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A new diagnostic test for cross-section independence in nonlinear panel data models

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dc.contributor.authorChen, Jiaen
dc.contributor.authorGao, Jitien
dc.contributor.authorLi, Deguien
dc.contributor.conferenceAustralasian Meeting of the Econometric Society (2009 : Canberra, Australia)en
dc.contributor.conferenceESAM09en
dc.contributor.schoolSchool of Economicsen
dc.date.issued2009en
dc.description.abstractIn this paper, we propose a new diagnostic test for residual cross section in dependence in a nonparametric panel data model. The proposed test is a nonparametric counterpart of an existing test proposed in Pesaren (2004) for the parametric case. First of all, we establish an asymptotic distribution of the proposed test statistic under the null hypothesis. As shown in the parametric case, the asymptotic distribution is a standard normality. We then analyze the power function of the proposed test statistic under an alternative hypothesis that involves a nonlinear multi-factor model. In order to compute both the sizes and the power values, we select a simulated critical value in each case based on a simple bootstrap simulation scheme in the context of nonparametric panel data models. We finally provide several numerical examples and an empirical analysis of a set of CPI data in Australian capital cities to illustrate the finite sample performance of the proposed test statistic.en
dc.description.statementofresponsibilityJia Chen, Jiti Gao and Degui Lien
dc.description.urihttp://wise.xmu.edu.cn/english/viewNews.asp?id=1955en
dc.identifier.citationProceedings of ESAM09, 2009en
dc.identifier.urihttp://hdl.handle.net/2440/56321
dc.language.isoenen
dc.publisherANUen
dc.subjectCross-sectional independence; empirical study; nonlinear panel data; nonparametricdiagnostic testen
dc.titleA new diagnostic test for cross-section independence in nonlinear panel data modelsen
dc.typeConference paperen

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