A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS

In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed...

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Veröffentlicht in:Journal of economic surveys 2009-07, Vol.23 (3), p.528-561
Hauptverfasser: Moscone, Francesco, Tosetti, Elisa
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description In this paper we review and compare diagnostic tests of cross‐section independence in the disturbances of panel regression models. We examine tests based on the sample pairwise correlation coefficient or on its transformations, and tests based on the theory of spacings. The ultimate goal is to shed some light on the appropriate use of existing diagnostic tests for cross‐equation error correlation. Our discussion is supported by means of a set of Monte Carlo experiments and a small empirical study on health. Results show that tests based on the average of pairwise correlation coefficients work well when the alternative hypothesis is a factor model with non‐zero mean loadings. Tests based on spacings are powerful in identifying various forms of strong cross‐section dependence, but have low power when they are used to capture spatial correlation.
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source Wiley Online Library - AutoHoldings Journals; EBSCOhost Business Source Complete
subjects Cross-sectional analysis
Diagnostic tests
Economic theory
Estimation
Hypotheses
Monte Carlo simulation
Panel data
Regression analysis
Review articles
Studies
title A REVIEW AND COMPARISON OF TESTS OF CROSS-SECTION INDEPENDENCE IN PANELS
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