Small Sample Properties of GMM for Business Cycle Analysis

50 Pages Posted: 11 Jul 2000 Last revised: 28 Jun 2023

See all articles by Lawrence J. Christiano

Lawrence J. Christiano

Northwestern University; Federal Reserve Bank of Cleveland; Federal Reserve Bank of Chicago; Federal Reserve Bank of Minneapolis; National Bureau of Economic Research (NBER)

Wouter J. den Haan

University of Amsterdam; Centre for Economic Policy Research (CEPR); Tinbergen Institute

Date Written: March 1995

Abstract

We investigate, by Monte Carlo methods, the finite sample properties of GMM 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.

Suggested Citation

Christiano, Lawrence J. and Den Haan, Wouter J., Small Sample Properties of GMM for Business Cycle Analysis (March 1995). NBER Working Paper No. t0177, Available at SSRN: https://ssrn.com/abstract=225087

Lawrence J. Christiano (Contact Author)

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Wouter J. Den Haan

University of Amsterdam ( email )

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Centre for Economic Policy Research (CEPR)

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Tinbergen Institute ( email )

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