Directed Tests of No Cross-Sectional Correlation in Large-N Panel Data Models

The paper proposes tests for no cross-correlation based on the information matrix equality. The tests rely on suitably weighted residual cross-covariances or cross-correlations, and are in this sense a generalization of Pesaran’s (2004, CESifo working paper 1229) test for no cross-sectional dependen...

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Bibliographic Details
Published in:Journal of applied econometrics (Chichester, England) England), 2016-01, Vol.31 (1), p.4-31
Main Authors: Demetrescu, Matei, Homm, Ulrich
Format: Article
Language:English
Subjects:
Econometrics
Economic models
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Summary:The paper proposes tests for no cross-correlation based on the information matrix equality. The tests rely on suitably weighted residual cross-covariances or cross-correlations, and are in this sense a generalization of Pesaran’s (2004, CESifo working paper 1229) test for no cross-sectional dependence. They follow chi-squared distributions under joint N, T asymptotics without restrictive sphericity or distributional assumptions. When using the outcome of the directed tests to decide whether to use panel-robust standard errors or not for testing slope parameters, the latter tests are apparently not affected; they can be severely affected, though, if using generic cross-correlation tests as pretests.
ISSN:0883-7252
1099-1255
DOI:10.1002/jae.2496