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Testing Weak Cross-Sectional Dependence in Large Panels

M Hashem Pesaran ()

No 6432, IZA Discussion Papers from Institute for the Study of Labor (IZA)

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 (search for similar items in EconPapers)
JEL-codes: C12 C13 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets
Date: 2012-03
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Working Paper: Testing Weak Cross-Sectional Dependence in Large Panels (2012) Downloads
Working Paper: Testing Weak Cross-Sectional Dependence in Large Panels (2012) Downloads
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