Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/216542 
Year of Publication: 
2020
Series/Report no.: 
CESifo Working Paper No. 8146
Publisher: 
Center for Economic Studies and ifo Institute (CESifo), Munich
Abstract: 
This paper proposes an estimator of factor strength and establishes its consistency and asymptotic distribution. The proposed estimator is based on the number of statistically significant factor loadings, taking account of the multiple testing problem. We focus on the case where the factors are observed which is of primary interest in many applications in macroeconomics and finance. We also consider using cross section averages as a proxy in the case of unobserved common factors. We face a fundamental factor identification issue when there are more than one unobserved common factors. We investigate the small sample properties of the proposed estimator by means of Monte Carlo experiments under a variety of scenarios. In general, we find that the estimator, and the associated inference, perform well. The test is conservative under the null hypothesis, but, nevertheless, has excellent power properties, especially when the factor strength is sufficiently high. Application of the proposed estimation strategy to factor models of asset returns shows that out of 146 factors recently considered in the finance literature, only the market factor is truly strong, while all other factors are at best semi-strong, with their strength varying considerably over time. Similarly, we only find evidence of semi-strong factors in an updated version of the Stock and Watson (2012) macroeconomic dataset.
Subjects: 
factor models
factor strength
measures of pervasiveness
cross-sectional dependence
market factor
JEL: 
C38
E20
G20
Document Type: 
Working Paper
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