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A closer look at the Spatial Durbin Model

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  • Jesus Mur
  • Ana Angulo

Abstract

The spatial Durbin model occupies an interesting position in Spatial Econometrics. It is the reduced form of a model with cross-sectional dependence in the errors, but it may be used, also, as the nesting model in a more general approach of model selection. In the first case, that is the equation where we solve the Likelihood Ratio test of Common Factors. The objective in this case is to discriminate between substantive and residual dependence in a misspecified equation. Its role, when discussing the specification of the model, is also of great value as a way to access either to a static model, to a dynamic model or to a model with residual dependence. Our paper tries to go further into the interpretation of this intermediate equation in both aspects. We include a small Monte Carlo study related to the LR tests and present some new results that expedites the use, and the interpretation, of the Durbin equation in the more general process of econometric model selection in a spatial context.

Suggested Citation

  • Jesus Mur & Ana Angulo, 2005. "A closer look at the Spatial Durbin Model," ERSA conference papers ersa05p392, European Regional Science Association.
    • Handle: RePEc:wiw:wiwrsa:ersa05p392
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    File URL: https://www-sre.wu.ac.at/ersa/ersaconfs/ersa05/papers/392.pdf
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    References listed on IDEAS

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    1. Jes�s Mur & Ana Angulo, 2005. "Model selection strategies in a spatial context," Documentos de Trabajo dt2005-06, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza.
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