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A Monte Carlo Study for Pure and Pretest Estimators of a Panel Data Model with Spatially Autocorrelated Disturbances

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  • Badi H. BALTAGI
  • Peter EGGER
  • Michael PFAFFERMAYR

Abstract

This paper examines the consequences of model misspecification using a panel data model with spatially autocorrelated disturbances. The performance of several maximum likelihood estimators assuming different specifications for this model are compared using Monte Carlo experiments. These include (i) MLE of a random effects model that ignore the spatial correlation; (ii) MLE described in Anselin [1988] which assumes that the individual effects are not spatially autocorrelated; (iii) MLE described in Kapoor, et al. [2006] which assumes that both the individual effects and the remainder error are governed by the same spatial autocorelation; (iv) MLE described in Baltagi, et al. [2006] which allows the spatial correlation parameter for the individual effects to be different from that of the remainder error term. The latter model encompasses the other models and allows the researcher to test these specifications as restrictions on the general model using LM and LR tests. In fact, based on these tests, we suggest a pretest estimator which is shown to perform well in Monte Carlo experiments, ranking a close second to the true MLE in mean squared error performance.

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Bibliographic Info

Article provided by ENSAE in its journal Annals of Economics and Statistics.

Volume (Year): (2007)
Issue (Month): 87-88 ()
Pages: 11-38

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Handle: RePEc:adr:anecst:y:2007:i:87-88:p:02

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References

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  1. Badi H. Baltagi & Peter Egger & Michael Pfafermayr, 2009. "A Generalized Spatial Panel Data Model with Random Effects," Center for Policy Research Working Papers 113, Center for Policy Research, Maxwell School, Syracuse University.
  2. 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.
  3. Giles, Judith A & Giles, David E A, 1993. " Pre-test Estimation and Testing in Econometrics: Recent Developments," Journal of Economic Surveys, Wiley Blackwell, vol. 7(2), pages 145-97, June.
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Cited by:
  1. Bernard Fingleton, 2010. "Predicting the geography of house prices," LSE Research Online Documents on Economics 33507, London School of Economics and Political Science, LSE Library.
  2. Bhattacharjee, A. & Holly, S., 2010. "Structural Interactions in Spatial Panels," Cambridge Working Papers in Economics 1004, Faculty of Economics, University of Cambridge.
  3. Badi Baltagi & Alain Pirotte, 2011. "Seemingly unrelated regressions with spatial error components," Empirical Economics, Springer, vol. 40(1), pages 5-49, February.
  4. Daniel Arribas-Bel & Julia Koschinsky & Pedro Amaral, 2012. "Improving the multi-dimensional comparison of simulation results: a spatial visualization approach," Letters in Spatial and Resource Sciences, Springer, vol. 5(2), pages 55-63, July.

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