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A joint serial correlation test for linear panel data models

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Author Info
Yamagata, Takashi

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Abstract

This paper proposes a joint error serial correlation test to be applied to linear panel data models after generalised method of moments estimation. This new test is an alternative inferential tool to both the m2 test of [Arellano, M., Bond, S., 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58, 277-297] and the overidentifying restrictions test. The proposed test, called the test, involves an examination of the joint significance of estimates of second to pth-order (first differenced) error serial correlations. The small sample properties of the test are investigated by means of Monte Carlo experiments. The evidence shows that the proposed test mostly outperforms the conventional m2 test and has high power when the overidentifying restrictions test does not, under a variety of alternatives including slope heterogeneity and cross section dependence.

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File URL: http://www.sciencedirect.com/science/article/B6VC0-4T84K6F-1/2/ef08204981c3ec8845f2aa6a711c8a85
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Publisher Info
Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 146 (2008)
Issue (Month): 1 (September)
Pages: 135-145
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Handle: RePEc:eee:econom:v:146:y:2008:i:1:p:135-145

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Web page: http://www.elsevier.com/locate/jeconom

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Related research
Keywords: Method of moments Dynamic panel data Serial correlation test Slope heterogeneity Cross section dependence m2 test Overidentifying restrictions test;

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