Rank-based tests of cross-sectional dependence in panel data models

Long Feng, Ping Zhao, Yanling Ding and Binghui Liu

Computational Statistics & Data Analysis, 2021, vol. 153, issue C

Abstract: In the study of panel regression, current existing cross-sectional dependence tests are mainly based on the normal assumption. However, in practical applications, the normal assumption is usually not valid, which weakens the usability of the tests. To develop more testing tools suitable for nonnormal panel data, we extend the rank-based framework of U-statistics to panel regressions, and derive their asymptotic null distributions respectively as (N,T)→∞. The results of some simulation results and a real data analysis demonstrate the superiority of the proposed tests, especially their robustness to deviation from normality.

Keywords: Cross-sectional dependence; Panel data models; Rank-based tests; Robust to deviation from normality; U-statistics (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:153:y:2021:i:c:s0167947320301614

DOI: 10.1016/j.csda.2020.107070

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