Misspecification-Robust Inference in Linear Asset Pricing Models with Irrelevant Risk Factors
87 Pages Posted: 22 Mar 2015
Date Written: October 2013
We show that in misspecified models with useless factors (for example, factors that are independent of the returns on the test assets), the standard inference procedures tend to erroneously conclude, with high probability, that these irrelevant factors are priced and the restrictions of the model hold. Our proposed model selection procedure, which is robust to useless factors and potential model misspecification, restores the standard inference and proves to be effective in eliminating factors that do not improve the model's pricing ability. The practical relevance of our analysis is illustrated using simulations and empirical applications.
Keywords: asset pricing models, lack of identification, model misspecification, GMM estimation
JEL Classification: G12, C12, C52
Suggested Citation: Suggested Citation