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

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  • Olivier Parent
  • James P. Lesage

    ()

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 general specification encompasses several more specific 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. Performance of the approach is demonstrated using both Monte Carlo experiments and an applied illustration.

Suggested Citation

  • Olivier Parent & James P. Lesage, 2009. "A space-time filter for panel data models containing random effects," University of Cincinnati, Economics Working Papers Series 2009-04, University of Cincinnati, Department of Economics.
  • Handle: RePEc:cin:ucecwp:2009-04
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    References listed on IDEAS

    as
    1. Olivier Parent & James P. Lesage, 2010. "A Spatial Dynamic Panel Model with Random Effects Applied to Commuting Times," University of Cincinnati, Economics Working Papers Series 2010-01, University of Cincinnati, Department of Economics.
    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. 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.
    4. Charles I. Jones, 2002. "Sources of U.S. Economic Growth in a World of Ideas," American Economic Review, American Economic Association, pages 220-239.
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    6. repec:spr:stemec:978-3-7908-2070-6 is not listed on IDEAS
    7. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    8. 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.
    9. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
    10. Magnus, J.R., 1982. "Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood," Other publications TiSEM 9ffb33fe-f5af-470f-b405-f, Tilburg University, School of Economics and Management.
    11. Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
    12. Gasper A. Garofalo & Steven Yamarik, 2002. "Regional Convergence: Evidence From A New State-By-State Capital Stock Series," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 316-323, May.
    13. Parent, Olivier & LeSage, James P., 2010. "A spatial dynamic panel model with random effects applied to commuting times," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 633-645, June.
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    Cited by:

    1. repec:rri:wpaper:201303 is not listed on IDEAS
    2. 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, pages 1581-1605.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.
    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), pages 377-402.
    9. 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.
    10. DEBARSY, Nicolas & DOSSOUGOIN, Cyrille & ERTUR, Cem & GNABO, Jean-Yves, 2016. "Measuring sovereign risk spillovers and assessing the role of transmission channels: a spatial econometrics approach," CORE Discussion Papers 2016053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. repec:eee:regeco:v:65:y:2017:i:c:p:65-88 is not listed on IDEAS
    16. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.

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