Oxford Economic Papers 47 (1995), 24-44
FACTS AND ARTIFACTS: CALIBRATION AND THE EMPIRICAL ASSESSMENT OF REAL-BUSINESS-CYCLE MODELS
By KEVIN D. HOOVER
Department of Economics, University of California, Davis, California 95616-8578, USA
THE RELATIONSHIP between theory and data has been, from the beginning, a central concern of the new-classical macroeconomics. This much is evident in the title of Robert E. Lucas’s and Thomas J. Sargent’s landmark edited volume, Rational Expectations and Econometric Practice (1981). With the advent of real-business-cycle models, many new classical economists have turned to calibration methods. The new classical macroeconomics is now divided between calibrators and estimators. But the debate is not a parochial one, raising, as it does, issues about the relationships of models to reality and the nature of econometrics that should be important to every school of macroeconomic thought, indeed to all applied economics. The stake in this debate is the future direction of quantitative macroeconomics. It is, therefore, critical to understand the root issues.
Lucas begins the second chapter of his Models of Business Cycles with the remark:
Discussions of economic policy, if they are to be productive in any practical sense, necessarily involve quantitative assessments of the way proposed policies are likely to affect resource allocation and individual welfare. (Lucas 1987, p. 6; emphasis added)
This might appear to be a clarion call for econometric estimation. But appearances are deceiving. After mentioning Sumru Altug’s (1989) estimation and rejection of the validity of a variant of Finn E. Kydland and Edward C. Prescott’s (1982) real-business-cycle model (a model which takes up a large portion of his book), Lucas writes:
…the interesting question is surely not whether [the real-business-cycle model] can be accepted as ‘true’ when nested within some broader class of models. Of course the model is not ‘true’: this much is evident from the axioms on which it is constructed. We know from the onset in an enterprise like this (I would say, in any effort in positive economics) that what will emerge—at best—is a workable approximation that is useful in answering a limited set of questions. (Lucas 1987, p. 45)
Lucas abandons not only truth but also the hitherto accepted standards of empirical economics. Models that clearly do not fit the data, he argues, may nonetheless be calibrated to provide useful quantitative guides to policy.
Calibration techniques are commonly applied to so-called ‘computable general-equilibrium’ models. They were imported into macroeconomics as a
© Oxford University Press 1995