A Monte Carlo Evaluation of the Efficiency of the PCSE Estimator

Panel data characterized by groupwise heteroscedasticity, cross-sectional correlation, and AR(1) serial correlation pose problems for econometric analyses. It is well known that the asymptotically efficient, FGLS estimator (Parks) sometimes performs poorly in finite samples. In a widely cited paper, Beck and Katz (1995) claim that their estimator (PCSE) is able to produce more accurate coefficient standard errors without any loss in efficiency in ¡°practical research situations.¡± This study disputes that claim. We find that the PCSE estimator is usually less efficient than Parks -- and substantially so -- except when the number of time periods is close to the number of cross-sections.