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The Spatial Durbin Model and the Common Factor Tests

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Author Info

  • Jes�s Mur
  • Ana Angulo

Abstract

Abstract The spatial Durbin model occupies an interesting position in the field of spatial econometrics. It is the reduced form of a model with cross-sectional dependence in the errors and it may be used as the nesting equation in a more general approach of model selection. Specifically, in this equation we obtain the common factor tests (of which the likelihood ratio is the best known) whose objective is to discriminate between substantive and residual dependence in an apparently misspecified equation. Our paper tries to delve deeper into the role of the spatial Durbin model in the problem of specifying a spatial econometric model. We include a Monte Carlo study related to the performance of the common factor tests presented in the paper in small sample sizes.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Spatial Economic Analysis.

Volume (Year): 1 (2006)
Issue (Month): 2 ()
Pages: 207-226

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Handle: RePEc:taf:specan:v:1:y:2006:i:2:p:207-226

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Related research

Keywords: Common factor tests; spatial lag model; spatial error model; C21; C50; R15;

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Cited by:
  1. Takagi, Daisuke & Ikeda, Ken’ichi & Kawachi, Ichiro, 2012. "Neighborhood social capital and crime victimization: Comparison of spatial regression analysis and hierarchical regression analysis," Social Science & Medicine, Elsevier, vol. 75(10), pages 1895-1902.
  2. Burridge, Peter, 2011. "A research agenda on general-to-specific spatial model search," Investigaciones Regionales, Asociación Española de Ciencia Regional, issue 21, pages 71-90.
  3. Catherine BAUMONT & Rachel GUILLAIN, 2013. "Interactions, Spillovers De Connaissance Et Croissance Des Villes Européennes - Quel Est Le Rôle De La Géographie, Du Climat Institutionnel Et Des Réseaux Des Firmes Multinationales ?," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 38, pages 161-207.
  4. Jesús Mur & Fernando López & Ana Angulo, 2010. "Instability in spatial error models: an application to the hypothesis of convergence in the European case," Journal of Geographical Systems, Springer, vol. 12(3), pages 259-280, September.
  5. Angulo, Ana M. & Mur, Jesús, 2011. "The Likelihood Ratio Test of Common Factors under Non-Ideal Conditions," Investigaciones Regionales, Asociación Española de Ciencia Regional, issue 21, pages 37-52.
  6. Arbia, Giuseppe & Battisti, Michele & Di Vaio, Gianfranco, 2010. "Institutions and geography: Empirical test of spatial growth models for European regions," Economic Modelling, Elsevier, vol. 27(1), pages 12-21, January.
  7. Nicola Pontarollo, 2013. "Structural change, productivity growth and Structural Funds in European regions," ERSA conference papers ersa13p747, European Regional Science Association.

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