ESTIMATES OF US IMPORT DEMAND ELASTICITIES FOR IRON AND STEEL

• Document Type: CREST
• Collection: General CIA Records
• Document Number (FOIA) /ESDN (CREST): CIA-RDP85T00875R001900030008-7
• Release Decision: RIPPUB
• Original Classification: U
• Document Page Count: 10
• Document Creation Date: December 19, 2016
• Document Release Date: August 17, 2005
• Sequence Number: 8
• Publication Date: July 3, 1974
• Content Type: MF

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Approve,. Release .05112114 CI,..5.0875.01900030008,
Approve,. Release .05112114 CI,..5.0875.01900030008,
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CENTRAL INTELLIGENCE AGENCY
WASHINGTON, D.C. 20505
C/A/ogy s 04.2 f-??-- 27/
3 July .1974
MEMORANDUM FOR: Mr. J.D. Darroch
Council of Economic Advisers
Old Executive Office Building
7,17/77-7,7777M717171,
SUBJECT Estimates of US Import Demand Elasticities
for Iron and Steel
of
US
STAT I
any additional questions you might have on this subject.
STAT
The attached report is in response to your request
13 June for information on CIA and other estimates of
import demand elasticities for iron and steel products.
will be happy to answer
Attachment:
As stated
Distribution: (S-6287)
On. & 1 - Addressee
OER/I/TM (3 July 1974)
A APA!"'T7N
(13t1CLAY CU.
STAT
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Estimates of US Import Demand Elasticities for Iron and Steel
Relatively little theoretical or empirical work exists on
commodity-specific import demand equations. Most researchers
who have estimated such equations have used some variant of the
simple log linear demand function in which the independent variables
typically are the ratio of the prices of imported and competitive
domestic goods, and one or more domestic activity terms:
? log M = a + b log (PM/PD) + c log Y + e
where: M is the import volume index for the commodity group
PM is the import price index for the commodity group
PD is the domestic price index for the commodity group
Y is real gross national product of other activity term
e is the error term
b is the estimated relative price elasticity
c is the estimated income elasticity.
C.R. MacPhee1 estimates an equation of this type for US steel
imports for the 19631 to 1968IV period:
log M = -.0493 - 4.170 ? log (PM/PD) + 2.307 ?
log Y,+ .
(0,139) (0.979)
(0.559)
;095 ? log (X1) + .176 ?
(X2)
- .243
(X1)
R = .977'
(0.289). (0.063)
(.426)
-
DW = 1.73
where: X1 is an index of capacity utilization in the US iron
and steel industry
is a binary dummy variable = 1 in periods of signifi-
cant strike activity in
the US steel industry
m 0 in other quarters
UGASSE (ti
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JN(LASSIPPY
X3 is the percent of US water transport and longshore
workers on strike.
tithe numbers in parentheses are the standard errors)
The price coefficient is quite large and is statistically significant.
The capacity utilization and dock strike variables were not
? significant, but the steel strike variable was. MacPhee
uses these estimates to help guage the restrictiveness of non-tariff
barriers on iron and steel trade.
Price and Thornblade2 have estimated a similar equation, but
distinguish between US demand for imports from different countries
and between various steel products. Their equation is:
2 PMt_, ? 2
log M. = a + bl ? log i...c1e ( + b2 ? log L. oe?,r9 =0 PDt_e_i rr 0
PMt-
ir
+ c log
-t d14:22 d2Q3 d3Q4
Y
POMt
?
114
where: the second and third terms use a three-quarter
weighted moving average where the weights are:
0 041=1/3
ce =1/2
*42=1/6
POM is the composite price index for steel imports
from countries other than country j.
Y is domestic steel production.
2
Wareseasonaldummyvariableswhere.has Qi
th
a value of one in the i quarter of the year and
zero otherwise.
Table 1 shows that Price and Thornblade had varying degrees of
success with their country and commodity specific import demand
-2-
?
ApproVed Fo e ease
kived
I1 ;
?
Table 1
US Import Demand in nal2E_g21.252Eit?_af Steel Products from Leading Foreign Suppliers
(values in parentheses are t values)
Iron & Steel Sheets,
Plates (SITC 674)
Pm
Domestic
Production
Con-
stant
023
4
Standard
2 Error of
R Estimate
POM
0.384
(.260)
11.142
(3.743)
1.739
(0.369)
1.674
(1.058)
-0.121
(-0.131)
-2.100
(-0.677)
5.401
(1.477)
0.869
(1.620)
.845
(-.827)
1.956
(1.383)
1.776
(2.599)
1.047
(1.859)
1.638
(2.696)
1.412
(1.575)
15.965
-1.269
-9.160
1.200
5.543
2.934
-4.957
0.095
(1.320)
0.308
(2.260)
.0.371 -
(1.964):
-0.009
(-0.094)
0.101
(1.857)
0.162
(2.809)
0.176
(1.997)
0.089
(1.170)
0.446
(3.156)
0.445
(2.243)
..i0.066
(-0.657)
'
0.055
(0.843)
0.058
(0.851)
0.050
(0.479)
?
0.061
(.947)
0.482
(4.052)
0.428
(2.488)
-0.076
(-0.926)
0.066
(1.279)
0.042
(0.784)
0.025
(0.301)
.726
.748
-
.550
.469
0.515
.665
.519
0.105
0.195
0.274
-r
0.133c
--)
..-.1
-
1
'.1
0.08-0,:::
0.085
0.130
Japan -8.354
(-5.228)
West Germany -10.755
(-4.116)
=United Kingdom -3.183
.7a7. (-0.835)
wt.,Canada -7.177
(-2.106)
Steel Bars
(SITC 673)
Japan
Belgium
France
-1.902
(-0.938)
-0.576
(-0.348)
-3.591
(-1.929)
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West Germany
United Kingdom
Pm
PD
-3.009
(-1.24P)
-4.669
? (-2.195)
Iron &.?Steel Tubes,
Pipes (SITC 678)
Japan -3.567
(-2.798)
Canada
8.269
(1.258)
POM
Table 1 -
cont'd
Q4
?
R2
Standard
Error of
Estimate
Domestic'
Production
Con-
stant
23
-1.299
(-0.333)
1.442
(0.645)
0.139
(0.260)
.0.418
(0.098)
0.515
(0.518)
-0.414
(-0.424)
0.255
(0.468)
1.900
(1.053)
13.410
17.110
13.374
-22.365
0.281 .
(2.864)
0.219
(2.294)
Cfn102
(1.539)
-0.247
(-1.141)
0.224
(1.899)
0.319
(2.802)
0.084
(0.876)
-0.435
(-1.401)
0.254
(2.770)
0.227
(2.542)
0.078
(1.247)
-0.247
(-1.192)
.601
.722
0.713
.748
0.145
0.141
0.073
0.223
"Pi
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UNG1..,ASSI!pr)
estimates. The relative price elasticity between domestic
and foreign supply has the expected negative sign in 10 out of
11 cases, but is significantly different from 0 (at the 95%
confidence level) in only 5 out of 11 cases. The relative price
elasticity between foreign suppliers has the expected negative
sign in only 3 out of 11 cases.
Kreinin,3'4 using the same general specification, found no
significant price effect on US aggregate demand for imported iron
and steel products. Similarly, Officer and Hurtubise5 -- using
?
a somewhat different framework -- report that the relative price
term was insignificant in their equation representing US demand for
Canadian iron and steel.
The studies mentioned share a number of significant weaknesses:
In each case, unit values were used to construct import
price indexes. There is considerable concern that unit
values -- while easy to acquire -- are not an accurate
price measure.
?There is substantial evidence that institutional factors,
such as strikes, non-tariff barriers, and cyclical swings,
have a significant impact on trade in steel, but most of
the studies ignore these factors. None of them accounts
for the institution of the VRA.
?No experimentation was made with alternate functional forms.
A major part of the CIA Trade-Flow Model Project consists of
the estimation of country and commodity-specific import demand
equations for the United States, and for 12 other counties, for
.iron and steel products. CIA employs a sophisticated n-level
procedure, which first estimates the elasticity of substitution between
domestic and foreign steel, and then the elasticity of substitution
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between foreign sources of supply. We are currently experimen-
ting with several different functional forms, and we expect to
include a considerable amount of institutional data. We have so
far estimated only the second stage of the demand relationship,
the elasticity of substitution between various foreign suppliers
of iron and steel in the US market. Some preliminary results are
presented in Table 2.6
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Table 2
f1144e1
t'c
:
Estimates of the Elasticity of Substitution Between
Foreign Steel Suppliers in the US Market
1. Unconstrained dynamic import demand Equations, estimated by
OLS (elasticity of substitution between French and German
steel in the US market).
Type of Lag
Almon Second Order 3
4
5
Almon Third Order 3
4
5
Free Lag
3
4
5
^
1.57
.60
1.61
.65.
2.31
.66
2.34
.75
2.81
.69
3.40
.66
2.57
.74
3.19
.72
1.24
.73
2. Static import demand system constrained to be equal
- .between foreign suppliers, estimated by OLS.
= 1.64 = 6.96
3. Import demand equation estimated by full information maNimum
likelihood technique (elasticity of substitution between
Japanese, Canadian, Benelux, German, and UK steel in the US
market).
1.38 "t =. 2.18
Individual equation
R2,s range from .48 to .94
4. Brown-Heien import demand equations estimated by the full
information maximum likelihocd technique (elasticity of
substitution between Japanese, Canadian, German, and
Benelux steel in the US market).
=1.16
;
System R2 = .91
tflVc: AcT..
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UNt7 6
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Li
1. C.R. MacPhee, Non-Tariff Barriers to International Trade in Steel,
University Microfilms #71-2112, Ann Arbor, Michigan.
2. James E. Price and James B. Thornblade, "US Import Demand Functions
Disaggregated by Country and Commodity," Southern Economic Journal,
July 1972.
3. Mordecai E. Kreinin, "DiSaggregated Import Demand Functions
? Further Results," Southern Economic Journal, July 1973.
4. GATT, A Survey of Possible Approaches to a Study of Trade Effects
of Tariff Changes,, June, 1972.
S. Lawrence Officer and James Hurtubise, "Price Effects of the Kennedy
Round on Canadian Trade," Review of Economic and Statistics,
August 1969.
6. CIA Trade-Flow Model, IPA Report, January 1974.
CIA/OER
3 July 1974
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