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A robust test for error cross-section correlation in panel models

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Abstract

A wild bootstrap test of the null hypothesis that the errors of a panel data model are not correlated over cross-section units is proposed. The new test is more generally applicable than others that use the restrictive assumptions of normality and homoskedasticity. Monte Carlo results indicate that the new test is reliable.

Suggested Citation

  • L Godfrey & T Yamagata, 2010. "A robust test for error cross-section correlation in panel models," Discussion Papers 10/16, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:10/16
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    File URL: https://www.york.ac.uk/media/economics/documents/discussionpapers/2010/1016.pdf
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    Cited by:

    1. Halunga, Andreea G. & Orme, Chris D. & Yamagata, Takashi, 2017. "A heteroskedasticity robust Breusch–Pagan test for Contemporaneous correlation in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 198(2), pages 209-230.

    More about this item

    Keywords

    Cross-section correlation; Wild bootstrap; Robust test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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