A New Diagnostic Test for Cross-Section Uncorrelatedness in Nonparametric Panel Data Models

42 Pages Posted: 18 Sep 2010

See all articles by Jiti Gao

Jiti Gao

Monash University - Department of Econometrics & Business Statistics

Jia Chen

University of Adelaide - School of Economics

Degui Li

University of Adelaide - School of Economics

Date Written: September 15, 2010

Abstract

In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness in a nonparametric panel data model. The proposed nonparametric cross-section uncorrelatedness (CU) test is a nonparametric counterpart of an existing parametric cross-section dependence (CD) test proposed in Pesaran (2004) for the parametric case. We establish asymptotic distributions of the proposed test statistic for several different cases. Without assuming cross-section independence, we establish asymptotic distributions for the proposed test for the case where both the cross-section dimension and the time dimension go to infinity simultaneously. We then analyze the power function of the proposed test under a sequence of local alternatives that involve a nonlinear multi-factor model. We also provide several numerical examples. The small sample studies show that the nonparametric CU test associated with an asymptotic critical value works well numerically in each individual case. An empirical analysis of a set of CPI data in Australian capital cities is given to examine the applicability of the proposed nonparametric CU test.

Suggested Citation

Gao, Jiti and Chen, Jia and Li, Degui, A New Diagnostic Test for Cross-Section Uncorrelatedness in Nonparametric Panel Data Models (September 15, 2010). Available at SSRN: https://ssrn.com/abstract=1677747 or http://dx.doi.org/10.2139/ssrn.1677747

Jiti Gao (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

900 Dandenong Road
Caulfield East, Victoria 3145
Australia
61399031675 (Phone)
61399032007 (Fax)

HOME PAGE: http://www.jitigao.com

Jia Chen

University of Adelaide - School of Economics ( email )

No 233 North Terrace, School of Commerce
Adelaide SA, SA 5005
Australia

Degui Li

University of Adelaide - School of Economics ( email )

No 233 North Terrace, School of Commerce
Adelaide, South Australia 5005
Australia

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
94
Abstract Views
873
Rank
499,092
PlumX Metrics