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

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  • Kukenova, Madina
  • Monteiro, Jose-Antonio

Abstract

Since there is so far no estimator that allows to estimate a dynamic panel model that includes a spatial lag as well as other potential endogenous variables. This paper wants to determine if it is suitable to instrument the spatial lag variable (which is by de�finition endogenous/simultaneous) using the instruments proposed by system GMM, i.e. lagged spatial lag values. The Monte Carlo investigation highlights the possibility to estimate a dynamic spatial lag model using the extended GMM proposed by Arellano and Bover (1995) and Blundell and Bover (1998), especially when N and T are large.

Suggested Citation

  • Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Spatial Dynamic Panel Model and System GMM: A Monte Carlo Investigation," MPRA Paper 11569, University Library of Munich, Germany, revised Nov 2008.
  • Handle: RePEc:pra:mprapa:11569
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    1. 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 509-533, May.
    2. 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.
    3. Bruce A. Blonigen & Ronald B. Davies & Glen R. Waddell & Helen T. Naughton, 2019. "FDI in Space: Spatial Autoregressive Relationships in Foreign Direct Investment," World Scientific Book Chapters, in: Foreign Direct Investment, chapter 2, pages 55-88, World Scientific Publishing Co. Pte. Ltd..
    4. 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.
    5. 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.
    6. Elhorst, J. Paul, 2001. "Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable," Research Report 01C05, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    7. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 2(2), pages 167-196.
    8. Nicole Madariaga & Sandra Poncet, 2007. "FDI in Chinese Cities: Spillovers and Impact on Growth," The World Economy, Wiley Blackwell, vol. 30(5), pages 837-862, May.
    9. Martial Foucault & Thierry Madies & Sonia Paty, 2008. "Public spending interactions and local politics. Empirical evidence from French municipalities," Public Choice, Springer, vol. 137(1), pages 57-80, October.
    10. 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, August.
    11. Harald Badinger & Werner Muller & Gabriele Tondl, 2004. "Regional Convergence in the European Union, 1985- 1999: A Spatial Dynamic Panel Analysis," Regional Studies, Taylor & Francis Journals, vol. 38(3), pages 241-253.
    12. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    13. Franzese, Robert J. & Hays, Jude C., 2007. "Spatial Econometric Models of Cross-Sectional Interdependence in Political Science Panel and Time-Series-Cross-Section Data," Political Analysis, Cambridge University Press, vol. 15(2), pages 140-164, April.
    14. repec:dgr:rugsom:03c27 is not listed on IDEAS
    15. 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, June.
    16. Baltagi, Badi H. & Egger, Peter & Pfaffermayr, Michael, 2007. "Estimating models of complex FDI: Are there third-country effects?," Journal of Econometrics, Elsevier, vol. 140(1), pages 260-281, September.
    17. 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.
    18. J. Paul Elhorst, 2014. "Spatial Econometrics," SpringerBriefs in Regional Science, Springer, edition 127, number 978-3-642-40340-8, September.
    19. 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.
    20. 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.
    21. repec:dgr:rugsom:01c05 is not listed on IDEAS
    22. Kukenova, Madina & Monteiro, Jose-Antonio, 2008. "Does Lax Environmental Regulation Attract FDI when accounting for "third-country" effects?," MPRA Paper 11321, University Library of Munich, Germany, revised Sep 2008.
    23. Keller, Wolfgang & Shiue, Carol H., 2007. "The origin of spatial interaction," Journal of Econometrics, Elsevier, vol. 140(1), pages 304-332, September.
    24. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    25. 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.
    26. Elhorst, J. Paul, 2003. "Unconditional maximum likelihood estimation of dynamic models for spatial panels," Research Report 03C27, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    27. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
    28. 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.
    29. 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.
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    More about this item

    Keywords

    Spatial Econometrics; Dynamic Panel Model; System GMM; Monte Carlo Simulations;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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