Calibration as Estimation

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Abstract
One aspect of calibration in macroeconomics is the notion that free parameters of models should be chosen by matching certain moments of the simulated models with those of actual data. We formally examine this notion by treating the process of calibration as an econometric estimator. A numerical version of the Mehra-Prescott (1985) economy is the setting for an evaluation of calibration estimators via Monte Carlo methods. While these estimators sometimes have reasonable finite-sample properties they are not robust to mistakes in setting non-free parameters. In contrast, generalized method of moments (GMM) estimators have satisfactory finite-sample properties, quick convergence, and informational requirements less stringent than those of consistent calibration estimators. In dynamic equilibrium models in which GMM is infeasible we offer some suggestion for improving estimates based on calibration methodology.

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