A Diagnostic Criterion for Approximate Factor Structure
Published in Journal of Econometrics
85 Pages Posted: 3 Aug 2016 Last revised: 18 Sep 2019
Date Written: January 1, 2018
We build a simple diagnostic criterion for approximate factor structure in large panel datasets. Given observable factors, the criterion checks whether the errors are weakly cross-sectionally correlated or share at least one unobservable common factor (interactive effects). A general version allows to determine the number of omitted common factors also for time-varying structures. The empirical analysis runs on ten thousand US stocks from January 1968 to December 2011. For monthly returns, we select time-invariant specifications with at least four financial factors, and a scaled three-factor specification. For quarterly returns, we cannot select macroeconomic models without the market factor.
Keywords: large panel, approximate factor model, asset pricing, model selection, interactive fixed effects
JEL Classification: C12, C13, C23, C51, C52, C58, G12
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