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Measures of Fit for Calibrated Models

Mark W. Watson^1,2,3

¹ Princeton Public Schools · ² Princeton University · ³ National Bureau of Economic Research

This paper suggests a new procedure for evaluating the fit of a dynamic structural economic model. The procedure begins by augmenting the variables in the model with just enough stochastic error so that the model can exactly match the second moments of the actual data. Measures of fit for the model can then be constructed on the basis of the size of this error. The procedure is applied to a standard real business cycle model. Over the business cycle frequencies, the model must be augmented with a substantial error to match data for the postwar U.S. economy. Lower bounds on the variance of the error range from 40 percent to 60 percent of the variance in the actual data.

DOI

10.1086/261913

Volume

101 (6)

Pages

1011-1041

Language

en

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BibTeX

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