Testing Weak Cross-Sectional Dependence in Large Panels

25 Pages Posted: 31 Mar 2012

See all articles by M. Hashem Pesaran

M. Hashem Pesaran

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

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Abstract

This paper considers testing the hypothesis that errors in a panel data model are weakly cross sectionally dependent, using the exponent of cross-sectional dependence α, introduced recently in Bailey, Kapetanios and Pesaran (2012). It is shown that the implicit null of the CD test depends on the relative expansion rates of N and T. When T=O(N^ϵ), for some 0 < ϵ ≤ 1, then the implicit null of the CD test is given by 0 ≤ α < (2–ϵ)/4, which gives 0 ≤ α < 1/4, when N and T tend to infinity at the same rate such that T/N → к, with к ; with being a finite positive constant. It is argued that in the case of large N panels, the null of weak dependence is more appropriate than the null of independence which could be quite restrictive for large panels. Using Monte Carlo experiments, it is shown that the CD test has the correct size for values of α in the range [0, 1/4], for all combinations of N and T, and irrespective of whether the panel contains lagged values of the dependent variables, so long as there are no major asymmetries in the error distribution.

Keywords: exponent of cross-sectional dependence, diagnostic tests, panel data models, dynamic heterogenous panels

JEL Classification: C12, C13, C33

Suggested Citation

Pesaran, M. Hashem, Testing Weak Cross-Sectional Dependence in Large Panels. IZA Discussion Paper No. 6432, Available at SSRN: https://ssrn.com/abstract=2032000

M. Hashem Pesaran (Contact Author)

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

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