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A NEW DIAGNOSTIC TEST FOR CROSS-SECTION UNCORRELATEDNESS IN NONPARAMETRIC PANEL DATA MODELS

Published online by Cambridge University Press:  27 April 2012

Jia Chen ,
Jiti Gao  and
Degui Li
Jia Chen*
Affiliation:
Monash University and University of Queensland
Jiti Gao
Affiliation:
Monash University and University of Adelaide
Degui Li
Affiliation:
Monash University
*
*Address correspondence to Jia Chen, School of Mathematics, University of Queensland, ST Lucia, Brisbane 4072, Australia; e-mail: jiachen1981@gmail.com.
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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.

Information

Type
Miscellanea
Information
Econometric Theory , Volume 28 , Issue 5 , October 2012 , pp. 1144 - 1163
Copyright
Copyright © Cambridge University Press 2012

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References

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