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Testing for Heteroskedasticity and Spatial Correlation in a Random Effects Panel Data Model

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Abstract

A panel data regression model with heteroskedastic as well as spatially correlated disturbance is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also deerived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests as well as their LR counterparts perform well even for small N and T. However, misleading inference can occur when using marginal rather than joint or conditional LM tests when spatial correlation or heteroskedasticity is present.

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Bibliographic Info

Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 108.

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Length: 42 pages
Date of creation: Jul 2008
Date of revision:
Handle: RePEc:max:cprwps:108

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Keywords: Panel data; heteroskedasticity; spatial correlation; Lagrange multiplier tests; random effects;

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  1. Baltagi, Badi H. & Song, Seuck Heun & Koh, Won, 2003. "Testing panel data regression models with spatial error correlation," Journal of Econometrics, Elsevier, vol. 117(1), pages 123-150, November.
  2. Baltagi B-H. & Bresson G. & Pirotte A., 2004. "Joint LM test for homoskedasticity in a one-way error component model," Working Papers ERMES 0408, ERMES, University Paris 2.
  3. Hsiao,Cheng, 2003. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9780521522717, October.
  4. 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.
  5. 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).
  6. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
  7. Li, Qi & Stengos, Thanasis, 1994. "Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(4), pages 981-1000, November.
  8. 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.
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  10. repec:fth:louvco:9606 is not listed on IDEAS
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Cited by:
  1. Markus Eberhardt & Francis Teal, 2009. "Econometrics for Grumblers: A New Look at the Literature on Cross-Country Growth Empirics," CSAE Working Paper Series 2009-07, Centre for the Study of African Economies, University of Oxford.
  2. 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.
  3. Kuersteiner, Guido M. & Prucha, Ingmar R., 2013. "Limit theory for panel data models with cross sectional dependence and sequential exogeneity," Journal of Econometrics, Elsevier, vol. 174(2), pages 107-126.
  4. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.

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