IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

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

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

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.

(This abstract was borrowed from another version of this item.)

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.sciencedirect.com/science/article/B6VC0-4H5N25N-1/2/e2838bc2f68ee86ac69b90ca269718b4
Download Restriction: Full text for ScienceDirect subscribers only

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Elsevier in its journal Journal of Econometrics.

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

as
in new window

Handle: RePEc:eee:econom:v:134:y:2006:i:2:p:401-417
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. 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.
  2. 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).
  3. Wansbeek, Tom, 1989. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 5(02), pages 326-326, August.
  4. 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.
  5. 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.
  6. 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.
  7. Russell Davidson & James G. MacKinnon, 2001. "Artificial Regressions," Working Papers 1038, Queen's University, Department of Economics.
  8. 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.
  9. 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.
  10. 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.
  11. Baltagi, Badi H., 1988. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 4(02), pages 349-350, August.
  12. Randolph, William C., 1988. "A transformation for heteroscedastic error components regression models," Economics Letters, Elsevier, vol. 27(4), pages 349-354.
  13. 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.
  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. 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.
  16. 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.
  17. 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).
  18. 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.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:eee:econom:v:134:y:2006:i:2:p:401-417. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.