Estimation in Single-Index Panel Data Models with Heterogeneous Link Functions

被引:14
|
作者
Chen, Jia [1 ,2 ]
Gao, Jiti [1 ]
Li, Degui [1 ]
机构
[1] Monash Univ, Dept Econometr & Business Stat, Melbourne, Vic 3145, Australia
[2] Univ Queensland, Sch Math, Brisbane, Qld, Australia
基金
澳大利亚研究理事会;
关键词
Asymptotic distribution; Local linear smoother; Minimum average variance estimation; Panel data; Semiparametric estimation; Single-index models; C14; C32; C33; NONPARAMETRIC-ESTIMATION; SEMIPARAMETRIC ESTIMATION; TIME-SERIES; IDENTIFICATION; ERGODICITY; REGRESSION;
D O I
10.1080/07474938.2012.690687
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this article, we study semiparametric estimation for a single-index panel data model where the nonlinear link function varies among the individuals. We propose using the refined minimum average variance estimation method to estimate the parameter in the single-index. As the cross-section dimension N and the time series dimension T tend to infinity simultaneously, we establish asymptotic distributions for the proposed estimator. In addition, we provide a real-data example to illustrate the finite sample behavior of the proposed estimation method.
引用
收藏
页码:928 / 955
页数:28
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