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Spatial Interaction and Spatial Autocorrelation

In: Perspectives on Spatial Data Analysis

Author

Listed:
  • Manfred M. Fischer

    (Vienna University of Economics and Business)

  • Martin Reismann

    (Vienna University of Economics and Business)

  • Thomas Scherngell

    (Vienna University of Economics and Business)

Abstract

The objective is to combine insights from two research traditions, spatial interaction modelling and spatial autocorrelation modelling, to deal with the issue of spatial autocorrelation in spatial interaction data analysis. First, the problem is addressed from an exploratory perspective for which a generalisation of the Getis–Ord G statistic is presented. This statistic may yield interesting insights into the processes that give rise to spatial association between residual flows. Second, the log-additive spatial interaction model is extended to spatial econometric origin-destination flow models consistent with an error structure that reflects origin, destination or origin-destination autoregressive spatial dependence. The models are formally equivalent to conventional spatial regression models. But they differ in terms of the data analysed and the way in which the spatial weights matrix is defined.

Suggested Citation

  • Manfred M. Fischer & Martin Reismann & Thomas Scherngell, 2010. "Spatial Interaction and Spatial Autocorrelation," Advances in Spatial Science, in: Luc Anselin & Sergio J. Rey (ed.), Perspectives on Spatial Data Analysis, chapter 0, pages 61-79, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-01976-0_5
    DOI: 10.1007/978-3-642-01976-0_5
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    Cited by:

    1. Klapka, Pavel & Kraft, Stanislav & Halás, Marián, 2020. "Network based definition of functional regions: A graph theory approach for spatial distribution of traffic flows," Journal of Transport Geography, Elsevier, vol. 88(C).
    2. Nijkamp Peter, 2012. "Behaviour of Humans and Behaviour of Models in Dynamic Space," Quaestiones Geographicae, Sciendo, vol. 31(2), pages 7-19, June.
    3. Pinto, Pablo E. & Vallone, Andres & Honores, Guillermo, 2019. "The structure of collaboration networks: Findings from three decades of co-invention patents in Chile," Journal of Informetrics, Elsevier, vol. 13(4).

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