Ray Fair recently posted a very interesting commentary on the macroeconomics dust-up between Lucas/Sargent and Solow as described by Paul Romer and commented upon by many others. His position is interesting: he represents the Old Guard of macroeconomics who works with what are variously called Structural Econometric Models or Cowles Commission models.

I am one of the few academics who has continued to work with CC models. They were rejected for basically three reasons: they do not assume rational expectations (RE), they are not identified, and the theory behind them is ad hoc. This sounds serious, but I think it is in fact not.

The whole post is worth reading, but I find it useful because it highlights (perhaps not purposefully) very different ways of conceiving of the relationship between theory and data. One might view the CC tradition as an attempt to start with data and then use theory to put structure on that data. The criticism, then, is that theories are ad hoc.

The alternative in the RBC and DSGE traditions is to start with rigorous theory, often one built on a representative agent. The criticism of RBC is that the theories may be internally consistent, but they don’t describe reality very well without ad hoc additions. As a non-specialist, I interpret the disagreement between RBC and DSGE as lying primarily in what kinds of ad hoc additions are permissible. See Delong for a typically pointed description. Of course, I cannot rule out the claim that RBC and DSGE traditions differ because people working these traditions need models that support their policy preferences.

Obviously this is simplifying mightily. But taking a look at a CC model, it is easy to see why a causal observer might miss the theory (e.g. this recent Fair paper). And looking at a RBC model (e.g. this McGrattan and Prescott paper), it obvious that theory comes first.

This makes Milton Friedman’s comments on assumptions and predictions all the more interesting.

…a theory cannot be tested by comparing its “assumptions” directly with “reality.” Indeed, there is no meaningful way in which this can be done. Complete “realism” is clearly unattainable, and the question whether a theory is realistic “enough” can be settled only by seeing whether it yields predictions that are good enough for the purpose in hand or that are better than predictions from alternative theories. Yet the belief that a theory can be tested by the realism of its assumptions independently of the accuracy of its predictions is widespread and the source of much of the perennial criticism of economic theory as unrealistic. Such criticism is largely irrelevant, and, in consequence, most attempts to reform economic theory that it has stimulated have been unsuccessful.

Perhaps someone in Fair’s tradition would hold that the assumptions of a theory are just as likely to be identifying assumptions in a simultaneous equations model as they are to optimizing assumptions in a representative agent model.