JOURNAL ARTICLE

SEMINONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF CONDITIONAL MOMENT RESTRICTION MODELS*

Chunrong Ai

Year: 2007 Journal:   International Economic Review Vol: 48 (4)Pages: 1093-1118   Publisher: Wiley

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.

Keywords:
Mathematics Estimator Moment (physics) Applied mathematics Covariance Efficient estimator Conditional variance Likelihood function Rate of convergence Covariance matrix Consistent estimator Statistics Minimum-variance unbiased estimator Estimation theory Econometrics Computer science Physics

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Citation History

Topics

Monetary Policy and Economic Impact
Social Sciences →  Economics, Econometrics and Finance →  General Economics, Econometrics and Finance
Economic Policies and Impacts
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
Spatial and Panel Data Analysis
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics

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Seminonparametric Conditional Density Models

Year: 2006 Pages: 847-922
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