Modeling and Estimation Issues in Spatial Simultaneous Equation Models
AbstractSpatial dependence is one of the main problems in stochastic processes and can be caused by a variety of measurement problems that are associated with the arbitrary delineation of spatial units of observation (such as counties boundaries, census tracts), problems of spatial aggregation, and the presence of spatial externalities and spillover effects. The existence of spatial dependence would then mean that the observations contain less information than if there had been spatial independence. Consequently, hypothesis tests and the statistical properties for estimators in the standard econometric approach will not hold. Thus, in order to obtain approximately the same information as in the case of spatial independence, the spatial dependence needs to be explicitly quantified and modeled. Although advances in spatial econometrics provide researchers with new avenues to address regression problems that are associated with the existence of spatial dependence in regional data sets, most of the applications have, however, been in single-equation frame-works. Yet, for many economic problems there are both multiple endogenous variables and data on observations that interact across space. Therefore, researchers have been in the undesirable position of having to choose between modeling spatial interactions in a single equation frame-work, or using multiple equations but losing the advantage of a spatial econometric approach. In an attempt to address this undesirable position, this research work deals with the modeling and estimation issues in spatial simultaneous equations models. The first part discusses modeling issues in multi-equation Spatial Lag, Spatial Error, and Spatial Autoregressive Models in both cross sectional and panel data sets. Whereas, the second part deals with estimation issues in spatial simultaneous equations models in both cross sectional and panel data sets. Finally, issues related specification tests in spatial simultaneous equations models are discussed.
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Bibliographic InfoPaper provided by Regional Research Institute, West Virginia University in its series Working Papers with number 200713.
Length: 43 pages
Date of creation: 2007
Date of revision:
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More information through EDIRC
spatial dependence; estimation; econometrics; simultaneous equations;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Anselin, Luc, 1992. "Space and applied econometrics : Introduction," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 307-316, September.
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