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

  • Olivier Parent
  • James P. Lesage

    ()

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.

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File URL: http://www.artsci.uc.edu/collegedepts/economics/research/docs/Wppdf/2009-04.pdf
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Paper provided by University of Cincinnati, Department of Economics in its series University of Cincinnati, Economics Working Papers Series with number 2009-04.

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Length: 42 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:cin:ucecwp:2009-04
Contact details of provider: Postal: Cincinnati, OH 45221-0371
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Web page: http://www.business.uc.edu/economics/
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  1. N. Gregory Mankiw & David Romer & David N. Weil, 1990. "A Contribution to the Empirics of Economic Growth," NBER Working Papers 3541, National Bureau of Economic Research, Inc.
  2. Jones, C.I., 2000. "Sources of U.S. Economic Growth in a World of Ideas," Papers 99-29, United Nations World Employment Programme-.
  3. 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.
  4. J. Barkley Rosser, 2009. "Introduction," Chapters, in: Handbook of Research on Complexity, chapter 1 Edward Elgar.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
  10. 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.
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