The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Generalized Method of Moments Estimation

  • Lars Peter Hansen
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2486

Abstract

Generalized method of moments estimates econometric models without requiring a full statistical specification. One starts with a set of moment restrictions that depend on data and an unknown parameter vector to be estimated. When there are more moment restrictions than underlying parameters, there is family of such estimators. The tractable form of the large sample properties of this family facilitates efficient estimation and statistical testing. This article motivates the method, presents some of the underlying statistical properties, and discusses implementation.

Keywords

Calibration Central limit theorems Gauss–Markov theorem Generalized method of moments Identification Instrumental variables Lagrange multipliers Law of large numbers Likelihood Martingales Maximum likelihood Rational expectations models Sequential estimation Statistical inference Stochastic discount factor models Wald test 

JEL Classifications

C10 
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Notes

Acknowledgments

I greatly appreciate comments from Lionel Melin, Monika Piazzesi, Grace Tsiang, and Francisco Vazquez-Grande. This material is based upon work supported by the National Science Foundation under Award Number SES0519372.

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© Macmillan Publishers Ltd. 2018

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  • Lars Peter Hansen

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