Fama-MacBeth Two-Pass Regressions: Improving Risk Premia Estimates
15 Pages Posted: 10 Apr 2015 Last revised: 22 Aug 2015
Date Written: June 2015
In this paper, we provide the asymptotic theory for the widely used Fama and MacBeth (1973) two-pass regression in the usual case of a large number of assets. We find that the convergence of the OLS two-pass estimator depends critically on the time series sample size in addition to the number of cross-sections. To accommodate typical relatively small time series length, we propose new OLS and GLS estimators that improve the small sample performances significantly.
Keywords: Fama and MacBeth; two-pass regression; cross section; risk premia
JEL Classification: G11, G14
Suggested Citation: Suggested Citation