“Hard Math” by misterbisson via flickr, used under a Creative Commons license .

Paul Krugman recently published an essay in the New York Times highlighting the misguided use of math by economists as the key reason for their inability to predict the current financial crisis:

As I see it, the economics profession went astray because economists, as a group, mistook beauty, clad in impressive-looking mathematics, for truth. Until the Great Depression, most economists clung to a vision of capitalism as a perfect or nearly perfect system. That vision wasn’t sustainable in the face of mass unemployment, but as memories of the Depression faded, economists fell back in love with the old, idealized vision of an economy in which rational individuals interact in perfect markets, this time gussied up with fancy equations. The renewed romance with the idealized market was, to be sure, partly a response to shifting political winds, partly a response to financial incentives. But while sabbaticals at the Hoover Institution and job opportunities on Wall Street are nothing to sneeze at, the central cause of the profession’s failure was the desire for an all-encompassing, intellectually elegant approach that also gave economists a chance to show off their mathematical prowess.

The essay is full of outrageous quotes from several economics Nobel laureates about an unrealistic assumption that underpins most of the mathematical models used in their theories: people are perfectly rational agents who always act in their own best interest. For example, he quotes John Cochrane from the University of Chicago as having said that recessions are sometimes good because they force people to leave jobs that are somehow undesirable:

Cochrane declares that high unemployment is actually good: “We should have a recession. People who spend their lives pounding nails in Nevada need something else to do.”

The quote is intended to illustrate how stubborn economists can be when defending the implications of the perfect-rationality assumption: if people are always acting in their own best interest, then unemployment is voluntary — they could have always kept their jobs if they would have been willing to work for a lower wage.

To be fair, Cochrane’s response to Krugman states that the quote was taken out of context:

I didn’t write this. It’s a quote, taken out of context, from a bloomberg.com article written by a rather dense reporter who I spent about 10 hours with patiently trying to explain some basics. (It’s the last time I’ll do that!) I was trying to explain how sectoral shifts contribute to unemployment. Krugman follows it by a lie — I never asserted that “it take mass unemployment across the whole nation to get carpenters to move out of Nevada.” You can’t even dredge up a quote for that monstrosity.

But even if Krugman went too far with the quote, Cochrane himself then asks

… what is the alternative [to mathematical models in macroeconomics]? Does Krugman really think we can make progress on his – and my – agenda for economic and financial research — understanding frictions, imperfect markets, complex human behavior, institutional rigidities – by reverting to a literary style of exposition, and abandoning the attempt to compare theories quantitatively against data? Against the worldwide tide of quantification in all fields of human endeavor (read “Moneyball”) is there any real hope that this will work in economics?

No, the problem is that we don’t have enough math. Math in economics serves to keep the logic straight, to make sure that the “then” really does follow the “if,” which it so frequently does not if you just write prose. The challenge is how hard it is to write down explicit artificial economies with these ingredients, actually solve them, in order to see what makes them tick. Frictions are just bloody hard with the mathematical tools we have now.

I agree on the math’s power for assuring the logical consistency of economic theories, but that’s an entirely different thing than the naivete with which economists have used econometric models to predict the actual behavior of markets, precisely because “frictions are bloody hard” to capture by the mathematical tools available. This naivete is at the root of the Gaussian copula function fiasco, which allowed for the triple-A ratings of toxic CDO’s.

Also, Cochrane’s skepticism towards prose in economic analysis is quite puzzling. At some point during his resposne he points out that after all,

…the central prediction of free-market economics, as crystallized by Hayek, [is] that no academic, bureaucrat or regulator will ever be able to fully explain market price movements.

But ironically, Hayek made this point while at the same time being a prominent advocate for playing down the role of mathematics in economic analysis, as I have pointed out in a previous post. Actually his “central prediction of free-market economics” was formulated in pure prose. Other Nobel laureates such as Ronald Coase, George Akerlof and most recently, Oliver Williamson and Elinor Ostrom, have all accomplished crucial theoretical breakthroughs without writing a single mathematical equation.

Krugman is right on spot. And if Hayek was alive, this would probably have been one of the very few issues they would agree on.