A weighted Fama-MacBeth two-step panel regression procedure

摘要

We propose a weighted Fama-MacBeth (FMB) two-step panel regression procedure and compare the properties of the usual unweighted versus our proposed weighted FMB procedures through a Monte Carlo simulation study. We find evidence that when the cross-sectional regression explanatory power changes over time as well as the standard errors of the coefficient estimates, the proposed weighted FMB procedure produces more efficient coefficient estimators and more powerful tests compared to the usual unweighted FMB procedure across various model specifications in terms of the sampling distribution, sample size, and time-series distribution.