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Explaining the size distribution of cities: x-treme economies

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  • Berliant, Marcus
  • Watanabe, Hiroki

Abstract

We criticize the theories used to explain the size distribution of cities. They take an empirical fact and work backward to obtain assumptions on primitives. The induced theoretical assumptions on consumer behavior, particularly about their inability to insure against the city-level productivity shocks in the model, are untenable. With either self insurance or insurance markets, and either an arbitrarily small cost of moving or the assumption that consumers do not perfectly observe the shocks to firms' technologies, the agents will never move. Even without these frictions, our analysis yields another equilibrium with insurance where consumers never move. Thus, insurance is a substitute for movement. We propose an alternative class of models, involving extreme risk against which consumers will not insure. Instead, they will move, generating a Fréchet distribution of city sizes that is empirically competitive with other models.

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  • Berliant, Marcus & Watanabe, Hiroki, 2009. "Explaining the size distribution of cities: x-treme economies," MPRA Paper 13671, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:13671
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    References listed on IDEAS

    as
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    17. Jonathan Eaton & Samuel Kortum, 2002. "Technology, Geography, and Trade," Econometrica, Econometric Society, vol. 70(5), pages 1741-1779, September.
    Full references (including those not matched with items on IDEAS)

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    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. On the size of cities
      by Economic Logician in Economic Logic on 2011-09-28 19:08:00

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    Cited by:

    1. Charles Ka Yui Leung & Joe Cho Yiu Ng, 2018. "Macro Aspects of Housing," GRU Working Paper Series GRU_2018_016, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
    2. 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.
    3. Ho Yeon KIM & Petra de Jong & Jan Rouwendal & Aleid Brouwer, 2012. "Shrinking population and the urban hierarchy [Housing preferences and attribute importance among Dutch older adults: a conjoint choice experiment]," ERSA conference papers ersa12p350, European Regional Science Association.
    4. Oshiro, Jun & Sato, Yasuhiro, 2021. "Industrial structure in urban accounting," Regional Science and Urban Economics, Elsevier, vol. 91(C).
    5. Duranton, Gilles & Puga, Diego, 2014. "The Growth of Cities," Handbook of Economic Growth, in: Philippe Aghion & Steven Durlauf (ed.), Handbook of Economic Growth, edition 1, volume 2, chapter 5, pages 781-853, Elsevier.
    6. Wen-Tai Hsu & Thomas J. Holmes, 2009. "Optimal City Hierarchy: A Dynamic Programming Approach to Central Place Theory," 2009 Meeting Papers 342, Society for Economic Dynamics.
    7. 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.
    8. Christian Ghiglino & Kazuo Nishimura & Alain Venditti, 2020. "A theory of heterogeneous city growth," International Journal of Economic Theory, The International Society for Economic Theory, vol. 16(1), pages 27-37, March.
    9. Tomoya Mori & Tony E. Smith, 2009. "A Reconsideration of the NAS Rule from an Industrial Agglomeration Perspective," KIER Working Papers 669, Kyoto University, Institute of Economic Research.
    10. Kim, Ho Yeon, 2012. "Shrinking population and the urban hierarchy," IDE Discussion Papers 360, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    11. Ramos, Arturo & Sanz-Gracia, Fernando, 2015. "US city size distribution revisited: Theory and empirical evidence," MPRA Paper 64051, University Library of Munich, Germany.
    12. Behzod B. Ahundjanov & Sherzod B. Akhundjanov & Botir B. Okhunjanov, 2022. "Power law in COVID‐19 cases in China," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 699-719, April.

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    More about this item

    Keywords

    Zipf's Law; Gibrat's Law; Size Distribution of Cities; Extreme Value Theory;
    All these keywords.

    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)

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