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Modelling the emergence of spatial patterns of economic activity

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  • Jung-Hun Yang
  • Dick Ettema
  • Koen Frenken

Abstract

Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. A simple model was proposed by Simon, who assumed that firms grow at a rate proportional to their size, and that new divisions of firms with certain probabilities relocate to other firms or to new centres of economic activity. Simon's model produces realistic results in the sense that the sizes of economic centres follow a Zipf distribution, which is also observed in reality. It lacks realism in the sense that mechanisms such as cluster formation, congestion (defined as an overly high density of the same activities) and dependence on the spatial distribution of external parties (clients, labour markets) are ignored. The present paper proposed an extension of the Simon model that includes both centripetal and centrifugal forces. Centripetal forces are included in the sense that firm divisions are more likely to settle in locations that offer a higher accessibility to other firms. Centrifugal forces are represented by an aversion of a too high density of activities in the potential location. The model is implemented as an agent-based simulation model in a simplified spatial setting. By running both the Simon model and the extended model, comparisons are made with respect to their effects on spatial configurations. To this end a series of metrics are used, including the rank-size distribution and indices of the degree of clustering and concentration.

Suggested Citation

  • Jung-Hun Yang & Dick Ettema & Koen Frenken, 2012. "Modelling the emergence of spatial patterns of economic activity," Papers 1204.6638, arXiv.org.
  • Handle: RePEc:arx:papers:1204.6638
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    File URL: http://arxiv.org/pdf/1204.6638
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    Cited by:

    1. DELLOYE, Justin & PEETERS, Dominique & THOMAS, Isabelle, 2015. "On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography," LIDAM Reprints CORE 2678, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Jung-Hun Yang & Kwang-Woo Nam, 2022. "Modelling the Relationship of Infrastructure and Externalities Using Urban Scaling," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    3. Marcel Ausloos & Herbert Dawid & Ugo Merlone, 2015. "Spatial Interactions in Agent-Based Modeling," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 353-377, Springer.
    4. Justin Delloye & Dominique Peeters & Isabelle Thomas, 2015. "On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-17, August.

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