Block empirical likelihood for partially linear panel data models with fixed effects

被引:7
|
作者
He, Bang-Qiang [1 ]
Hong, Xing-Jian [2 ]
Fan, Guo-Liang [1 ]
机构
[1] Anhui Polytech Univ, Sch Math & Phys, Wuhu 241000, Peoples R China
[2] Zhejiang Univ Finance & Econ, Sch Data Sci, Hangzhou 310018, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Block empirical likelihood; Partially linear model; Panel data; Fixed effect; NONPARAMETRIC-ESTIMATION; INFERENCE;
D O I
10.1016/j.spl.2016.11.021
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 consider a partially linear panel data models with fixed effects. In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to partially linear panel data models with fixed effects, and prove a nonparametric version of Wilks' theorem which can be used to construct the confidence region for the parametric. By the block empirical likelihood ratio function, the maximum empirical likelihood estimator of the parameter is defined and the asymptotic normality is shown. A simulation study and a real data application are undertaken to assess the finite sample performance of our proposed method. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:128 / 138
页数:11
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