Alan Greenspan: predicting irrationality

My colleague Jerry sent over this clip from a CBS interview with Alan Greenspan, who was talking about his new book “The Map and the Territory” after spending two years looking back through economic data to try and figure out why huge crashes were so hard to predict.


One conclusion – they didn’t know how to model irrationality and other human variables that don’t fit neatly into classical economics and efficient market theory (which assume people are always rational).  “It became very apparent to me that we misunderstand how systematic fear is,” he said.  “The fear that led to panic selling and the euphoria that inflated the housing bubble were not factored into the Federal Reserve’s computer models.”

Greenspan used to believe irrational behavior could not be projected or analyzed.  Now, he says, “I was wrong.”

“You think you can put human behavior in a model or in an equation?” Mason asked.

“In fact, you can measure it,” Greenspan replied. “Because if you look at the business cycle, for example, euphoria drives it about, and then fear collapses it.  And you can take one example after the other, and they look alike.”

Even irrationality can have predictable patterns.

This Post Has One Comment

  1. Michael Palmer

    For many non-professional economists (those with no indoctrination into the guild), the belief in aggregate rationality (i.e., a rational market) is similar to a belief in an omniscient/omnipotent god that has some plan that will cause everything to work out well in the end. The key difference is that the latter is a self-contained system that cannot be falsified by evidence, while at least some adherents of the rational market hypothesis will occasionally, if grudgingly, admit that the facts don’t fit the theory. One such inconvenient collection of evidence was the financial crisis of 2008, which Greenspan, to his credit, said had caused him to rethink his belief. (John Kenneth Galbraith: “When confronted with a need to change their minds or prove that there is no need to do so, most people get busy with the proof.” Apparently, Greenspan is an exception.)
    The notion that we could model sub-optimal decision making to predict what people will, in fact, do is not only intriguing but potentially disruptive of the way we go about making predictions of all kinds that involve human behavior. Here, the term “sub-optimal” means not best suited to serve the interests of the decision maker, whatever those are. I avoid “rational” in this context because some seem to define its content as being what a hypothetically rational person would want (e.g., more money), which involves a degree of circularity.
    I’ve worked on creating a predictive model for assessing the financial value of a lawsuit (see but have never posed the question raised by Thomas’s post: Can we create a model that predicts irrational (or sub-optimal) behavior with respect to specific circumstances (such as investing in startups)?
    I’m game to learn more and discuss possibilities.

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