Seminonparametric maximum likelihood estimation of conditional moment restriction models

• 成果类型: Article
• 署名作者: Ai, Chunrong
• 署名单位: State University System of Florida; University of Florida; Shanghai University of Finance & Economics
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/j.1468-2354.2007.00456.x
• 发表日期: 2007
• 页码: 1093-1118
• 关键词: empirical likelihood; generalized-method; convergence-rates; tests; EFFICIENCY; inference; normality; gmm

摘要

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 theta 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 theta estimator is presented.