A diagnostic criterion for approximate factor structure

Patrick Gagliardini, Elisa Ossola () and Olivier Scaillet

Journal of Econometrics, 2019, vol. 212, issue 2, 503-521

Abstract: 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 (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 C51 C52 C58 G12 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

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Related works:
Working Paper: A diagnostic criterion for approximate factor structure (2017)
Working Paper: A Diagnostic Criterion for Approximate Factor Structure (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:212:y:2019:i:2:p:503-521

DOI: 10.1016/j.jeconom.2019.06.001

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