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Seminonparametric Maximum Likelihood Estimation Of Conditional Moment Restriction Models

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  • Chunrong Ai

Abstract

This article studies estimation of a conditional moment restriction model with the seminonparametric maximum likelihood approach proposed by Gallant and Nychka ("Econometrica" 55 (March 1987), 363-90). Under some sufficient conditions, we show that the estimator of the finite dimensional parameter θ is asymptotically normally distributed and attains the semiparametric efficiency bound and that the estimator of the density function is consistent under "L" 2 norm. Some results on the convergence rate of the estimated density function are derived. An easy to compute covariance matrix for the asymptotic covariance of the θ estimator is presented. Copyright 2007 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.

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  • Chunrong Ai, 2007. "Seminonparametric Maximum Likelihood Estimation Of Conditional Moment Restriction Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1093-1118, November.
    • Handle: RePEc:ier:iecrev:v:48:y:2007:i:4:p:1093-1118
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    Cited by:

    1. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.

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