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Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology

Author

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  • LeSage, James P.

    (Texas State University- San Marcos)

  • Pace, Robert Kelley

    (Louisiana State University)

Abstract

Spatial regression methodology has been around for most of the 50 years (1961-2011) that the Southern Regional Science Association has been in existence. Cliff and Ord (1969) devised a parsimonious specification for the structure of spatial dependence among observations that could be used to empirically model spatial interdependence. Later work (Cliff and Ord, 1973, 1981; Ord, 1975) further developed these ideas into basic spatial regression models, which were popularized and augmented by Anselin (1988). We discuss several issues that have arisen in recent work that attempts to extend basic models of spatial interdependence to include more types of spatial and non-spatial interdependencies. Understanding these issues should help future work avoid several pitfalls that plague current and past attempts at extensions along these lines.

Suggested Citation

  • LeSage, James P. & Pace, Robert Kelley, 2011. "Pitfalls in Higher Order Model Extensions of Basic Spatial Regression Methodology," The Review of Regional Studies, Southern Regional Science Association, vol. 41(1), pages 13-26, Summer.
    • Handle: RePEc:rre:publsh:v:41:y:2011:i:1:p:13-26
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    Keywords

    higher order spatial regression models;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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