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

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• 作者：Bang-Qiang He^a ; Xing-Jian Hong^b ; ^{myemailh@126.com} ; Guo-Liang Fan^a
• 关键词：62G15 ; 62G20
• 刊名：Statistics & Probability Letters
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：123
• 期：Complete
• 页码：128-138
• 全文大小：469 K
• 卷排序：123

文摘

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.