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Semiparametric Quantile Regression Estimation in Dynamic Models with Partially Varying Coefficients

id：2114 时间：20131014 status：published 点击数：
杂志Journal of Econometrics   
作者Zongwu Cai, Zhijie Xiao
正文We study quantile regression estimation for dynamic models with partially varying coefficients so that the values of some coefficients may be functions of informative covariates. Estimation of both parametric and nonparametric functional coefficients are proposed. In particular, we propose a three stage semiparametric procedure. Both consistency and asymptotic normality of the proposed estimators are derived. We demonstrate that the parametric estimators are root-n consistent and the estimation of the functional coefficients is oracle. In addition, efficiency of parameter estimation is discussed and a simple efficient estimator is proposed. A simple and easily implemented test for the hypothesis of varying-coefficient is proposed. A Monte Carlo experiment is conducted to evaluate the performance of the proposed estimators.
JEL-Codes：
关键词：Efficiency; nonlinear time series; partially linear; partially varying coefficients; quantile regression; semiparametric.
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