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Spatial interactions in urban scaling laws

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  • Eduardo G Altmann

Abstract

Analyses of urban scaling laws assume that observations in different cities are independent of the existence of nearby cities. Here we introduce generative models and data-analysis methods that overcome this limitation by modelling explicitly the effect of interactions between individuals at different locations. Parameters that describe the scaling law and the spatial interactions are inferred from data simultaneously, allowing for rigorous (Bayesian) model comparison and overcoming the problem of defining the boundaries of urban regions. Results in five different datasets show that including spatial interactions typically leads to better models and a change in the exponent of the scaling law.

Suggested Citation

  • Eduardo G Altmann, 2020. "Spatial interactions in urban scaling laws," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-12, December.
    • Handle: RePEc:plo:pone00:0243390
    DOI: 10.1371/journal.pone.0243390
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    References listed on IDEAS

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    1. Hernán D. Rozenfeld & Diego Rybski & Xavier Gabaix & Hernán A. Makse, 2011. "The Area and Population of Cities: New Insights from a Different Perspective on Cities," American Economic Review, American Economic Association, vol. 101(5), pages 2205-2225, August.
    2. Diego Rybski & Elsa Arcaute & Michael Batty, 2019. "Urban scaling laws," Environment and Planning B, , vol. 46(9), pages 1605-1610, November.
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    Cited by:

    1. Anthony FJ van Raan, 2024. "Simulating urban scaling with a term linkages network of a university," Environment and Planning B, , vol. 51(9), pages 2092-2107, November.

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