Yves here. The headline overstates the conclusions from new research on the stock markets. However, the study serves to confirm that economists’ need to depict consumers and investors as cool and rational is all wet. But the assumption of strong-form rationality was essential to toy models that showed markets as producing virtuous outcomes. And do not forget, the need to shore up the pretense that market-based activity is at least efficient and better yet optimal (in terms of resource allocation) has become fundamental to the defense of capitalism. In other words, consumer/investor rationality is central to the economic dogma that defends capitalism.

We’ll get to the argument in the new INET paper soon, but basically, its authors are chuffed to establish that stock market activity is driven by stories. That is old hat to anyone on Wall Street. It is also old hat that decision- making revolves around stories; criminal attorneys know well that their success depends on getting the jury to put together the evidence and legal interpretations into a story they find convincing as the basis for their decision.

But back to the importance of the fiction of rational decision-making to economic dogma. For more detail, read ECONNED. Some key parts:

The scientific pretenses of economics got a considerable boost in 1953, with the publication of what is arguably the most influential work in the economics literature, a paper by Kenneth Arrow and Gérard Debreu (both later Nobel Prize winners), the so-called Arrow- Debreu theorem. Many see this proof as confirmation of Adam Smith’s invisible hand. It demonstrates what Walras sought through his successive auction process of tâtonnement, that there is a set of prices at which all goods can be bought and sold at a particular point in time .42 Recall that the shorthand for this outcome is that “markets clear,” or that there is a “market clearing price,” leaving no buyers with unfilled orders or vendors with unsold goods.

However, the conditions of the Arrow-Debreu theorem are highly restrictive. For instance, Arrow and Debreu assume perfectly competitive markets (all buyers and sellers have perfect information, no buyer or seller is big enough to influence prices), and separate markets for different locations (butter in Chicago is a different market than butter in Sydney). So far, this isn’t all that unusual a set of requirements in econ-land.

But then we get to the doozies. The authors further assume forward markets (meaning you can not only buy butter now, but contract to buy or sell butter in Singapore for two and a half years from now) for every commodity and every contingent market for every time period in all placesmeaning till the end of time! In other words, you could hedge anything, such as the odds you will be ten minutes late to your 4:00 PMmeeting three weeks from Tuesday. And everyone has perfect foreknowledge of all future periods.
In other words, you know everything your unborn descendants six generations from now will be up to.

In other words, the model bears perilous little resemblance to any world of commerce we will ever see. What follows from Arrow-Debreu is absolutely nothing: Arrow-Debreu leaves you just as in the dark about whether markets clear in real life as you were before reading Arrow-Debreu.

And remember, this paper is celebrated as one of the crowning achievements of economics.

And the notion that financial markets worked the way financial economics said was also exposed early on as bunk, but the theoreticians preferred to keep selling it than admit they didn’t have much to offer. Elite mathematician Beniot Mandelbrot got his hands on what was then the largest set of trading data and found that the distribution was not “normal” (aka Gaussian or “bell curve”). Their randomness was much wilder. He found that trading data from other markets showed the same behavior.

Here’s what happened next:

Mandelbrot and his ideas began to circulate in the financial economics community. At first, the reception was positive. The European polymath became an informal thesis advisor to University of Chicago economist Eugene Fama, who had found that the prices of the members of the Dow Jones Industrial Average were indeed not “normal” but were what statisticians called “leptokurtic,” with high peaks, meaning they had more observations close to the mean than in a normal distribution, but also much fatter tails. In lay terms, that means dayto- day variability is low, but when unusual events occur, variability both is more extreme and occurs more often than would occur with a normal distribution. MIT’s Paul Samuelson and other economists started looking into Lévy distributions and their implications.

The problem with Mandelbrot’s work, however, was it threatened the entire edifice of not simply financial economics, but also the broader efforts to use formulas to describe economic phenomena. Lévy distributions didn’t merely have difficult math; that might have been an intriguing challenge . There wasn’t even a way to calculate Lévy’s “alpha” reliably, although Fama’s efforts with market data did show that it was less than two, which confirmed the fear that the distributions were not normal.

The backlash was predictable. MIT professor Paul Cootner, who later published a book of essays on the random-walk hypothesis, tore into Mandelbrot at a winter 1962 meeting of the Econometric Society:

Mandelbrot, like Winston Churchill before him, promises us not utopia but
blood, sweat, toil, and tears. If he is right, almost all of our statistical tools are
obsolete. . . . Almost without exception, past econometric work is meaningless.

Surely, before consigning centuries of work to the ash pile we should like to have some assurance that all our work is not truly useless. If we have permitted ourselves to be fooled this long into thinking the Gaussian assumption is valid, is it not possible that the [Lévy] revolution is similarly illusory? At any rate, it would seem desirable not only to have more precise and unambiguous evidence in favor of Mandelbrot’s hypothesis as it stands, but also to have some tests with greater power against alternatives that are less destructive of what we know .

But Churchill had been right. The British prime minister had advocated a
difficult, perilous, and ultimately successful course of action, yet Cootner perversely
invoked him to argue instead for a failed status quo. He wanted assurances that exploring new terrain would be successful, but that isn’t the way a paradigm shift works. Indeed, Lévy distributions might not provide a comprehensive solution, but the point is to move toward better approximations, particularly when the existing ones have serious shortcomings.

Now to the current post.

By Lynn Parramore, Senior Research Analyst at the Institute for New Economic Thinking. Originally published at the Institute for New Economic Thinking website