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Socio-Spatial Dynamics and Discrete Non-Linear Probabilistic Chains

In: Tool Kits in Regional Science

Author

Listed:
  • Michael Sonis

    (Bar-Ilan University)

  • Dimitrios S. Dendrinos

    (University of Kansas)

Abstract

This chapter reviews the recent developments that have occurred in the field of discrete socio-spatial dynamics (DSS Dynamics) during the decade after the publication of the book by Dendrinos and Sonis (1990). DSS Dynamics focuses on the redistribution dynamics of m different statistical populations (stocks) relatively distributed between n different locations (or choosing n different choice alterna1tives). Examples of such stocks could be m different populations or labor types, distinct capital stocks (classified, for example, according to vintage); financial capital (currencies), different types of economic outputs (products) or any economic, social, political and other of socio-spatial variables, or combinations of them. The transfer from time period t to the time period t+1 naturally generates a probabilistic chain describing the evolutionary redistribution process. The relationships between distributions of m populations in n locations in times t, t+1,…, t+n,… can be presented with the help of generating functions reflecting the changes in composite temporal and locational comparative advantages enjoyed by any social stock in different locations in different time periods.

Suggested Citation

  • Michael Sonis & Dimitrios S. Dendrinos, 2009. "Socio-Spatial Dynamics and Discrete Non-Linear Probabilistic Chains," Advances in Spatial Science, in: Michael Sonis & Geoffrey J. D. Hewings (ed.), Tool Kits in Regional Science, chapter 7, pages 177-197, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-00627-2_7
    DOI: 10.1007/978-3-642-00627-2_7
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    Cited by:

    1. Hiroshi Sakamoto, 2011. "Inter-regional spillovers in Fukuoka Prefecture: Using VAR model," ERSA conference papers ersa11p360, European Regional Science Association.
    2. Sakamoto, Hiroshi, 2013. "Prediction of the Prefectural Economy in Japan Using a Stochastic Model," AGI Working Paper Series 2013-02, Asian Growth Research Institute.

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