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A scale‐free transportation network explains the city‐size distribution

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  • Marcus Berliant
  • Axel H. Watanabe

Abstract

Zipf's law is one of the best known empirical regularities in urban economics. There is extensive research on the subject, where each city is treated symmetrically in terms of the cost of transactions with other cities. Recent developments in network theory facilitate the examination of an asymmetric transport network. In a scale‐free network, the chance of observing extremes in network connections becomes higher than the Gaussian distribution predicts and, therefore, it explains the emergence of large clusters. The city‐size distribution shares the same pattern. This paper decodes how accessibility of a city to other cities on the transportation network can boost its local economy and explains the city‐size distribution as a result of its underlying transportation network structure. We confirm our model predictions with US and Belgian data. Finally, we discuss the endogenous evolution of transport networks.

Suggested Citation

  • Marcus Berliant & Axel H. Watanabe, 2018. "A scale‐free transportation network explains the city‐size distribution," Quantitative Economics, Econometric Society, vol. 9(3), pages 1419-1451, November.
    • Handle: RePEc:wly:quante:v:9:y:2018:i:3:p:1419-1451
    DOI: 10.3982/QE619
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    Cited by:

    1. P. Nijkamp & A. Reggiani, 2012. "Did Zipf Anticipate Socio-Economic Spatial Networks?," Working Papers wp816, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Ahmed Saber Mahmud, 2025. "Network formation and agglomeration," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 74(3), pages 1-51, September.
    3. Axel Watanabe, 2020. "The Size Distribution of Cities with Distance-Bound Households," Working Papers 20001, Concordia University, Department of Economics.
    4. Ahmed Saber Mahmud, 2021. "How do All Roads Lead to Rome? The Story of Transportation Network Inducing Agglomeration," Networks and Spatial Economics, Springer, vol. 21(2), pages 419-464, June.
    5. Ahmed Saber Mahmud, 2022. "Demand-pull versus cost-push: monocentric equilibrium in a spatial network," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 69(2), pages 455-485, October.
    6. Wei Zhu & Ding Ma & Zhigang Zhao & Renzhong Guo, 2020. "Investigating the Complexity of Spatial Interactions between Different Administrative Units in China Using Flickr Data," Sustainability, MDPI, vol. 12(22), pages 1-12, November.

    More about this item

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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    1. A scale‐free transportation network explains the city‐size distribution (Quantitative Economics 2018) in ReplicationWiki

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