Unexplained factors and their effects on second pass R-squared’s

By F. Kleibergen, Zhaoguo Zhan. 2015

69 citations recorded by the source corpus.

We construct the large sample distributions of the OLS and GLS R2’s of the second pass regression of the Fama and MacBeth (1973) two pass procedure when the observed proxy factors are minorly correlated with the true unobserved factors. This implies an unexplained factor structure in the first pass residuals and, consequently, a large estimation error in the estimated beta’s which is spanned by the beta’s of the unexplained true factors. The average portfolio returns and the estimation error of the estimated beta’s are then both linear in the beta’s of the unobserved true factors which leads to possibly large values of the OLS R2 of the second pass regression. These large values of the OLS R2 are not indicative of the strength of the relationship. Our results question many empirical findings that concern the relationship between expected portfolio returns and (macro-) economic factors.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/30a6ed3211dd983157f109b5ac26ccd00634f72e

Citations in the corpus

• Robust Inference for Consumption‐Based Asset Pricing (2019, unknown): “Moreover, Kan and Zhang (1999b), Lewellen, Nagel, and Shanken (2010), and Kleibergen and Zhan (2015, 2018) provide intuitive explanations for why poor quality risk factors can induce seemingly promising empirical outcomes.”