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