Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-18T05:27:51.064Z Has data issue: false hasContentIssue false
  • English
  • Français

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: [email protected].
Get access Rights & Permissions [Opens in a new window]

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.

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Breusch, T.S. & Pagan, A.R. (1980) The Lagrange multiplier test and its application to model specifications in econometrics. Review of Economic Studies 47, 239–253.Google Scholar
Cai, Z. & Li, Q. (2008) Nonparametric estimation of varying coefficient dynamic panel data models. Econometric Theory 24, 1321–1342.Google Scholar
Chen, J., Gao, J., & Li, D. (2009) Testing for Cross-Section Uncorrelatedness in Nonparametric Panel Data Models: Theory and Practice. Working paper, University of Adelaide. Available athttp://www.adelaide.edu.au/directory/jiti.gao.Google Scholar
Fan, J. & Gijbels, J. (1996) Local Polynomial Modelling and Its Applications. Chapman and Hall.Google Scholar
Fan, J. & Yao, Q. (2003) Nonlinear Time Series: Nonparametric and Parametric Methods. Springer-Verlag.Google Scholar
Frees, E.W. (1995) Assessing cross sectional correlation in panel data. Journal of Econometrics 69, 393–414.Google Scholar
Gao, J. (2007) Nonlinear Time Series: Semiparametric and Nonparametric Methods. Chapman and Hall.Google Scholar
Hsiao, C., Pesaran, M.H., & Pick, A. (2007) Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models. IZA Discussion paper 2756.CrossRefGoogle Scholar
Huang, H., Kab, C., & Urga, G. (2008) Copula-based tests for cross-sectional independence in panel models. Economics Letters 100, 224–228.Google Scholar
Li, Q. & Racine, J. (2007) Nonparametric Econometrics: Theory and Practice. Princeton University Press.Google Scholar
Ng, S. (2006) Testing cross section correlation in panel data using spacing. Journal of Business & Economic Statistics 24, 12–23.Google Scholar
Pesaran, M.H. (2004) General Diagnostic Tests for Cross Section Dependence in Panels. Cambridge Working paper in Economics 0435.Google Scholar
Pesaran, M.H., Ullah, A., & Yamagata, T. (2008) A bias adjusted LM test of error cross section independence. Econometrics Journal 11, 105–127.Google Scholar
Phillips, P.C.B. & Moon, H. (1999) Linear regression limit theory for nonstationary panel data. Econometrica 67, 1057–1111.Google Scholar
Sarafidis, V., Yamagata, T., & Robertson, D. (2009) A test of cross section dependence for a linear dynamic panel model with regressors. Journal of Econometrics 148, 149–161.Google Scholar
Shao, Q. & Yu, H. (1996) Weak convergence for weighted empirical processes of dependent sequences. Annals of Probability 24, 2098–2127.Google Scholar
Su, L. & Ullah, A. (2009) Testing conditional uncorrelatednesss. Journal of Business & Economic Statistics 27, 18–29.CrossRefGoogle Scholar