Journal
OXFORD BULLETIN OF ECONOMICS AND STATISTICS
Volume 82, Issue 5, Pages 1198-1216Publisher
WILEY
DOI: 10.1111/obes.12378
Keywords
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Funding
- NSFC [11501092, 11571068, 11671073]
- Fundamental Research Funds for the Central Universities [2412017BJ002]
- Key Laboratory of Applied Statistics of MOE (KLAS) [130026507, 130028612]
- Jilin Education Science Planning Project [GH180346, JKBLX2018-077]
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Most existing methods for testing cross-sectional dependence in fixed effects panel data models are actually conducting tests for cross-sectional uncorrelation, which are not robust to departures of normality of the error distributions as well as nonlinear cross-sectional dependence. To this end, we construct two rank-based tests for (static and dynamic) fixed effects panel data models, based on two very popular rank correlations, that is, Kendall's tau and Bergsma-Dassios'tau*, respectively, and derive their asymptotic distributions under the null hypothesis. Monte Carlo simulations demonstrate applicability of these rank-based tests in large (N,T) case, and also the robustness to departures of normality of the error distributions and nonlinear cross-sectional dependence.
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