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Exponent of Cross-sectional Dependence for Residuals

Natalia Bailey (), George Kapetanios () and M Pesaran ()

No 7223, CESifo Working Paper Series from CESifo

Abstract: In this paper we focus on estimating the degree of cross-sectional dependence in the error terms of a classical panel data regression model. For this purpose we propose an estimator of the exponent of cross-sectional dependence denoted by α; which is based on the number of non-zero pair-wise cross correlations of these errors. We prove that our estimator, ᾶ; is consistent and derive the rate at which ᾶ approaches its true value. We evaluate the finite sample properties of the proposed estimator by use of a Monte Carlo simulation study. The numerical results are encouraging and supportive of the theoretical findings. Finally, we undertake an empirical investigation of α for the errors of the CAPM model and its Fama-French extensions using 10-year rolling samples from S&P 500 securities over the period Sept 1989 - May 2018.

Keywords: pair-wise correlations; cross-sectional dependence; cross-sectional averages; weak and strong factor models; CAPM and Fama-French factors (search for similar items in EconPapers)
JEL-codes: C21 C32 (search for similar items in EconPapers)
Date: 2018
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: Exponent of Cross-sectional Dependence for Residuals (2019) Downloads
Working Paper: Exponent of cross-sectional dependence for residuals (2018) Downloads
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