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A joint serial correlation test for linear panel data models

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  • Yamagata, Takashi

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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  • Yamagata, Takashi, 2008. "A joint serial correlation test for linear panel data models," Journal of Econometrics, Elsevier, vol. 146(1), pages 135-145, September.
    • Handle: RePEc:eee:econom:v:146:y:2008:i:1:p:135-145
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    6. Montes-Rojas Gabriel & Sosa-Escudero Walter & Zincenko Federico, 2020. "Level-Based Estimation of Dynamic Panel Models," Journal of Econometric Methods, De Gruyter, vol. 9(1), pages 1-23, January.
    7. Ryo Okui, 2017. "Misspecification in Dynamic Panel Data Models and Model-Free Inferences," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 283-304, September.
    8. Wu, Jianhong & Zhu, Lixing, 2011. "Testing for serial correlation and random effects in a two-way error component regression model," Economic Modelling, Elsevier, vol. 28(6), pages 2377-2386.
    9. Ding, Weili & Lehrer, Steven F., 2014. "Understanding the role of time-varying unobserved ability heterogeneity in education production," Economics of Education Review, Elsevier, vol. 40(C), pages 55-75.
    10. Arbues, Fernando & Villanu´a, Inmaculada & Barberán Ortí, Ramón, 2010. "Household size and residential water demand: an empirical approach," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(1), pages 1-20.
    11. Jianhong Wu & Lixing Zhu, 2012. "Estimation of and testing for random effects in dynamic panel data models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 477-497, September.
    12. Wu, Jianhong, 2020. "A joint test for serial correlation and heteroscedasticity in fixed-T panel regression models with interactive effects," Economics Letters, Elsevier, vol. 197(C).
    13. Fritsch, Markus, 2019. "On GMM estimation of linear dynamic panel data models," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe B-36-19, University of Passau, Faculty of Business and Economics.
    14. Fernando Arbués & Inmaculada Villanúa & Ramón Barberán, 2010. "Household size and residential water demand: an empirical approach ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 54(1), pages 61-80, January.

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