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Joint LM test for homoskedasticity in a one-way error component model

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  • Baltagi, Badi H.
  • Bresson, Georges
  • Pirotte, Alain

Abstract

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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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 134 (2006)
Issue (Month): 2 (October)
Pages: 401-417

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Handle: RePEc:eee:econom:v:134:y:2006:i:2:p:401-417

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

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  1. 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.
  2. 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.
  3. repec:fth:louvco:9606 is not listed on IDEAS
  4. 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.
  5. Wansbeek, Tom, 1989. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 5(02), pages 326-326, August.
  6. Magnus, J.R., 1978. "Maximum likelihood estimation of the GLS model with unknown parameters in the disturbance covariance matrix," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153204, Tilburg University.
  7. Russell Davidson & James G. MacKinnon, 2001. "Artificial Regressions," Working Papers 1038, Queen's University, Department of Economics.
  8. Baltagi, Badi H., 1988. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 4(02), pages 349-350, August.
  9. 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.
  10. 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.
  11. Randolph, William C., 1988. "A transformation for heteroscedastic error components regression models," Economics Letters, Elsevier, vol. 27(4), pages 349-354.
  12. Breusch, T.S. & Pagan, A.R., . "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).
  13. 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).
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
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Citations

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Cited by:
  1. Badi H. Baltagi & Seuck Heun Song & Jae Hyeok Kwon, 2008. "Testing for Heteroskedasticity and Spatial Correlation in a Random Effects Panel Data Model," Center for Policy Research Working Papers 108, Center for Policy Research, Maxwell School, Syracuse University.
  2. Walter Sosa Escudero & Anil K. Bera & Gabriel Montes Rojas, 2009. "Testing Under Local Misspecification and Artificial Regressions," Working Papers 97, Universidad de San Andres, Departamento de Economia, revised Oct 2009.
  3. Montes-Rojas, Gabriel & Sosa-Escudero, Walter, 2011. "Robust tests for heteroskedasticity in the one-way error components model," Journal of Econometrics, Elsevier, vol. 160(2), pages 300-310, February.
  4. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer, vol. 95(4), pages 435-452, December.
  5. Badi H. Baltagi & Byoung Cheol Jung & Seuck Heun Song, 2008. "Testing for Heteroskedasticity and Serial Correlation in a Random Effects Panel Data Model," Center for Policy Research Working Papers 111, Center for Policy Research, Maxwell School, Syracuse University.
  6. Kouassi, Eugene & Mougoué, Mbodja & Sango, Joel & Bosson Brou, J.M. & Amba, Claude M.O. & Salisu, Afeez Adebare, 2014. "Testing for heteroskedasticity and spatial correlation in a two way random effects model," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 153-171.
  7. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
  8. Galvao, Antonio F. & Montes-Rojas, Gabriel & Sosa-Escudero, Walter & Wang, Liang, 2013. "Tests for skewness and kurtosis in the one-way error component model," Journal of Multivariate Analysis, Elsevier, vol. 122(C), pages 35-52.

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