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Small Sample Properties of Maximum Likelihood Versus Generalized Method of Moments Based Tests for Spatially Autocorrelated Errors

  • Peter Egger
  • Mario Larch
  • Michael Pfaffermayr
  • Janette Walde

This paper undertakes a Monte Carlo study to compare MLE-based and GMM-based tests regarding the spatial autocorrelation coefficient of the error term in a Cliff and Ord type model. The main finding is that a Wald-test based on GMM estimation as derived by Kelejian and Prucha (2005a) performs surprisingly well. Our Monte Carlo study indicates that the GMM Wald-test is correctly sized even in small samples and exhibits the same power as their MLE-based counterparts. Since GMM estimates are much easier to calculate, the GMM Wald-test is recommended for applied researches.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2005/wp-cesifo-2005-10/cesifo1_wp1558.pdf
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Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1558.

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Date of creation: 2005
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Handle: RePEc:ces:ceswps:_1558
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  1. White,Halbert, 1994. "Estimation, Inference and Specification Analysis," Cambridge Books, Cambridge University Press, number 9780521252805.
  2. Anselin, Luc & Moreno, Rosina, 2003. "Properties of tests for spatial error components," Regional Science and Urban Economics, Elsevier, vol. 33(5), pages 595-618, September.
  3. Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
  4. 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.
  5. Aten, Bettina, 1996. "Evidence of Spatial Autocorrelation in International Prices," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 42(2), pages 149-63, June.
  6. Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
  7. Joris Pinkse & Margaret E. Slade & Craig Brett, 2002. "Spatial Price Competition: A Semiparametric Approach," Econometrica, Econometric Society, vol. 70(3), pages 1111-1153, May.
  8. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
  9. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
  10. 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.
  11. Kelejian, Harry H. & Prucha, Ingmar R., 2002. "2SLS and OLS in a spatial autoregressive model with equal spatial weights," Regional Science and Urban Economics, Elsevier, vol. 32(6), pages 691-707, November.
  12. Saavedra, Luz A., 2003. "Tests for spatial lag dependence based on method of moments estimation," Regional Science and Urban Economics, Elsevier, vol. 33(1), pages 27-58, January.
  13. Conley, T. G., 1999. "GMM estimation with cross sectional dependence," Journal of Econometrics, Elsevier, vol. 92(1), pages 1-45, September.
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