Advanced Search
MyIDEAS: Login to save this paper or follow this series

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

Contents:

Author Info

  • BALTAGI B-H.
  • BRESSON G.
  • PIROTTE A.

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.

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

Download Info

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.u-paris2.fr/ermes/doctrav/0408
Our checks indicate that this address may not be valid because: 500 Can't connect to ermes.u-paris2.fr:80 (10060) (http://www.u-paris2.fr/ermes/doctrav/0408 [302 Found]--> http://ermes.u-paris2.fr/doctrav/0408). If this is indeed the case, please notify ()
Download Restriction: no

Bibliographic Info

Paper provided by ERMES, University Paris 2 in its series Working Papers ERMES with number 0408.

as in new window
Length:
Date of creation: 2004
Date of revision:
Handle: RePEc:erm:papers:0408

Contact details of provider:
Postal: 12, place du Panthéon, 75230 Paris Cedex 05
Phone: (33) 1 44 41 89 61 (66)
Fax: (33) 1 40 51 81 30
Web page: http://ermes.u-paris2.fr/
More information through EDIRC

Related research

Keywords:

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

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. repec:fth:louvco:9606 is not listed on IDEAS
  2. 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.
  3. 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).
  4. 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.
  5. 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.
  6. Davidson, R. & MacKinnon & J.G., 1999. "Artificial Regressions," G.R.E.Q.A.M. 99a04, Universite Aix-Marseille III.
  7. 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.
  8. Randolph, William C., 1988. "A transformation for heteroscedastic error components regression models," Economics Letters, Elsevier, vol. 27(4), pages 349-354.
  9. 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).
  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 & 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.
  12. 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.
  13. 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.
  14. 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.
  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. 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.
  17. Baltagi, Badi H., 1988. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 4(02), pages 349-350, August.
  18. 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.
  19. Wansbeek, Tom, 1989. "An Alternative Heteroscedastic Error Components Model," Econometric Theory, Cambridge University Press, vol. 5(02), pages 326-326, August.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Bresson G. & Hsiao C. & Pirotte A., 2007. "Assessing the Contribution of R&D to Total Factor Productivity – a Bayesian Approach to Account for Heterogeneity And Heteroscedasticity," Working Papers ERMES 0708, ERMES, University Paris 2.
  2. Gabriel Montes-Rojas & Walter Sosa-Escudero, 2010. "Robust tests for heteroskedasticity in the one-way error components model," Post-Print peer-00768191, HAL.
  3. 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.
  4. Baltagi, Badi H. & Song, Seuck Heun & Kwon, Jae Hyeok, 2009. "Testing for heteroskedasticity and spatial correlation in a random effects panel data model," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2897-2922, June.
  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. Wu, Jianhong & Li, Guodong, 2014. "Moment-based tests for individual and time effects in panel data models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 569-581.
  7. 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.
  8. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
  9. 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.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:erm:papers:0408. 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: ().

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.