Testing for random effects and spatial lag dependence in panel data models
This paper derives a joint Lagrange Multiplier (LM) test which simultaneously tests for the absence of spatial lag dependence and random individual effects in a panel data regression model. It turns out that this LM statistic is the sum of two standard LM statistics. The first one tests for the absence of spatial lag dependence ignoring the random individual effects, and the second one tests for the absence of random individual effects ignoring the spatial lag dependence. This paper also derives two conditional LM tests. The first one tests for the absence of random individual effects without ignoring the possible presence of spatial lag dependence. The second one tests for the absence of spatial lag dependence without ignoring the possible presence of random individual effects.
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Volume (Year): 78 (2008)
Issue (Month): 18 (December)
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References listed on IDEAS
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- Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003.
"Testing panel data regression models with spatial error correlation,"
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- Badi H. Baltagi & Seuck Heun Song & Won Koh, 2002. "Testing Panel Data Regression Models with Spatial Error Correlation," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B6-4, International Conferences on Panel Data.
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"The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics,"
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Oxford University Press, vol. 47(1), pages 239-253.
- Breusch, T.S. & Pagan, A.R., "undated". "The Lagrange multiplier test and its applications to model specification in econometrics," CORE Discussion Papers RP 412, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Harry H. Kelejian & Ingmar R. Prucha, 1999.
"On the Asymptotic Distribution of the Moran I Test Statistic with Applications,"
Electronic Working Papers
99-002, University of Maryland, Department of Economics.
- H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
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