A0252
Title: Empirical likelihood based testing device for a semiparametric panel data model with cross-sectional dependence
Authors: Luis Antonio Arteaga Molina - Universidad de Cantabria (Spain) [presenting]
Juan Manuel Rodriguez-Poo - Universidad de Cantabria (Spain)
Abstract: Empirical-likelihood-based inference for nonparametric panel data models with cross-sectional dependence is investigated. A common factor structure is used to characterize the cross-sectional dependence. The empirical likelihood is employed to formulate a functional form specification test. The procedure is based on a comparison with kernel smoothing estimators. To obtain the estimators, an empirical likelihood ratio is first developed to obtain a maximum empirical likelihood local linear common correlated effects estimator. To show the feasibility of the technique and to analyze its small sample properties, a Monte Carlo simulation exercise is implemented, and the proposed technique is also illustrated in an empirical analysis of the environmental Kuznets curve hypothesis.
