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Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation

This paper investigates the ?finite sample properties of estimators for spatial dynamic panel models in the presence of several endogenous variables. So far, none of the available estimators in spatial econometrics allows considering spatial dynamic models with one or more endogenous variables. We propose to apply system-GMM, since it can correct for the endogeneity of the dependent variable, the spatial lag as well as other potentially endogenous variables using internal and/or external instruments. The Monte-Carlo investigation compares the performance of spatial MLE, spatial dynamic MLE (Elhorst (2005)), spatial dynamic QMLE (Yu et al. (2008)), LSDV, difference-GMM (Arellano & Bond (1991)), as well as extended-GMM (Arellano & Bover (1995), Blundell & Bover (1998)) in terms of bias, root mean squared error and standard-error accuracy. The results suggest that, in order to account for the endogeneity of several covariates, spatial dynamic panel models should be estimated using extended GMM. On a practical ground, this is also important, because system-GMM avoids the inversion of high dimension spatial weights matrices, which can be computationally unfeasible for large N and/or T.

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Paper provided by IRENE Institute of Economic Research in its series IRENE Working Papers with number 09-01.

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Length: 29 pages
Date of creation: Mar 2009
Date of revision:
Handle: RePEc:irn:wpaper:09-01
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  1. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2005. "Estimating Models of Complex FDI: Are There Third-Country Effects?," Center for Policy Research Working Papers 73, Center for Policy Research, Maxwell School, Syracuse University.
  2. Blundell, R. & Bond, S., 1995. "Initial Conditions and Moment Restrictions in Dynamic Panel Data Models," Economics Papers 104, Economics Group, Nuffield College, University of Oxford.
  3. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
  4. Gabriele Tondl & Harald Badinger & Werner Müller, 2003. "Regional convergence in the European Union (1985-1999). A spatial dynamic panel analysis," ERSA conference papers ersa03p455, European Regional Science Association.
  5. 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.
  6. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
  7. Sandy Dall'erba & Julie Le Gallo, 2008. "Regional convergence and the impact of European structural funds over 1989-1999: A spatial econometric analysis," Papers in Regional Science, Wiley Blackwell, vol. 87(2), pages 219-244, 06.
  8. Nicole Madariaga & Sandra Poncet, 2006. "FDI in Chinese Cities: Spillovers and Impact on Growth," Working Papers 2006-22, CEPII research center.
  9. Bruce A. Blonigen & Ronald B. Davies & Helen T. Naughton & Glen R. Waddell, 2005. "Spacey Parents: Spatial Autoregressive Patterns in Inbound FDI," NBER Working Papers 11466, National Bureau of Economic Research, Inc.
  10. José-Antonio Monteiro & Madina Kukenova, 2008. "Does Lax Environmental Regulation Attract FDI When Accounting For "Third-Country" Effects?," IRENE Working Papers 08-01, IRENE Institute of Economic Research.
  11. 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.
  12. Elhorst, J. Paul, 2010. "Dynamic panels with endogenous interaction effects when T is small," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 272-282, September.
  13. Blonigen, Bruce A. & Davies, Ronald B. & Waddell, Glen R. & Naughton, Helen T., 2007. "FDI in space: Spatial autoregressive relationships in foreign direct investment," European Economic Review, Elsevier, vol. 51(5), pages 1303-1325, July.
  14. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
  15. Wolfgang Keller & Carol H. Shiue, 2003. "The Origins of Spatial Interaction," NBER Working Papers 10069, National Bureau of Economic Research, Inc.
  16. Hsiao, Cheng & Hashem Pesaran, M. & Kamil Tahmiscioglu, A., 2002. "Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods," Journal of Econometrics, Elsevier, vol. 109(1), pages 107-150, July.
  17. Yu, Jihai & de Jong, Robert & Lee, Lung-fei, 2008. "Quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both n and T are large," Journal of Econometrics, Elsevier, vol. 146(1), pages 118-134, September.
  18. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(2), pages 167-196.
  19. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  20. 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.
  21. Martial Foucault & Thierry Madies & Sonia Paty, 2008. "Public Spending Interactions and Local Politics. Empirical Evidence from French Municipalities," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00339812, HAL.
  22. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, 08.
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