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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.

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Bibliographic Info

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

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  1. 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.
  2. Charles I. Jones, 2002. "Sources of U.S. Economic Growth in a World of Ideas," American Economic Review, American Economic Association, vol. 92(1), pages 220-239, March.
  3. 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.
  4. 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.
  5. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
  6. 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.
  7. 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.
  8. Magnus, J.R., 1982. "Multivariate error components analysis of linear and nonlinear regression models by maximum likelihood," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153211, Tilburg University.
  9. 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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Cited by:
  1. Romain Houssa, 2010. "Spatial Propagation of Macroeconomic Shocks in Europe," Working Papers 1009, University of Namur, Department of Economics.
  2. Harry H. Kelejian & Gianfranco Piras, 2013. "A J-Test for Panel Models with Fixed Effects, Spatial and Time," Working Papers 201303, Regional Research Institute, West Virginia University.
  3. 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.
  4. 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.
  5. 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.
  6. Olivier Parent, 2012. "A space-time analysis of knowledge production," Journal of Geographical Systems, Springer, vol. 14(1), pages 49-73, January.
  7. J. Elhorst, 2012. "Dynamic spatial panels: models, methods, and inferences," Journal of Geographical Systems, Springer, vol. 14(1), pages 5-28, January.

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