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How to Get Rid of W: A Latent Variables Approach to Modelling Spatially Lagged Variables

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  • Henk Folmer

    (Department of Spatial Sciences, University of Groningen, PO Box 800, NL-9700AV Groningen, The Netherlands, and Department of Social Sciences, Wageningen University, PO Box 8130, NL-6700 EW Wageningen, The Netherlands)

  • Johan Oud

    (Behavioural Science Institute, Radboud University Nijmegen, PO Box 9104, NL-6500 HE Nijmegen, The Netherlands)

Abstract

In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are indicators. This approach allows us to incorporate and test more information on spatial dependence and offers more flexibility than the representation in terms of Wy or Wx. Furthermore, we adapt the ML estimator included in the software package Mx to estimate SEMs with spatial dependence. We present illustrations based on Anselin's Columbus, Ohio, crime dataset.

Suggested Citation

  • Henk Folmer & Johan Oud, 2008. "How to Get Rid of W: A Latent Variables Approach to Modelling Spatially Lagged Variables," Environment and Planning A, , vol. 40(10), pages 2526-2538, October.
    • Handle: RePEc:sae:envira:v:40:y:2008:i:10:p:2526-2538
    DOI: 10.1068/a4078
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    References listed on IDEAS

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    1. Bernard Fingleton, 2003. "Externalities, Economic Geography, And Spatial Econometrics: Conceptual And Modeling Developments," International Regional Science Review, , vol. 26(2), pages 197-207, April.
    2. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
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