Small-Sample Properties of GMM for Business-Cycle Analysis

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Abstract
We investigate, by Monte Carlo methods, the finite-sample properties of generalized method of moment procedures for conducting inference about statistics that are of interest in the business-cycle literature. These statistics include the second moments of data filtered using the first-difference and Hodrick–Prescott filters, and they include statistics for evaluating model fit. Our results indicate that, for the procedures considered, the existing asymptotic theory is not a good guide in a sample the size of quarterly postwar U.S. data.