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

Jia Chen, Jiti Gao and Degui Li

No 2009-16, School of Economics and Public Policy Working Papers from University of Adelaide, School of Economics and Public Policy

Abstract: 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.

Keywords: Cross–section independence; local linear smoother; nonlinear panel data model; nonparametric diagnostic test, size and power function (search for similar items in EconPapers)
Pages: 36 pages
Date: 2009
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Citations: View citations in EconPapers (9)

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