Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/101040
Authors: 
Gospodinov, Nikolay
Kan, Raymond
Robotti, Cesare
Year of Publication: 
2013
Series/Report no.: 
Working Paper, Federal Reserve Bank of Atlanta 2013-9
Abstract: 
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.
Subjects: 
asset pricing models
lack of identification
model misspecification
GMM estimation
JEL: 
G12
C12
C52
Document Type: 
Working Paper

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