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A New Diagnostic Test For Cross-Section Uncorrelatedness In Nonparametric Panel Data Models

Listed author(s):
  • Chen, Jia
  • Gao, Jiti
  • Li, Degui

In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in a nonparametric panel data model. The proposed nonparametric CU test is a nonparametric counterpart of an existing parametric cross-section dependence test proposed in Pesaran ( 2004 , Cambridge Working paper in Economics 0435). Without assuming cross-section independence, we establish asymptotic distribution for the proposed test statistic for the case where both the cross-section dimension and the time dimension go to infinity simultaneously, and then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multifactor model. The simulation results and real data analysis show that the nonparametric CU test associated with an asymptotic critical value works well.

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Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 28 (2012)
Issue (Month): 05 (October)
Pages: 1144-1163

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Handle: RePEc:cup:etheor:v:28:y:2012:i:05:p:1144-1163_00
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