by Mario Rizzo
The current issue of The Economist has a very interesting article on the turmoil among macroeconomists (“The Other-Wordly Philosophers”). Essentially, the article argues that although the dominant macro model, dynamic stochastic general equilibrium theory [DSGE], appears to be in a state of near-total breakdown, there is no agreement among economists as to what should replace it.
“Would economists be better off starting from somewhere else? Some think so. They draw inspiration from neglected prophets, like Minsky, who recognised that the “real” economy was inseparable from the financial. Such prophets were neglected not for what they said, but for the way they said it. Today’s economists tend to be open-minded about content, but doctrinaire about form. They are more wedded to their techniques than to their theories. They will believe something when they can model it.”
Therefore, it is not simply a matter of finding the right explanation of the recent financial meltdown and recession. The search by most macroeconomists is constrained by a certain set of unquestioned methodological precepts. These precepts go to the heart of the conception of Economics as a Science. They are the standards of what constitute acceptable forms of expression of economic ideas.
First, here are some anecdotes.
My friend Peter Boettke tells a story of a conversation he had years ago with a prominent economist. (I may have some details wrong but the main point is accurate.) The young Peter Boettke said of this person’s theory: All that is in Adam Smith. The response, dripping with arrogance, was: Maybe — but until my theory it was not Science.
This is the great problem with economics today: methodological exclusivism (or in my more intemperate moments I call it “methodological fascism”).
A young person goes to graduate school. He or she is filled with the excitement of ideas. Today, in particular, some may come with a great desire to understand what has happened in the real world of the bailouts, recessions, stimulus, and so forth. And then academic reality hits.
Formal modeling, axiomatic foundations, tractability, technical power, and topological studies. Shall I get an MA in mathematics? Do I need to take a third semester of macro-econometrics?
As a member of NYU’s Ph.D. admissions committee for the past fifteen years, I have even seen applicants who apologize for taking “too many” philosophy courses in college. I have seen others remind us that although they have been interested in history and literature, they are fully cognizant of the need to express their ideas in precise mathematical terms.
What of a clearly brilliant student who wants to question (or at least think about) these methodological issues? I had a colleague tell me, informally, that he would probably be a disruptive influence in the first-year classes. I guess it depends on one’s definition of “disruptive.”
This wouldn’t be so bad if Economics as a Science were as successful as, say, modern medicine, or if the criterion of predictive success gave the dominant macro theories high marks.
It seems pretty clear that what we have is a collective insecurity. If we open the floodgates to methodological inquiry, or even worse, to methodological pluralism, we shall become like political science, or God forefend, like sociology. So let’s keep those with disruptive instincts out of the profession. If this is not possible, then let’s at least keep them out of the good schools.
Second, what is the root of the difficulty in which macroeconomics finds itself?
I think it is the inability to reconcile a reasonable treatment of radical uncertainty with the strictures of out-of-control formalism. We have come a long way from Alfred Marshall’s idea that one does the mathematics and then burns it. In a 1906 letter to A.L. Bowley (of the Edgeworth-Bowley box fame) Marshall says:
“But I know I had a growing feeling in the later years of my work at the subject that a good mathematical theorem dealing with economic hypotheses was very unlikely to be good economics: and I went more and more on the rules – (1) Use mathematics as a shorthand language, rather than an engine of inquiry. (2) Keep to them till you have done. (3) Translate into English. (4) Then illustrate by examples that are important in real life. (5) Burn the mathematics. (6) If you can’t succeed in (4), burn (3). This last I did often.”
Clearly, the adherents of DSGE did not follow points (4) through (6).
Furthermore, in The Economist article Perry Mehrling of Barnard College is quoted as saying:
“Philosophically speaking,” economists are “materialists” for whom “bags of wheat are more important than stacks of bonds.” Finance is a veil, obscuring what really matters. As a poet once said, “promises of payment/Are neither food nor raiment”.
The objective facts are far easier to handle in the models than the shifting, subjective expectations of people trying to deal with radically uncertain futures. This is what may get reflected in financial markets. Attempting to understand all of this requires conceding that some knowledge will be imprecise and will lie outside of the box (model). The model is simply a toy that can be thrown out when it no longer suits. This means that it is indeed possible to have valuable knowledge outside of hyper-models (although, of course, all thinking proceeds in terms of assumptions and simplifications).
But this will give the “scientists” among us headaches. As John Maynard Keynes famously said about the econometrician Jan Tinbergen, “[H]e is much more interested in getting on with the job than in spending time in deciding whether the job is worth getting on with.”
As long as this is the dominant attitude, macroeconomics will remain “other-wordly.” Instead, the way to greater realism is through more attention to the methodology of science and to whether “the job is worth getting on with.” Paradoxically, greater philosophical sophistication would put economists is closer touch with the real world. (Or so I hope.)
Of course, the doctrinaire among us will no doubt reject all of this. They will tell us: Just a little more tweaking of the models is what we need.