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

Bang-Qiang He, Xing-Jian Hong and Guo-Liang Fan

Statistics & Probability Letters, 2017, vol. 123, issue C, 128-138

Abstract: 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.

Keywords: Block empirical likelihood; Partially linear model; Panel data; Fixed effect (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.spl.2016.11.021

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