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

Abstract

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 α-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.