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Type: Journal article
Title: A new diagnostic test for cross-section uncorrelatedness in non parametric panel data models
Author: Chen, Jia
Gao, Jiti
Li, Degui
Citation: Econometric Theory, 2012; 28(5):1144-1163
Publisher: Cambridge University Press
Issue Date: 2012
ISSN: 0266-4666
School/Discipline: School of Economics
Statement of
Jia Chen And Jiti Gao And Degui Li
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.
Rights: © Cambridge University Press 2012
DOI: 10.1017/S0266466612000072
Appears in Collections:Economics publications

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