In this article, I offer some comments on the role of econometrics in macroeconomics.(1) These reflect a specific perspective: The role of econometrics ought to be the advancement of empirically plausible economic theory. This is a natural perspective for any economist to take, but it is one that is particularly compelling for a macroeconomist. Lucas' (1976) critique of econometric policy evaluation aside, it seems obvious that most policy questions cannot be fruitfully addressed using traditional quasi-reduced form econometric models. In the end, there are no alternatives to the use of fully specified general equilibrium models for addressing many of the problems that interest macroeconomists.
The real issue is: Different fully specified general equilibrium models can generate very different answers to the same question. Indeed it is possible to work backwards from any answer to some model. So given a particular question, which model should a macroeconomist use? Developing the tools to answer this question is the key challenge facing econometricians. Because all models are wrong along some dimension, the classic Haavelmo (1944) program of testing whether models are "true" will not be useful in meeting this challenge.(2) We do not need high-powered econometrics to tell us that models are false. We know that. What we need to know are the dimensions along which a given model does well and the dimensions along which it does poorly. In Leamer's (1978) terminology, we need a workable version of "specimetrics" that is applicable to dynamic general equilibrium models.(3) Developing the diagnostic tools for this specimetrics program ought to be the primary occupation of econometricians, not developing ever-increasingly sophisticated tools for implementing the Haavelmo program.
The need for progress on this front is pressing. General equilibrium business cycle analysts have begun to move beyond their initial practice of assessing models on a small set of moments without a formal statistical methodology.(4) Real business cycle (RBC) theory is evolving to accommodate a wide variety of impulses to the business cycle, including shocks to fiscal and monetary policy. But the process is in its infancy. The ultimate success of the enterprise will depend on the willingness of econometricians to devote more energy to the development of diagnostic tools for structural models and less to the development of estimators for the parameters of reduced form systems and increasingly powerful tests of null hypotheses, such as 'The model is a literal description of the data-generating mechanism'.
What is at stake for econometricians in all this? Why should they care about the needs of macroeconomists? Because, as social scientists, their product has to meet a market test. There is no point in producing elegant merchandise that is buried in the inventory of advanced econometrics textbooks. Unfortunately, this happens all too often. To many young macro-economists, econometrics seems irrelevant.(5) To remedy the situation, econometricians need to write instruction manuals for their products in a language that their customers understand. The language of economists centers on objects like agents' criterion functions, information sets, and constraints.(6) Consequently, econometricians need to focus their efforts on developing tools to obtain information about those objects. To the extent that they concentrate on analyzing the parameters of reduced form representations of the data or devising tests of whether specific structural models are false, their output is likely to be ignored by most of their (macro) colleagues.
This is not to suggest that there is no room for specialization in research or that econometricians should not engage in basic research and development. No one knows in advance which tools will be valuable in applied research. Still, the paradigm within which econometricians operate affects the types of tools they are likely to develop. …