Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/70717 
Year of Publication: 
2009
Series/Report no.: 
Working Paper No. 2009-12
Publisher: 
Federal Reserve Bank of Atlanta, Atlanta, GA
Abstract: 
Since Black, Jensen, and Scholes (1972) and Fama and MacBeth (1973), the two-pass cross-sectional regression (CSR) methodology has become the most popular tool for estimating and testing beta asset pricing models. In this paper, we focus on the case in which simple regression betas are used as regressors in the second-pass CSR. Under general distributional assumptions, we derive asymptotic standard errors of the risk premia estimates that are robust to model misspecification. When testing whether the beta risk of a given factor is priced, our misspecification robust standard error and the Jagannathan and Wang (1998) standard error (which is derived under the correctly specified model) can lead to different conclusions.
Subjects: 
two-pass cross-sectional regressions
risk premia
model misspecification
simple regression betas
multivariate betas
JEL: 
G12
Document Type: 
Working Paper

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