This must be the period of soul searching, with the *Economist* engaging upon multi-article exegeses on where mainstream macro went wrong [1], [2], [3]. Alternatively, I think this is a happy time for some economists outside the (perceived) mainstream, who can now chortle “I told you so”. One recent example is by Mario Rizzo.

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.)

Lean, mean DSGE machines?

Reading the recent characterizations of Ph.D. education in our top departments, one would conclude that all one ever learned in a program is how to write out and calibrate dynamic stochastic general equilibrium (DSGE) models, or for the older among us, calibrate a real business cycle model. I have to say that this all seems a little like an all too convenient caricature (and, as I have said repeatedly in the past, these types of models have led to important insights for issues *besides* crises [4]).

I won’t deny that in the past 20 years, I haven’t seen more than a few models that struck me as pretty irrelevant for analysis of real world issues. But I think that some mathematical training, and the use of models, is essential to economic analysis. After all, one can think of completely irrelevant frameworks for looking at the world even without a model, just as one can with a model.

Furthermore, perhaps my experience in a Ph.D. program is atypical but I don’t remember being forced into a particular mode of analysis in writing my dissertation (University of California, Berkeley, 1985-1991). In macro/international/econometrics, my teachers included Roger Craine, George Akerlof, Jeffrey Frankel, Andy Rose, and Richard Meese. We studied Euler equations as well as the market for lemons. We knew what Arrow-Debreu markets were, but we also learned about the Great Depression (from Bernanke’s paper as well as Friedman and Schwartz). The time series econometrics taught did not presuppose optimizing behavior. We even studied models with sticky prices (gasp!). Doesn’t sound too doctrinaire to me.

So what was a common theme in the curriculum? For me, the defining feature in thinking about what model to use was whether the analysis answered the question posed, and whether the question posed was of interest. Now, whenever I read a dissertation prospectus, the key question I ask the student is: “What is the question being asked?”, not “What is the methodology?” (Admittedly, the subdisciplines have different “characters”, as alluded to by Paul Krugman; my focus was open economy macroeconomics, rather than macroeconomics/monetary economics.).

How monolithic?

I wonder if indeed the macroeconomic mainstream is as monolithic as conveyed by various observers. For instance, one certainly perceives a certain homogeneity amongst Ph.D.’s trained at certain universities. And there’s a certain similarity in the mode of analysis preferred by economists in financial firms. Since the financial press tends to focus on Wall Street economists, one gets a misleading impression regarding the degree of uniformity of views.

To make this more concrete, let’s consider whether academic economists differ in their views regarding the economy, as compared to those in the financial sector. I have some indirect evidence, pulled from Dilbert’s survey of economists in the American Economics Association (see also [5]). Scott Adams, with the assistance of Joshua Libresco of the OSR Group, was kind enough to have the stats pulled. Last summer, academic economists believed that a President Obama administration would promise more progress on the economy than a McCain administration, by a 2 to 1 margin (n=314); in contrast financial sector economists were equally split. The sample in the latter case is quite small (n=29) (I dropped the undecided/no difference responses). Nonetheless, a difference in means test (recalling the variance of a binomial is (1/4)/n) rejects the null hypothesis of equality at 6%, using a two tailed test.

(As an aside, this finding further suggests that when the *WSJ* says most economist oppose a second stimulus, that probably characterizes Wall Street economists better than all AEA economists. Even for Wall Street economists, it’s interesting to note that a majority of economists feel the stimulus package has already improved economics prospects, and will have a bigger impact in subsequent months. Hence, opposition to a second stimulus among WSJ-surveyed economists is not necessarily rooted in skepticism about the aggregate demand enhancing effect of the ARRA. (One would need a cross-tabulation of responses to verify that assertion.))

Concluding thoughts:

If my conjecture is correct, then the supposed failure of macroeconomics is more the failure of macroeconomics as described in the popular press, rather than of the discipline itself (after all, Joseph Stiglitz is as much of the economics discipline, if not more, than Eugene Fama.) My conclusion: Not quite time to jettison the apparatus of modern macroeconomics.

For a less personal perspective, see Brad Delong and Paul Krugman, as well as my April post on “macroeconomic schisms”.

Update 9am 7/21: See also Mark Thoma’s observations.

Originally published at Econbrowser and reproduced here with the author’s permission.

I am a Biologist(computational) and was previously a Mechanical Engineer. Of course I have a great respect for the power of equations.In Comp. Biology all structuring is done on Probability and Statistics-there is not the certitude of Differential Equations. Actually we are only trying to wrestle with a chaotic universe of data sets and make some sense of it.In Mechanical Engineering, the Navier-Stokes Fluid Flow Equation comes up in Fluid Dynamics, an important topic. We regularly arrow some of the terms to ZERO and thus reduce the equation to a very simple entity.I am totally in disagreement with economics, as a science, simply because none of you ACTUALLY has a guess as to the number of possible variables entering into ANY important equation. And, as a stupid non-economist I fail to see how an equation could be valid in the slightest if the variables are not known. What are you calculating??? Seat of the pants guesstimates seem to be about as accurate as econometric predictions.and Yes, my cousin pupped at Univ. of Chicago Bus. School, 1979 (MBA) And after graduating proudly bragged to me that if he was given sound data on 5 econometric variables he could predict economic behaviour 12 months hence. Now he works for the Pentagon.