Estimation of a censored regression panel data model using conditional moment restrictions efficiently

摘要

Honore has introduced a semiparametric estimator for the censored regression panel data model with fixed individual effects. Newey has shown how to obtain efficient estimators under a give conditional moment restriction. We apply Newey's approach to obtain a two-step GM estimator which is more efficient than the Honore estimator. We compare this estimator to the Honore estimator and to parametric estimators including Chamberlain's quasi-fixed effects estimator in a Monte Carlo experiment. We also extend the Honore Estimator and the two-step GMM estimator to the case of a balanced or unbalanced panel of more than two waves. We apply the estimators to an empirical example concerning earnings of married females, using data from the Dutch Socio-Economic Panel.