Estimation for Partially Linear Single-index Instrumental Variables Models

被引:4
|
作者
Zhou, Yousheng [1 ,4 ]
Yang, Yiping [2 ]
Han, Jian [3 ]
Zhao, Peixin [2 ]
机构
[1] Chongqing Univ Posts & Telecommun, Coll Comp Sci & Technol, Chongqing, Peoples R China
[2] Chongqing Technol & Business Univ, Coll Math & Stat, Chongqing, Peoples R China
[3] Zhongnan Univ Econ & Law, Sch Finance & Taxat, Wuhan, Peoples R China
[4] Dublin City Univ, Sch Elect Engn, Dublin, Ireland
基金
中国国家自然科学基金;
关键词
Endogenous variables; Instrumental variables; Local linear smoother; Partially linear single-index model; 62G05; 62G20; EMPIRICAL LIKELIHOOD; NONPARAMETRIC MODELS; LONGITUDINAL DATA; INFERENCE; REGRESSION;
D O I
10.1080/03610918.2014.950745
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this article, we generalize the partially linear single-index models to the scenario with some endogenous covariates variables. It is well known that the estimators based on the existing methods are often inconsistent because of the endogeneity of covariates. To deal with the endogenous variables, we introduce some auxiliary instrumental variables. A three-stage estimation procedure is proposed for partially linear single-index instrumental variables models. The first stage is to obtain a linear projection of endogenous variables on a set of instrumental variables, the second stage is to estimate the link function by using local linear smoother for given constant parameters, and the last stage is to obtain the estimators of constant parameters based on the estimating equation. Asymptotic normality is established for the proposed estimators. Some simulation studies are undertaken to assess the finite sample performance of the proposed estimation procedure.
引用
收藏
页码:3629 / 3642
页数:14
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