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A space-time filter for panel data models containing random effects

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  • Parent, Olivier
  • LeSage, James P.

Abstract

A space-time filter structure is introduced that can be used to accommodate dependence across space and time in the error components of panel data models that contain random effects. This specification provides insights regarding several space-time structures that have been used recently in the panel data literature. Markov Chain Monte Carlo methods are set forth for estimating the model which allow simple treatment of initial period observations as endogenous or exogenous. The performance of the approach is demonstrated using both Monte Carlo experiments and an applied illustration.

Suggested Citation

  • Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
  • Handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:475-490
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    References listed on IDEAS

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    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.
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    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. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
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    Cited by:

    1. Fingleton, Bernard, 2018. "Exploring Brexit with dynamic spatial panel models : some possible outcomes for employment across the EU regions," MPRA Paper 86553, University Library of Munich, Germany.
    2. repec:eee:dyncon:v:87:y:2018:i:c:p:21-45 is not listed on IDEAS
    3. repec:taf:ijspmg:v:21:y:2017:i:3:p:240-255 is not listed on IDEAS
    4. repec:bla:presci:v:96:y:2017:i:3:p:627-645 is not listed on IDEAS
    5. Viego, Valentina & Temporelli, Karina, 2010. "Econometría espacial: una aplicación a los problemas de sobrepeso y obesidad en las provincias de Argentina
      [Spatial econometrics: an application to obesity indicators in Argentinian provinces]
      ," MPRA Paper 26878, University Library of Munich, Germany.
    6. 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.
    7. Debarsy, Nicolas & Dossougoin, Cyrille & Ertur, Cem & Gnabo, Jean-Yves, 2018. "Measuring sovereign risk spillovers and assessing the role of transmission channels: A spatial econometrics approach," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 21-45.
    8. Hans Dewachter & Romain Houssa & Priscilla Toffano, 2012. "Spatial propagation of macroeconomic shocks in Europe," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 148(2), pages 377-402, June.
    9. Baltagi, Badi H. & Fingleton, Bernard & Pirotte, Alain, 2018. "A Time-Space Dynamic Panel Data Model with Spatial Moving Average Errors," MPRA Paper 86371, University Library of Munich, Germany.
    10. Harry H. Kelejian & Gianfranco Piras, 2013. "A J-Test for Panel Models with Fixed Effects, Spatial and Time," Working Papers Working Paper 2013-03, Regional Research Institute, West Virginia University.
    11. repec:rri:wpaper:201303 is not listed on IDEAS
    12. Harry H. Kelejian & Gianfranco Piras, 2016. "A J test for dynamic panel model with fixed effects, and nonparametric spatial and time dependence," Empirical Economics, Springer, vol. 51(4), pages 1581-1605, December.
    13. repec:eee:regeco:v:65:y:2017:i:c:p:65-88 is not listed on IDEAS
    14. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    15. James LeSage & Yuxue Sheng, 2014. "A spatial econometric panel data examination of endogenous versus exogenous interaction in Chinese province-level patenting," Journal of Geographical Systems, Springer, vol. 16(3), pages 233-262, July.
    16. Lee, Lung-fei & Yu, Jihai, 2015. "Estimation of fixed effects panel regression models with separable and nonseparable space–time filters," Journal of Econometrics, Elsevier, vol. 184(1), pages 174-192.
    17. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.
    18. Zhang, Yuanqing & Sun, Yanqing, 2015. "Estimation of partially specified dynamic spatial panel data models with fixed-effects," Regional Science and Urban Economics, Elsevier, vol. 51(C), pages 37-46.
    19. Taspinar, Suleyman & Dogan, Osman & Bera, Anil K., 2017. "GMM Gradient Tests for Spatial Dynamic Panel Data Models," MPRA Paper 82830, University Library of Munich, Germany.
    20. J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
    21. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.

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