324.9 12,589.0 Other current outlays Kindergartens Total outlays net of investment (million rubles) 2,600.4 2,755.8 2,922.9 3,167.6 3,328.5 3,513.3 3,713.0 3,979.0 4,277.0 14,518.0 Other current outlays as a percent of total outlays 53.0 52.9 51.7 50.4 50.4 51.4 51.4 51.4 51.4 51.4 Other current outlays (million rubles) 1,768.1 1,875.8 1,928.5 2,028.7 2,135.5 2,292.3 2,422.6 2,596.3 2,790.6 2,947.7 General education Republic budge1 non-investment outlays (million rubles) 1,768.1 1,875.8 1,928.5 2,028.7 2,135.5 2,292.3 2,422.6 2,596.3 2,790.6 2,947.5 Republic budget other current outlays (million rubles) 1,232.5 1,276.5 1,310.9 1,347.7 1,400.8 1,462.0 1,491.9 1,515.5 1,537.8 1,567.9 Republic budget other current outlays as a percent of total outlays 18.0 17.9 17.4 16.5 16.7 17.2 17.2 17.3 17.2 17.3 USSR outlays, less kindergartens' (million rubles) USSR investment outlays, less kindergardens (million rubles) USSR outlays net of investment, less kindergartens (million rubles) 10,748.8 11,224.6 11,880.3 12,910.6 13,367.5 13,853.7 14,283.0 14.722.0 15,326.0 15,728.0 USSR other current outlays (million rubles) 1,464.3 1,517.4 1,559.3 1,604.0 1,678.1 1,775.2 1,819.3 1,858.3 1,901.4 1,944.8 Higher education (Vuzy) Outlays net of investment and stipends (million rubles) 1,097.8 1,151.6 1,221.5 1,285.4 1,354.5 1,420.6 1,485.6 1,561.1 1,648.6 1,717.9 Other current outlays (million rubles) 192.1 195.6 205.3 209.5 223.8 234.5 245.2 257.6 272.1 283.5 Other current outlays as a percent of total outlays 17.5 17.0 16.8 16.3 16.5 16.5 16.5 16.5 16.5 16.5 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Specialized education (tekhnikums) Republic budget outlays net of investment and stipends (million rubles) 576.4 605.8 650.9 720.4 747.6 764.0 788.8 818.2 842.5 854.1 Republic budget other current outlays (million rubles) 119.0 125.9 131.5 135.9 142.4 146.2 150.9 156.6 161.2 163.5 Republic budget other current outlays as a percent of total outlays 20.6 20.8 20.2 18.9 19.0 19.1 19.1 19.1 19.1 19.1 Cadre preparation- Vuzy, tekhnikums and trade schools USSR total outlays (million rubles) Investment (million rubles) Outlays net of investment (million rubles) 4,853.6 5,145.8 5,572.4 6,177.2 6,630.3 7,019.4 7,387.0 7,734.0 8,108.0 8,393.0 Stipends (million rubles) 765.5 800.6 1,068.8 1,300.8 1,373.8 1,432.5 1,507.4 1,578.2 1,654.5 1,712.6 Outlays net of investment and stipends (million rubles) 4,091.7 4,347.2 4,504.8 4,877.6 5,257.5 5,587.5 5,880.2 6,156.4 6,454.1 6,681.0 Republic budget other current outlays (million rubles) 311.1 321.5 336.8 345.4 366.2 380.7 396.1 414.2 433.3 447.0 Republic budget outlays net of investment and stipends (million rubles) 1,674.2 1,757.4 1,872.4 2,005.8 2,102.1 2,184.6 2,274.4 2,379.3 2,491.1 2,572.0 Republic budget other current outlays as a percent of total 18.6 18.3 18.0 17.2 17.4 17.4 17.4 _ 17.4 17.4 17.4 USSR other current outlays (million rubles) 760.3 795.3 810.3 839.9 915.9 973.7 1,024.1 1,071.7 1,122.6 1,161.1 All education-total 4,188.5 4,298.1 4,472.7 4,729.5 5,041.2 5,265.9 5,526.3 5,814.7 6,053.6 Other current outlays (million rubles) 3,992.7 Price index for material expenditures (1970=100) 106.2 108.3 112.3 113.2 114.3 116.5 117.8 119.0 120.8 123.0 Other current outlays (million 1970 rubles) 3,992.7 4,109.0 4,064.7 4,194.8 4,392.6 4,597.4 4,746.4 4,931.0 5,110.9 5,223.4 Health Employment-thousands 5,080. 5,239. 5,386. 5,522. . 5,655. 5,769. 5,878. 5,962. 6,033. 6,197. Manhours-million 8,832.9 9,136.1 9,382.9 9,587.9 9,831.0 10,020.1 10,209.7 10,344.6 10,467.8 10,752.0 Republic budget outlays net of investment (million rubles) 8,675.3 9,030.9 9,418.0 9.856.6 10,289.7 10,760.2 11,144.0 11,692.8 12,656.1 13,159.2 Republic budget other current outlays (million rubles) 2,936.5 3,012.3 3,161.9 3,272.2 3,422.0 3,578.6 3,706.2 3,888.8 4,209.0 4,376.4 Republic budget other current outlays as a share of total outlays � 35.4 35.2 35.3 34.7 34.9 35.0 35.0 35.0 35.0 35.0 USSR outlays net of investment (million rubles) 8,785.0 9,033. 9,441. 9.950. 10,375. 10,823. 11,209. 11,761. 12,730. 13,236. USSR other current outlays (million rubles) 3,105.7 3,179.9 3,337.3 3,455.9 3,619.0 3,787.8 3,922.8 4,116.1 4,455.1 4,632.2 Price index for material expenditures (1970=100) 106.2 108.3 112.3 113.2 114.3 116.5 117.8 119.0 120.8 123.0 Other current outlays (million 1970 rubles) 3,105.7 3,119.6 3,156.1 3,241.2 3,361.2 3,454.3 3,535.8 3,672.7 3,915.8 3,999.3 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Appendix F (continued) 1980 Education Personnel Services Education and culture�employment 10,475. (thousands) Culture�employment (thousands) 1,265. Education�employment (thousands) 9,210. 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Education and culture�manhours (million) 15,285.5 Culture�manhours (million) 2,242.7 Education�manhours (million) 13,042.8 Other current outlays Kindergartens Total outlays net of investment (million rubles) 4,775.0 Other current outlays as a percent of 51.4 total outlays Other current outlays (million rubles) 3,115.5 General education Republic budget non-investment outlays 9,263.5 (million rubles) Republic budget other current outlays 1,608.2 (million rubles) Republic budget other current outlays as 17.4 a percent of total outlays USSR outlays, less kindergartens (million rubles) USSR investment outlays, less kindergartens (million rubles) USSR outlays net of investment, less 16,121.2 kindergartens (million rubles) USSR other Current outlays (million rubles) 1,969.8 Higher education (Vuzy) Republic budget outlays net of investment and 1,760.9 stipends (million rubles) Republic budget other current outlays 290.6 (million rubles) Republic budget other current outlays as a 16.5 percent of total outlays 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Specialized education (tekhnikums) Republic budget outlays net of investment and 875.4 stipends (million rubles) Republic budget other current outlays 167.4 (million rubles) Republic budget other current outlays as a 19.1 percent of total outlays Cadre preparation� Vuzy, tekhnikums and trade schools USSR total outlays (million rubles) 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV Investment (million rubles) Outlays net of investment (million rubles) 8,602.9 Stipends (million rubles) 1,790.8 General education stipends (million rubles) 0.3 Outlays net of investment and stipends 6,812.7 (million rubles) Republic budget other current outlays 458.0 (million rubles) Republic budget outlays net of investment and 2,636.3 stipends (million rubles) Republic budget other current outlays as 17.4 a percent of total USSR other current outlays (million rubles) 1,183.6 All education-total Other current outlays (million rubles) 6,268.8 Price index for material expenditure 126.1 (1970 = 100) Other current outlays (million 1970 rubles) 5,278.8 Health Employment�ftousands 6,250. Manhours�million 10,844.4 Republic budget outlays net of investment 13,554.0 (million rubles) Republic budget other current outlays 4,507.8 (million rubles) Republic budget other current outlays as 35.0 percent of total outlays USSR outlays net of investment (million rubles) 13,633.1 USSR other current outlays (million rubles) 4,771.3 Price index for material expenditure (1970 = 100) 126.1 Other current outlays (million 1970 rubles) 4,017.8 1.Z170 1.Z900 6/LO/6 1.0Z :aseaia JOI pancuddV