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Explaining the Prevalence, Scaling and Variance of Urban Phenomena

Author

Listed:
  • Andres Gomez-Lievano

    (Center for International Development at Harvard University)

  • Oscar Patterson-Lomba

    (Harvard T.H. Chan School of Public Health)

  • Ricardo Hausmann

    (Center for International Development at Harvard University)

Abstract

The prevalence of many urban phenomena changes systematically with population size. We propose a theory that unifies models of economic complexity, and cultural evolution to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.

Suggested Citation

  • Andres Gomez-Lievano & Oscar Patterson-Lomba & Ricardo Hausmann, 2016. "Explaining the Prevalence, Scaling and Variance of Urban Phenomena," CID Working Papers 329, Center for International Development at Harvard University.
    • Handle: RePEc:cid:wpfacu:329
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    File URL: http://growthlab.cid.harvard.edu/files/growthlab/files/urban_phenomena_cidwp329.pdf
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    Citations

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    Cited by:

    1. Fritsch, Michael & Wyrwich, Michael, 2021. "Is innovation (increasingly) concentrated in large cities? An international comparison," Research Policy, Elsevier, vol. 50(6).
    2. Fabiano L Ribeiro & Joao Meirelles & Vinicius M Netto & Camilo Rodrigues Neto & Andrea Baronchelli, 2020. "On the relation between transversal and longitudinal scaling in cities," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-20, May.
    3. Andres Gomez-Lievano, 2018. "Methods and Concepts in Economic Complexity," Papers 1809.10781, arXiv.org, revised Oct 2018.
    4. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(3).
    5. Oscar Patterson-Lomba & Andres Gomez-Lievano, 2018. "On the Scaling Patterns of Infectious Disease Incidence in Cities," CID Working Papers 94a, Center for International Development at Harvard University.
    6. Li, Yang & Neffke, Frank M.H., 2024. "Evaluating the principle of relatedness: Estimation, drivers and implications for policy," Research Policy, Elsevier, vol. 53(3).
    7. Balland, Pierre-Alexandre & Broekel, Tom & Diodato, Dario & Giuliani, Elisa & Hausmann, Ricardo & O'Clery, Neave & Rigby, David, 2022. "Reprint of The new paradigm of economic complexity," Research Policy, Elsevier, vol. 51(8).
    8. Elisa Heinrich Mora & Jacob J. Jackson & Cate Heine & Geoffrey B. West & Vicky Chuqiao Yang & Christopher P. Kempes, 2021. "Scaling of Urban Income Inequality in the United States," Papers 2102.13150, arXiv.org.
    9. Andres Gomez-Lievano & Vladislav Vysotsky & Jose Lobo, 2018. "Artificial Increasing Returns to Scale and the Problem of Sampling from Lognormals," Papers 1807.09424, arXiv.org, revised Jul 2020.
    10. Zhou Huang & Ganmin Yin & Xia Peng & Xiao Zhou & Quanhua Dong, 2023. "Quantifying the environmental characteristics influencing the attractiveness of commercial agglomerations with big geo-data," Environment and Planning B, , vol. 50(9), pages 2470-2490, November.
    11. Andres Gomez-Lievano & Oscar Patterson-Lomba, 2018. "Estimating the drivers of urban economic complexity and their connection to economic performance," Papers 1812.02842, arXiv.org, revised Sep 2021.
    12. Xu, Gang & Xu, Zhibang & Gu, Yanyan & Lei, Weiqian & Pan, Yupiao & Liu, Jie & Jiao, Limin, 2020. "Scaling laws in intra-urban systems and over time at the district level in Shanghai, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    13. Ruiqi Li & Lingyun Lu & Weiwei Gu & Shaodong Ma & Gang Xu & H. Eugene Stanley, 2020. "Assessing the attraction of cities on venture capital from a scaling law perspective," Papers 2011.06287, arXiv.org.
    14. Martin Arvidsson & Niclas Lovsjö & Marc Keuschnigg, 2023. "Urban scaling laws arise from within-city inequalities," Nature Human Behaviour, Nature, vol. 7(3), pages 365-374, March.
    15. Ryan C Taylor & Xiaofan Liang & Manfred D Laubichler & Geoffrey B West & Christopher P Kempes & Marion Dumas, 2021. "Systematic shifts in scaling behavior based on organizational strategy in universities," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-21, October.
    16. Yang Li & Frank Neffke, 2022. "Relatedness in regional development: in search of the right specification," Papers in Evolutionary Economic Geography (PEEG) 2208, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Apr 2022.

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    Keywords

    urban phenomena;

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