Small-sample properties of GMM for business-cycle analysis

Lawrence J. Christiano, Wouter J. Den Haan

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)309-327
Number of pages19
JournalJournal of Business and Economic Statistics
Issue number3
StatePublished - Jul 1996


  • Covariance matrix estimation
  • Finite-sample analysis
  • Hypothesis testing
  • Monte Carlo simulation
  • Prewhitening
  • Spectral density

ASJC Scopus subject areas

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Small-sample properties of GMM for business-cycle analysis'. Together they form a unique fingerprint.

Cite this