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Small-Sample Properties of GMM for Business-Cycle Analysis

Lawrence J. Christiano and Wouter J. den Haan
Journal of Business & Economic Statistics
Vol. 14, No. 3 (Jul., 1996), pp. 309-327
DOI: 10.2307/1392445
Stable URL: http://www.jstor.org/stable/1392445
Page Count: 19
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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.

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