What the World Economic Crisis
Should Teach Us
Carmen Medina and Rebecca Fisher
This article is based on a presentation made to a conference on the future of intelligence in May 2009.
There is much for intelligence professionals to learn from the follies of economists, and from this folly in particular.
“Why did economists not do a better job anticipating the crisis?” was the question everyone seemed to be asking as the global economy began to unravel last fall. The consensus seems to be that most economists not only failed to see the crisis coming but also were downright hostile to the few who argued that The Great Moderation—the era of economic stability brought about by modern banking system controls—wasn’t so great after all. New York Times columnist (and 2009 Nobel Prize winner in economics) Paul Krugman was ridiculed for much of this decade.1 Another harbinger named Danny Schechter wrote a book that 30 publishers rejected because they believed he was exaggerating. His book, Plunder: Investigating Our Economic Calamity and the Subprime Scandal, finally went to print in September 2008, just as the implosion was getting under way.
As economists wrote about not having done a better job anticipating the meltdown, it became apparent that there were parallel take-aways for analysis in the field of intelligence. There is, in fact, much for intelligence professionals to learn from the follies of economists, and from this folly in particular. Warren Buffet’s 2002 Berkshire Hathaway annual report hinted at such an association when he used the term “financial weapons of mass destruction” to describe the derivative asset class. When one of the world’s most respected businessmen borrows from the intelligence lexicon, turnabout is fair play.
Though we probably don’t need much reminding, it may be helpful to recall how the economic crisis evolved and the extent to which it radiated out. Anyone who has looked at his brokerage accounts or her retirement portfolio lately already “gets it” at the macro level. But what exactly happened on the cellular level to get us to where we ended up? And what can we, as intelligence professionals, learn from those events?
Twenty years ago, economists—quite important ones—did see a game-changing financial crisis looming, although without any specificity as to its timing. In a conference organized in 1989 by the National Bureau of Economic Research to consider the risk of economic crisis, Lawrence Summers—then a professor of economics at Harvard University—presented a paper that tracked, in impressively close formation, with the timeline of today’s crisis. With uncanny prescience, Summers wrote:
It is probably now easier to lever assets than ever before, and the combination of reduced transactions costs and new markets in derivative securities make it easier than it has been in the past for the illusion of universal liquidity to take hold. Asset price bubbles are now as likely as they have ever been. Bubbles eventually burst. The increased speed with which information diffuses and the increased use of quantitative-rule-based trading strategies make it likely that they will burst more quickly today than they have in the past.2
As far back as 20 years ago Summers was writing about the increased speed at which information can disseminate and contagion can occur. Yet, when CNN International’s Richard Quest interviewed world economic leaders in January 2008 at the Davos Summit, only half of those asked said they thought the then new, disturbing reports about the housing crisis and equity problems would extend beyond the banking industry.
The fact is that most economists and business experts did not anticipate this economic regression, or its particular timing, with any great degree of specificity, despite the astute analysis of Larry Summers and a few other highly regarded theorists. Economist James Galbraith estimated that, out of thousands of economists, perhaps only eight or 10 individuals really saw the crisis coming.3 Harsh as it may seem, his estimate is more generally true than not. But in the wake of calamity, the profession has vigorously begun its own “after action review”—with all kinds of lessons emerging in its own ranks, in the press, and in classrooms across the country. The difficulty is choosing just a few to single out as particularly relevant to the intelligence profession.
Six lessons from the economists’ experience seem to have unique applicability to what we, as intelligence professionals, do.
Leaving behind the issues of bias on the part of economists (which has already been discussed among intelligence officers, along many dimensions) and “group-think” because, again, we are deeply familiar with these pitfalls, six lessons from the economists’ experience seem to have unique applicability to what we, as intelligence professionals, do.
Lesson 1: There are no easy, obvious, straightforward policy responses to the economic crisis.
Once a financial crisis begins, there are no simple or clear policy responses; in reality, every policy response will inevitably feed back onto the economic crisis, for better or worse (in the tradition of the adage “When Alan Greenspan sneezes, the world catches a cold.”). For example, Summers described the range of possible policy responses to economic crises to include:
- The laissez-faire position, which holds there is no reason for public intervention in financial markets.
- The monetarist position: that the only appropriate government role is to insulate the money stock from developments, i.e., declines, in asset markets.
- The classical position, which argues that the government, as lender of last resort, should only lend to solvent banks, at a penalty rate, for short periods of time.
- The pragmatic position, which says the government must always do whatever is necessary to preserve the integrity of the financial system.4
All of these, even the option of doing nothing, have impacts on the crisis itself: an expansive monetary policy can lead to a currency crisis, which could in turn lead foreigners to sell, putting further downward pressure on assets and placing more strain on the financial system, which is where we started in the first place.
Admittedly, the issue of policy response is not part of the answer to the question of why economists missed important warning signs. But it is an object lesson in why responding to crises is so perilous: decisions can be dangerous, even those made with the best intentions. In this respect, the issue of policy response suggests a certain truth that intelligence professionals are wise to ponder: We often assume decisions are the start of long term, committed relationships—but sometimes decision making is just a one night stand. In the endless courting that occurs between intelligence professionals and policymakers, we, the intelligence professionals, often behave as if our version of the truth—our “decisions”—take on Talmudic proportions (only this, one might argue, could justify the time it often takes us to deliver our considered judgments). We treat the decision space as though it is preparation for a committed relationship, but quite often the decision—frequently a not-very-clear choice among several other equally reasonable options—will be amended rather quickly, or overtaken by events even sooner.
Furthermore, decisions are rarely made in the full possession of perfect information, another reason they lack staying power. Our understanding of causality and sequence leaves much to be desired, and every day that passes offers more opportunities for new decisions that will affect the context of any given problem.
Lesson 2: We are overly sanguine about how close our information and intelligence sources approximate reality.
Our understanding of causality and sequence leaves much to be desired.
The second lesson from the global financial crisis is that economists thought their limited data accurately reflected reality. Famously, many of the financial houses in New York quantified their risk positions using algorithms that “assumed away” the very conditions that led to the crisis. In addition, as blogger and CNBC commentator Barry Ritholtz has noted, many of the actions that precipitated the crisis were hidden even to the most careful observers; what was in essence a “run” on the world’s largest financial institutions didn't occur in the physical world—it happened as people pulled the virtual plug on their investments in the privacy of their own homes.
We intelligence professionals can be horribly guilty of this same error, treating the information that arrives in our inboxes as the population (to borrow a term from the pollsters), when in fact the information (secret or open source) can only ever be a sample. This is, of course, as the American, British, Australian, and other commissions and reports pointed out, one of the major plot lines in the Iraq WMD misstep. As Ritholtz also pointed out, the tendency of economists to uncritically accept data from certain limited sources led to only a passing familiarity with reality. The same can be said at times of intelligence professionals.
Lesson 3: Traditional economic analysis has trouble dealing with human irrationality.
We all tend to underestimate the importance of emotions when we attempt to understand the actions of world leaders or the sentiments of a population.
Our third learning from economics is that economists have a difficult time confronting the problem of irrationality. Perhaps the best example of this is Alan Greenspan’s testimony before Congress that it never occurred to him that bankers and other capitalists would make decisions counter to their own best and long-term interests (what he actually said was, “Those of us who have looked to the self-interest of lending institutions to protect shareholder’s equity [myself especially] are in a state of shocked disbelief.”); after all, classical economics is built on principles such as the invisible hand and the rational decision maker.
For intelligence professionals, the lesson here is straightforward: we, too, have an irrational attachment to rationality. We all tend to underestimate the importance of emotions when we attempt to understand the actions of world leaders or the sentiments of a population.
Lesson 4: Timing is very different from analysis.
Barry Ritholtz made this insightful observation in his blog; we would do well to apply it to intelligence. Understanding timing is different from analysis and requires an additional, probably still-to-be-defined set of skills; it is impossible to improve our ability to provide specific warning of threats or opportunities just by “doing analysis better.” Advances here will require that we explore much broader sources of information. Advances in this area will also require as yet undiscovered (or, if already available, underutilized) cutting-edge intellectual and cognitive techniques and tools.
The importance of timing becomes evident in economists’ struggles to identify the precipitating events in the countdown to crisis. Two camps seem to form in the debate: those who attribute the crisis to failings by individuals (e.g., bankers who irrationally failed to protect their own interests, whiz kids who created flawed algorithms) and those who recognize much more dynamic and amorphous forces at work (e.g., the emergence of new financial instruments which were deployed before anyone fully understood all their possible consequences; the use of new technologies that would affect the volume and velocity of trades in unprecedented ways, the growing interdependencies among financial centers, which increased the potential for and ease of contagion, and so forth). As a segue to lesson 5, it does appear that those who argue for more regulation in response to the crisis land in the first camp—explicitly or implicitly, they believe that regulating the actions of individuals can impose order on chaos—that is, they assume that the “individual actor” model will carry the day.
Lesson 5: How we think about causality in the world has great bearing on the priorities we set as an intelligence service and as a nation.
What caused the economic crisis? Was it the result of trends and dynamics that no individual, brokerage house, central bank could see coming, much less control—an “act of God”? Or was it caused primarily by the actions of a few, like the whiz kids who devised the clever algorithms that left out as “unlikely” the disastrous chain of events that actually happened? Perhaps it was the brokerage house that figured out how to bundle mortgages into some kind of new investment instrument. Maybe it was someone else entirely—the product of a “Great Man”? That the policy response to the economic crisis has thus far been to regulate and reregulate implies the “Great Man” theory wins out—as it often appears to dominate intelligence analysis and collection.
The wiser course is to consider all possible causalities; we may not be able to say exactly how or why, but few can deny that the world we now inhabit is vastly different from the one in which great men and the discovery of their secrets was the stock-in-trade of intelligence work. This points to an even larger question: the great debate between the value of secrets (and secrecy, writ large) and open-source information. As we consider the way we as a profession have regarded either and both of these, it is difficult to avoid the conclusion that far too little attention has been paid to the importance of open sources.
In fact, it may already be too late for us—in automatically assuming that secrets are more valuable than anything entire populations could possibly tell us, we may have missed valuable opportunities to integrate not only our thinking about but our ability to integrate open sources into work processes, technologies, and products. In many respects it seems the open-source world has passed us by.
Lesson 6: The complexity of the modern world is overwhelming our existing intellectual and informational models.
The modern economy with its complex financial instruments—derivatives, credit default swaps, and other exotic investments—became too unwieldy, too complex for anyone, even the “experts,” to understand. No amount of number crunching by economists using current analytical and information techniques would have allowed them to anticipate fully what was happening. They did not fail to execute; they failed to understand.
We too are in danger of failing to understand. Our rule-based and single-method approaches are adequate for tackling orderly problems but fall short in terms of helping us to master the chaotic ones—yet if we continue to ignore that chaotic problems do exist and profoundly affect our world, it will be at our peril. Increasingly, we see that individual (“Great Man”) beliefs and the beliefs of small groups (“experts”) comprise a very small part of what we mean when we use the term “intelligence.”
What seems warranted now is active movement away from intelligence analysis as rule-based, universally and eternally true. Physicist Mark Buchanan wrote:
The peculiar and exceptionally unstable organization of the critical state does indeed seem to be ubiquitous in our world. Researchers in the past few years have found its mathematical fingerprints in the workings of all the upheavals mentioned so far (earthquakes, eco-disasters, market crashes), as well as in the spreading of epidemics, the flaring of traffic jams, the patterns by which instructions trickle down from managers to workers in the office, and in many other things.5
What seems warranted now is active movement away from intelligence analysis as rule-based, universally and eternally true.
This requires acknowledging that systems often viewed in the past as stable entities that need significant shocks to disintegrate are just as often veined with many minute and therefore largely unseen fault lines that can be activated by very small disturbances. The fact that these small disturbances (physicists call them “critical states”) exist and can powerfully impact world events has innumerable implications for intelligence work, but at the very least it requires that we have the patience to let intelligence officers pursue very small leads and gather data on seemingly unimportant, tiny fault lines.
Many individuals, thinking about how to adjust our intellectual approaches to this much more complex environment, are beginning to introduce a new term to describe the cognitive adjustment we need to make—sense-making. It would require another extensive article to do this topic justice, but at its core is a realization that sense-making can never be contained in a finished product created by a lone expert; sense-making can only occur at the confluence of many different points of view.
Complexity is clearly the key theme that runs through the economists’ post-mortems…. Let us take heed.
There is no easy, obvious response to difficult intelligence questions because the complexity of the modern world has outpaced the capabilities of our current intellectual and informational models. These do not always accurately approximate reality, they make little accounting for human irrationality, and they fail to help us distinguish between timing and analysis. Taken together, these shortcomings force us to reconsider how we think about causality. In terms of the global financial crisis, complexity is clearly the key theme that runs through the economists’ post-mortems and it serves as an important analogue for the intelligence profession. Let us take heed.
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clear...because the world is:
fluid...because the world is:
the control of men
enough to understand
complex for rules
this world we need intelligence
this world we need sense-making
1. For Krugman’s post mortem see “How did Economists Get It So Wrong,” New York Times Magazine, 6 September 2009.
2. Larry H. Summers, “Macroeconomic Consequences of Financial Crises,” in The Risk of Economic Crisis, edited by Martin Feldstein (Chicago,IL: University of Chicago Press, 1991), 135–82. Available online at http://www.nber.org/chapters/c6231. [External link disclaimer]
3. Deborah Solomon, “The Populist: Questions for James K. Galbraith,” the New York Times Magazine, 31 October 2008. http://www.nytimes.com/2008/11/02/magazine/02wwIn-Q4-t.html. [External link disclaimer]
4. Summers, “Macroeconomic Consequences.”
5. Mark Buchanan, Ubiquity: Why Catastrophes Happen (New York: Three Rivers Press, 2002), 21.
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All statements of fact, opinion, or analysis expressed in this article are those of the authors. Nothing in the article should be construed as asserting or implying US government endorsement of its factual statements and interpretations.