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Proofs for large sample properties of generalized method of moments estimators

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  • Hansen, Lars Peter

Abstract

I present proofs for the consistency of generalized method of moments (GMM) estimators presented in Hansen (1982). Some basic approximation results provide the groundwork for the analysis of a class of such estimators. Using these results, I establish the large sample convergence of GMM estimators under alternative restrictions on the estimation problem.

Suggested Citation

  • Hansen, Lars Peter, 2012. "Proofs for large sample properties of generalized method of moments estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 325-330.
  • Handle: RePEc:eee:econom:v:170:y:2012:i:2:p:325-330 DOI: 10.1016/j.jeconom.2012.05.008
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    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
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    Cited by:

    1. Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.
    2. Olayide, Olawale Emmanuel & Tetteh, Isaac Kow & Popoola, Labode, 2016. "Differential impacts of rainfall and irrigation on agricultural production in Nigeria: Any lessons for climate-smart agriculture?," Agricultural Water Management, Elsevier, vol. 178(C), pages 30-36.
    3. McKenzie Jordi & Walls W. David, 2016. "File Sharing and Film Revenues: Estimates of Sales Displacement at the Box Office," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 16(1), pages 25-57, January.

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