Small-sample properties of GMM for business-cycle analysis

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.