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Applications of Generalized Method of Moments Estimation

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  • Jeffrey M. Wooldridge

Abstract

I describe how the method of moments approach to estimation, including the more recent generalized method of moments (GMM) theory, can be applied to problems using cross section, time series, and panel data. Method of moments estimators can be attractive because in many circumstances they are robust to failures of auxiliary distributional assumptions that are not needed to identify key parameters. I conclude that while sophisticated GMM estimators are indispensable for complicated estimation problems, it seems unlikely that GMM will provide convincing improvements over ordinary least squares and two-stage least squares--by far the most common method of moments estimators used in econometrics--in settings faced most often by empirical researchers.

Suggested Citation

  • Jeffrey M. Wooldridge, 2001. "Applications of Generalized Method of Moments Estimation," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 87-100, Fall.
    • Handle: RePEc:aea:jecper:v:15:y:2001:i:4:p:87-100
    Note: DOI: 10.1257/jep.15.4.87
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    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/jep.15.4.87
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    References listed on IDEAS

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    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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