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Standardized LM Tests for Spatial Error Dependence in Linear or Panel Regressions

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Author Info

  • Badi H. Baltagi

    () (Department of Economics and Center for Policy Research, Syracuse University)

  • Zhenlin Yang

    () (School of Economics, Singapore Management University)

Abstract

The robustness of the LM tests for spatial error dependence of Burridge (1980) for the linear regression model and Anselin (1988) for the panel regression model are examined. While both tests are asymptotically robust against distributional misspecification, their finite sample behavior can be sensitive to the spatial layout. To overcome this shortcoming, standardized LM tests are suggested. Monte Carlo results show that the new tests possess good finite sample properties. An important observation made throughout this study is that the LM tests for spatial dependence need to be both mean and variance-adjusted for good finite sample performance to be achieved. The former is, however, often neglected in the literature.

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Bibliographic Info

Paper provided by Singapore Management University, School of Economics in its series Working Papers with number 11-2010.

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Length: 25 pages
Date of creation: Sep 2010
Date of revision:
Publication status: Published in SMU Economics and Statistics Working Paper Series
Handle: RePEc:siu:wpaper:11-2010

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Related research

Keywords: Distributional misspecification; Group interaction; LM test; Moran’s I Test; Robustness; Spatial panel models.;

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References

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  1. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-65, July.
  2. Yang, Zhenlin, 2010. "A robust LM test for spatial error components," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 299-310, September.
  3. 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.
  4. Moulton, Brent R & Randolph, William C, 1989. "Alternative Tests of the Error Components Model," Econometrica, Econometric Society, vol. 57(3), pages 685-93, May.
  5. Nicolas Debarsy & Cem Ertur, 2009. "Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model," Post-Print halshs-00414133, HAL.
  6. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
  7. Honda, Yuzo, 1991. "A standardized test for the error components model with the two-way layout," Economics Letters, Elsevier, vol. 37(2), pages 125-128, October.
  8. Robinson, P.M., 2008. "Correlation testing in time series, spatial and cross-sectional data," Journal of Econometrics, Elsevier, vol. 147(1), pages 5-16, November.
  9. Benjamin Born & Jörg Breitung, 2011. "Simple regression‐based tests for spatial dependence," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 330-342, 07.
  10. Baltagi, Badi H. & Chang, Young-Jae & Li, Qi, 1992. "Monte Carlo results on several new and existing tests for the error component model," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 95-120.
  11. H. Kelejian, Harry & Prucha, Ingmar R., 2001. "On the asymptotic distribution of the Moran I test statistic with applications," Journal of Econometrics, Elsevier, vol. 104(2), pages 219-257, September.
  12. Koenker, Roger, 1981. "A note on studentizing a test for heteroscedasticity," Journal of Econometrics, Elsevier, vol. 17(1), pages 107-112, September.
  13. Honda, Yuzo, 1985. "Testing the Error Components Model with Non-normal Disturbances," Review of Economic Studies, Wiley Blackwell, vol. 52(4), pages 681-90, October.
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Cited by:
  1. Guo, Penghui & Liu, Lihu, 2011. "Robust Test for Spatial Error Model:Considering Changes of Spatial Layouts and Distribution Misspecification," MPRA Paper 38050, University Library of Munich, Germany, revised Apr 2012.

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