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GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Replaced by CentER DP 2015-003)

Author

Listed:
  • Cizek, P.

    (Tilburg University, Center For Economic Research)

  • Jacobs, J.P.A.M.
  • Ligthart, J.E.

    (Tilburg University, Center For Economic Research)

  • Vrijburg, H.

Abstract

We extend the three-step generalized methods of moments (GMM) approach of Kapoor et al. (2007), which corrects for spatially correlated errors in static panel data models, by introducing a spatial lag and a one-period lag of the dependent variable as additional explanatory variables. Combining the extended Kapoor et al. (2007) approach with the dynamic panel data model GMM estimators of Arellano and Bond (1991) and Blundell and Bond (1998) and specifying moment conditions for various time lags, spatial lags, and sets of exogenous variables yields new spatial dynamic panel data estimators. We prove their consistency and asymptotic normality for a large number of spatial units N and a xed small number of time periods T. Monte Carlo simulations demonstrate that the root mean squared error of spatially corrected GMM estimates|which are based on a spatial lag and spatial error correction|is generally smaller than that of corresponding spatial GMM estimates in which spatial error correlation is ignored. We show that the spatial Blundell-Bond estimators outperform the spatial Arellano-Bond estimators.

Suggested Citation

  • Cizek, P. & Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2011. "GMM Estimation of Fixed Effects Dynamic Panel Data Models with Spatial Lag and Spatial Errors (Replaced by CentER DP 2015-003)," Discussion Paper 2011-134, Tilburg University, Center for Economic Research.
  • Handle: RePEc:tiu:tiucen:b80cf367-c435-4f20-8e4c-83571039771c
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    4. Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
    5. 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.
    6. 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.
    7. Baltagi, Badi H. & Heun Song, Seuck & Cheol Jung, Byoung & Koh, Won, 2007. "Testing for serial correlation, spatial autocorrelation and random effects using panel data," Journal of Econometrics, Elsevier, vol. 140(1), pages 5-51, September.
    8. Su, Liangjun & Yang, Zhenlin, 2015. "QML estimation of dynamic panel data models with spatial errors," Journal of Econometrics, Elsevier, vol. 185(1), pages 230-258.
    9. David Bartolini & Raffaella Santolini, 2012. "Political yardstick competition among Italian municipalities on spending decisions," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 49(1), pages 213-235, August.
    10. Baltagi, Badi H. & Bresson, Georges, 2011. "Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris," Journal of Urban Economics, Elsevier, vol. 69(1), pages 24-42, January.
    11. Jacobs, J.P.A.M. & Ligthart, J.E. & Vrijburg, H., 2009. "Dynamic Panel Data Models Featuring Endogenous Interaction and Spatially Correlated Errors," Discussion Paper 2009-92, Tilburg University, Center for Economic Research.
    12. Elhorst, J. Paul, 2008. "Serial and spatial error correlation," Economics Letters, Elsevier, vol. 100(3), pages 422-424, September.
    13. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
    14. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    15. Ryan R. Brady, 2011. "Measuring the diffusion of housing prices across space and over time," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 213-231, March.
    16. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    17. 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.
    18. Yu, Jihai & Lee, Lung-fei, 2010. "Estimation Of Unit Root Spatial Dynamic Panel Data Models," Econometric Theory, Cambridge University Press, vol. 26(05), pages 1332-1362, October.
    19. 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.
    20. Egger, Peter & Pfaffermayr, Michael & Winner, Hannes, 2005. "An unbalanced spatial panel data approach to US state tax competition," Economics Letters, Elsevier, vol. 88(3), pages 329-335, September.
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    Cited by:

    1. Rodolfo Metulini, 2013. "Spatial gravity models for international trade: a panel analysis among OECD countries," ERSA conference papers ersa13p522, European Regional Science Association.
    2. Huang, Yongfu & Quibria, M. G., 2013. "Green Growth: Theory and Evidence," WIDER Working Paper Series 056, World Institute for Development Economic Research (UNU-WIDER).
    3. Asonuma, Tamon, 2014. "Sovereign defaults, external debt and real exchange rate dynamics," MPRA Paper 55133, University Library of Munich, Germany.

    More about this item

    Keywords

    Dynamic panel models; spatial lag; spatial error; GMM estimation;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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