Inferences on the regression coefficients in panel data models: parametric bootstrap approach

Abstract

AbstractThis article presents a parametric bootstrap approach to inference on the regression coefficients in panel data models. We aim to propose a method that is easily applicable for implement hypothesis testing and construct confidence interval of the regression coefficients vector of balanced and unbalanced panel data models. We show the results of our simulation study to compare of our parametric bootstrap approach with other approaches and approximated methods based on a Monte Carlo simulation study.