Semiparametric estimation of a partially linear censored regression model

被引:31
作者
Chen, SN
Khan, S [1 ]
机构
[1] Univ Rochester, Dept Econ, Rochester, NY 14627 USA
[2] Hong Kong Univ Sci & Technol, Hong Kong, Hong Kong, Peoples R China
关键词
D O I
10.1017/S0266466601173032
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this paper we propose an estimation procedure for a censored regression model where the latent regression function has a partially linear form. Based on a conditional quantile restriction, we estimate the model by a two stage procedure. The first stage nonparametrically estimates the conditional quantile function at in-sample and appropriate out-of-sample points, and the second stage involves a simple weighted least squares procedure. The proposed procedure is shown to have desirable asymptotic properties under regularity conditions that are standard in the literature. A small scale simulation study indicates that the estimator performs well in moderately sized samples.
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页码:567 / 590
页数:24
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