Econometric Theory

Miscellanea

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

Jia Chena1 c1, Jiti Gaoa2 and Degui Lia3

a1 Monash University and University of Queensland

a2 Monash University and University of Adelaide

a3 Monash University

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.

Correspondence:

c1 Address correspondence to Jia Chen, School of Mathematics, University of Queensland, ST Lucia, Brisbane 4072, Australia; e-mail: jiachen1981@gmail.com.

Footnotes

  The authors thank the co-editor Professor Oliver Linton and the referees for their constructive comments. Thanks also go to seminar and conference participants in Xiamen University in China, The Australian National University, the 2009 Econometric Society Australasian Meeting in Canberra, and Nanyang Technological University in Singapore. This research was supported by grant DP0879088 of the Australian Research Council.

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