Fama–MacBeth regression

The Fama-Macbeth regression is a method used to estimate parameters for asset pricing models such as the Capital asset pricing model (CAPM). The method estimates the betas and risk premia for any risk factors that are expected to determine asset prices. The method works with multiple assets across time (panel data). The parameters are estimated in two steps:

1. First regress each asset against the proposed risk factors to determine that asset's beta for that risk factor.
2. Then regress all asset returns for a fixed time period against the estimated betas to determine the risk premium for each factor.

Eugene F. Fama and James D. MacBeth (1973) demonstrated that the residuals of risk-return regressions and the observed "fair game" properties of the coefficients are consistent with an "efficient capital market" (quotes in the original).

Note that Fama MacBeth regressions provide standard errors corrected only for cross-sectional correlation. The standard errors from this method do not correct for time-series correlation. This is usually not a problem for asset returns since they have little time series correlation. This means Fama MacBeth regressions are inappropriate to use in many corporate finance settings. For alternative methods of correcting standard errors for time series and cross-sectional correlation in the error term see: double clustering by firm and year. See Mitch Petersen's (Northwestern) paper on this topic.

References

• "EconTerms - Glossary of Economic Research "Fama-MacBeth Regression"". http://econterms.com/glossary.cgi?action=++Search++&query=Fama-Macbeth+regression. Retrieved --02:38, 2 November 2006 (UTC).