Small sample properties of GMM for business cycle analysis
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.Download Info
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Paper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 199.Length:
Date of creation: 1995
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Handle: RePEc:fip:fedmsr:199
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Keywords: Business cycles;Other versions of this item:
- Chistiano, Lawrence J & den Haan, Wouter J, 1996. "Small-Sample Properties of GMM for Business-Cycle Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 309-27, July.
- Lawrence J. Christiano & Wouter J. Den Haan, 1995. "Small Sample Properties of GMM for Business Cycle Analysis," NBER Technical Working Papers 0177, National Bureau of Economic Research, Inc.
- Lawrence J. Christiano & Wouter den Haan, 1995. "Small sample properties of GMM for business cycle analysis," Working Paper Series, Macroeconomic Issues 95-3, Federal Reserve Bank of Chicago.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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