Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models
In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the observed dependent variable from its expected value and generalized residuals. We show the asymptotic consistency of the cross section dependence (CD) test of Pesaran (2004). In Monte Carlo experiments it emerges that the CD test has the correct size for any combination of N and T whereas the LM test relies on T large relative to N. We then analyze the roll-call votes of the 104th U.S. Congress and find considerable dependence between the votes of the members of Congress.
|Date of creation:||Apr 2007|
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- Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(02), pages 252-277, April.
- Frees, Edward W., 1995. "Assessing cross-sectional correlation in panel data," Journal of Econometrics, Elsevier, vol. 69(2), pages 393-414, October.
- Gourieroux, C. & Monfort, A. & Trognon, A., 1985. "A General Approach to Serial Correlation," Econometric Theory, Cambridge University Press, vol. 1(03), pages 315-340, December.
- Pesaran, M. Hashem, 2004.
"General Diagnostic Tests for Cross Section Dependence in Panels,"
IZA Discussion Papers
1240, Institute for the Study of Labor (IZA).
- M. Hashem Pesaran, 2004. "General Diagnostic Tests for Cross Section Dependence in Panels," CESifo Working Paper Series 1229, CESifo Group Munich.
- Pesaran, M.H., 2004. "‘General Diagnostic Tests for Cross Section Dependence in Panels’," Cambridge Working Papers in Economics 0435, Faculty of Economics, University of Cambridge.
- 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.
- Pesaran, M.H. & Ullah, A. & Yamagata. T., 2006.
"A Bias-Adjusted LM Test of Error Cross Section Independence,"
Cambridge Working Papers in Economics
0641, Faculty of Economics, University of Cambridge.
- M. Hashem Pesaran & Aman Ullah & Takashi Yamagata, 2008. "A bias-adjusted LM test of error cross-section independence," Econometrics Journal, Royal Economic Society, vol. 11(1), pages 105-127, 03.
- Ullah, Aman, 2004. "Finite Sample Econometrics," OUP Catalogue, Oxford University Press, edition 1, number 9780198774488, May.
- Gourieroux, Christian & Monfort, Alain & Renault, Eric & Trognon, Alain, 1987. "Generalised residuals," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 5-32.
- Ng, Serena, 2006. "Testing Cross-Section Correlation in Panel Data Using Spacings," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 12-23, January.
- Chesher, Andrew & Irish, Margaret, 1987. "Residual analysis in the grouped and censored normal linear model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 33-61.
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