Exponent of Cross-Sectional Dependence for Residuals

54 Pages Posted: 31 Oct 2018

See all articles by Natalia Bailey

Natalia Bailey

Monash University

M. Hashem Pesaran

University of Southern California - Department of Economics; University of Cambridge - Trinity College (Cambridge)

George Kapetanios

Bank of England

Multiple version iconThere are 2 versions of this paper

Date Written: 2018

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

JEL Classification: C210, C320

Suggested Citation

Bailey, Natalia and Pesaran, M. Hashem and Kapetanios, George, Exponent of Cross-Sectional Dependence for Residuals (2018). CESifo Working Paper No. 7223, Available at SSRN: https://ssrn.com/abstract=3275397

Natalia Bailey (Contact Author)

Monash University ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

M. Hashem Pesaran

University of Southern California - Department of Economics

3620 South Vermont Ave. Kaprielian (KAP) Hall 300
Los Angeles, CA 90089
United States

University of Cambridge - Trinity College (Cambridge) ( email )

United Kingdom

George Kapetanios

Bank of England ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
25
Abstract Views
259
PlumX Metrics