A new diagnostic test for cross-section uncorrelatedness in non parametric panel data models
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Date
2012
Authors
Chen, Jia
Gao, Jiti
Li, Degui
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Journal article
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Econometric Theory, 2012; 28(5):1144-1163
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Jia Chen And Jiti Gao And Degui Li
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Abstract
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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School of Economics
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© Cambridge University Press 2012