A Taxonomy of Spatial Econometric Models for Simultaneous Equations Systems

  • Sergio J. Rey
  • Marlon G. Boarnet
Part of the Advances in Spatial Science book series (ADVSPATIAL)


The spatial econometric literature has developed a large number of approaches that can handle spatial dependence and heterogeneity, yet almost all of these approaches are single equation techniques. For many regional economic problems there are both multiple endogenous variables and data on observations that interact across space. To date, researchers have often been in the undesirable position of having to choose between modeling spatial interactions in a single equation framework, or using multiple equations but losing the advantages of a spatial econometric approach. This chapter establishes a framework for applying spatial econometrics within the context of multi-equation systems. Specifically, we discuss the need for multi-equation spatial econometric models and we develop a general model that can subsume many interesting special cases. We also examine the small sample properties of common estimators for specific cases of the general model.


Root Mean Square Error Ordinary Little Square Endogenous Variable Data Generate Process Public Capital 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Sergio J. Rey
    • 1
  • Marlon G. Boarnet
    • 2
  1. 1.San Diego State UniversityUSA
  2. 2.University of CaliforniaIrvineUSA

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