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The Spatial Durbin Model and the Common Factor Tests

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  • Jesús 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.

Suggested Citation

  • Jesús Mur & Ana Angulo, 2006. "The Spatial Durbin Model and the Common Factor Tests," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 207-226.
    • Handle: RePEc:taf:specan:v:1:y:2006:i:2:p:207-226
    DOI: 10.1080/17421770601009841
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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.
    2. Daniel A. Griffith, 2003. "Spatial Autocorrelation and Spatial Filtering," Advances in Spatial Science, Springer, number 978-3-540-24806-4.
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    Keywords

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    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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