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A New Diagnostic Test for Cross-Section Independence in Nonparametric Panel Data Model

Listed author(s):
  • Jia Chen

    (School of Economics, University of Adelaide)

  • Jiti Gao


    (School of Economics, University of Adelaide)

  • Degui Li

    (School of Economics, University of Adelaide)

In this paper, we propose a new diagnostic test for residual cross–section independence in a nonparametric panel data model. The proposed nonparametric cross–section dependence (CD) test is a nonparametric counterpart of an existing parametric CD test proposed in Pesaren (2004) for the parametric case. We establish an asymptotic distribution of the proposed test statistic under the null hypothesis. As in the parametric case, the proposed test has an asymptotically normal distribution. We then analyze the power function of the proposed test under an alternative hypothesis that involves a nonlinear multi–factor model. We also provide several numerical examples. The small sample studies show that the nonparametric CD 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 CD test.

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Paper provided by University of Adelaide, School of Economics in its series School of Economics Working Papers with number 2009-16.

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Length: 36 pages
Date of creation: 2009
Handle: RePEc:adl:wpaper:2009-16
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