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Joint LM Test for Homoskedasticity in a One-Way error Component Model

This paper considers a general heteroskedastic error component model using panel data, and derives a joint LM test for homoskedasticity against the alternative of heteroskedasticity in both error components. It contrasts this joint LM test with marginal LM tests that ignore the heteroskedasticity in one of the error components. Monte Carlo results show that misleading inference can occur when using marginal rather than joint tests when heteroskedasticity is present in both components.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 72.

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Length: 25 pages
Date of creation: Oct 2005
Date of revision:
Handle: RePEc:max:cprwps:72
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  1. Alberto HOLLY & Lucien GARDIOL, 1999. "A Score Test for Individual Heteroscedasticity in a One-way Error Components Model," Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) 9915, Université de Lausanne, Faculté des HEC, DEEP.
  2. Wansbeek, Tom, 1989. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 5(02), pages 326-326, August.
  3. Russell Davidson & James G. MacKinnon, 2001. "Artificial Regressions," Working Papers 1038, Queen's University, Department of Economics.
  4. Verbon, H. A. A., 1980. "Testing for heteroscedasticity in a model of seemingly unrelated regression equations with variance components (SUREVC)," Economics Letters, Elsevier, vol. 5(2), pages 149-153.
  5. Delgado, Miguel A., 1992. "Semiparametric Generalized Least Squares in the Multivariate Nonlinear Regression Model," Econometric Theory, Cambridge University Press, vol. 8(02), pages 203-222, June.
  6. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-94, September.
  7. Magnus, Jan R., 1982. "Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 239-285, August.
  8. LEJEUNE, Bernard, 1996. "A Full Heteroscedastic One-Way Error Components Model for Incomplete Panel : Maximum Likelihood Estimation and Lagrange Multiplier Testing," CORE Discussion Papers 1996006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
  10. Rilstone, Paul, 1991. "Some Monte Carlo Evidence on the Relative Efficiency of Parametric and Semiparametric EGLS Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 179-87, April.
  11. Stengos, T. & Li, Q., 1993. "Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form," Working Papers 1993-4, University of Guelph, Department of Economics and Finance.
  12. Baltagi, Badi H & Griffin, James M, 1988. "A Generalized Error Component Model with Heteroscedastic Disturbances," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 29(4), pages 745-53, November.
  13. Magnus, J.R., 1978. "Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix," Other publications TiSEM 388c2c25-0925-4b56-834a-7, Tilburg University, School of Economics and Management.
  14. Baltagi, Badi H., 1988. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 4(02), pages 349-350, August.
  15. Randolph, William C., 1988. "A transformation for heteroscedastic error components regression models," Economics Letters, Elsevier, vol. 27(4), pages 349-354.
  16. Nilanjana Roy, 2002. "Is Adaptive Estimation Useful For Panel Models With Heteroskedasticity In The Individual Specific Error Component? Some Monte Carlo Evidence," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 189-203.
  17. Magnus, Jan R., 1978. "Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix," Journal of Econometrics, Elsevier, vol. 7(3), pages 281-312, April.
  18. Robert F. Phillips, 2003. "Estimation of a Stratified Error-Components Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 501-521, 05.
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