Empirical likelihood for semi-varying coefficient models for panel data with fixed effects

The empirical likelihood inference for semi-varying coefficient models for panel data with fixed effects is investigated in this paper. We propose an empirical log-likelihood ratio function for the regression parameters in the model under alpha-mixing condition. The empirical log-likelihood ratio is proven to be asymptotically chi-squared. We also obtain the maximum empirical likelihood estimator of the parameters of interest, and prove that it is the asymptotically normal under some suitable conditions. A simulation study and a real data application are undertaken to assess the finite sample performance of our proposed method. (C) 2016 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.