Movatterモバイル変換


[0]ホーム

URL:


Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Human Behaviour
  • Letter
  • Published:

Explaining the prevalence, scaling and variance of urban phenomena

Nature Human Behaviourvolume 1, Article number: 0012 (2017)Cite this article

Subjects

Abstract

The prevalence of many urban phenomena changes systematically with population size1. We propose a theory that unifies models of economic complexity2,3 and cultural evolution4 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.

This is a preview of subscription content,access via your institution

Access options

Access through your institution

Subscribe to this journal

Receive 12 digital issues and online access to articles

¥14,900 per year

only ¥1,242 per issue

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

¥ 4,980

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Four facts across ten different urban phenomena that we seek to explain.
Figure 2: Relationship between inferred values of parametersG,H andGHlnN, across 43 different urban phenomena.
Figure 3: Predictions.

Similar content being viewed by others

References

  1. Bettencourt, L. M. A., Lobo, J., Helbing, D., Kìhnert, C. & West, G. B. Growth, innovation, scaling, and the pace of life in cities.Proc. Natl Acad. Sci. USA104, 7301–7306 (2007).

    Article CAS PubMed PubMed Central  Google Scholar 

  2. Hidalgo, C. A. & Hausmann, R. The building blocks of economic complexity.Proc. Natl Acad. Sci. USA106, 10570–10575 (2009).

    Article CAS PubMed PubMed Central  Google Scholar 

  3. Hausmann, R. & Hidalgo, C. A. The network structure of economic ouput.J. Econ. Growth16, 309–342 (2011).

    Article  Google Scholar 

  4. Henrich, J. Demography and cultural evolution: how adaptive cultural processes can produce maladaptive losses—the Tasmanian case.Am. Antiq.69, 197–214 (2004).

    Article  Google Scholar 

  5. Schroeder, M.Fractals, Chaos, Power Laws: Minutes from an Infinite Paradise (Freeman, 1991; republished Dover, 2009).

  6. Sornette, D. Critical Phenomena in Natural Sciences—Chaos, Fractals, Selforganization and Disorder: Concepts and Tools2nd edn (Springer, 2006).

    Google Scholar 

  7. West, G. B. & Brown, J. H. The origin of allometric scaling laws in biology from genomes to ecosystems: towards a quantitative unifying theory of biological structure and organization.J. Exp. Biol.208, 1575–1592 (2005).

    Article PubMed  Google Scholar 

  8. Gonzalez, M. C., Hidalgo, C. A. & Barabasi, A.-L. Understanding individual human mobility patterns.Nature453, 779–782 (2008).

    Article CAS PubMed  Google Scholar 

  9. McNerney, J., Farmer, J. D., Redner, S. & Trancik, J. E. Role of design complexity in technology improvement.Proc. Natl Acad. Sci. USA108, 9008–9013 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  10. Batty, M. The size, scale, and shape of cities.Science319, 769 (2008).

    Article CAS PubMed  Google Scholar 

  11. West, G. B., Brown, J. H. & Enquist, B. J. A general model for the origin of allometric scaling laws in biology.Science276, 122–126 (1997).

    Article CAS PubMed  Google Scholar 

  12. Banavar, J. R., Maritan, A. & Rinaldo, A. Size and form in efficient transportation networks.Nature399, 130–132 (1999).

    Article CAS PubMed  Google Scholar 

  13. Arbesman, S., Kleinberg, J. M. & Strogatz, S. H. Superlinear scaling for innovation in cities.Phys. Rev. E79, 016115 (2009).

    Article  Google Scholar 

  14. Pan, W., Ghoshal, G., Krumme, C., Cebrian, M. & Pentland, A. Urban characteristics attributable to density-driven tie formation.Nat. Commun.4, 1961 (2013).

    Article PubMed  Google Scholar 

  15. Bettencourt, L. M. A. The origins of scaling in cities.Science340, 1438 (2013).

    Article MathSciNet CAS PubMed  Google Scholar 

  16. Yakubo, K., Saijo, Y. & Korošak, D. Superlinear and sublinear urban scaling in geographical networks modeling cities.Phys. Rev. E90, 022803 (2014).

    Article CAS  Google Scholar 

  17. Banavar, J. R. et al. A general basis for quarter-power scaling in animals.Proc. Natl Acad. Sci. USA107, 15816–15820 (2010).

    Article CAS PubMed PubMed Central  Google Scholar 

  18. McMahon, T. Size and shape in biology.Science179, 1201–1204 (1973).

    Article CAS PubMed  Google Scholar 

  19. West, G. B., Brown, J. H. & Enquist, B. J. The fourth dimension of life: fractal geometry and allometric scaling of organisms.Science284, 1677–1679 (1999).

    Article MathSciNet CAS PubMed  Google Scholar 

  20. Samaniego, H. & Moses, M. E. Cities as organisms: allometric scaling of urban road networks.J. Transp. Land Use1, 21–39 (2008).

    Article  Google Scholar 

  21. Hidalgo, C. A., Klinger, B., Barabasi, A.-L. & Hausmann, R. The product space conditions the development of nations.Science317, 482–487 (2007).

    Article CAS PubMed  Google Scholar 

  22. Klimek, P., Hausmann, R. & Thurner, S. Empirical confirmation of creative destruction from world trade data.PLoS ONE7, 1–9 (2012).

    Article  Google Scholar 

  23. Henrich, J. & Boyd, R. On modeling cognition and culture: why cultural evolution does not require replication of representations.J. Cogn. Culture2, 87–112 (2002).

    Article  Google Scholar 

  24. Powell, A., Shennan, S. & Thomas, M. G. Late Pleistocene demography and the appearance of modern human behavior.Science324, 1298–1301 (2009).

    Article CAS PubMed  Google Scholar 

  25. Kline, M. A. & Boyd, R. Population size predicts technological complexity in oceania. Proc. R. Soc. Lond. B277, 2559–2564 (2010).

    Google Scholar 

  26. Mesoudi, A. Variable cultural acquisition costs constrain cumulative cultural evolution.PLoS ONE6, e18239 (2011).

    Article CAS PubMed PubMed Central  Google Scholar 

  27. Derex, M., Beugin, M.-P., Godelle, B. & Raymond, M. Experimental evidence for the influence of group size on cultural complexity.Nature503, 389–391 (2013).

    Article CAS PubMed  Google Scholar 

  28. Kempe, M. & Mesoudi, A. An experimental demonstration of the effect of group size on cultural accumulation.Evol. Hum. Behav.35, 285–290 (2014).

    Article  Google Scholar 

  29. Collard, M., Ruttle, A., Buchanan, B. & OBrien, M. J. Population size and cultural evolution in nonindustrial food-producing societies.PLoS ONE8, e72628 (2013).

    Article CAS PubMed PubMed Central  Google Scholar 

  30. Bromham, L., Hua, X., Fitzpatrick, T. G. & Greenhill, S. J. Rate of language evolution is affected by population size. Proc. Natl Acad. Sci. USA112, 2097–2102 (2015).

    Article CAS PubMed PubMed Central  Google Scholar 

  31. Brummitt, C. D., Gomez-Lievano, A., Goudemand, N. & Haslam, G. Hunting for keys to innovation: the diversity and mixing of occupations do not explain a city’s patent and economic productivity. InProc. Complex Systems Summer School Santa Fe Institute 1–13 (2012);https://www.santafe.edu/engage/learn/resources/csss-2012-proceedings

  32. Youn, H. et al. Scaling and universality in urban economic diversification.J. R. Soc. Interf.13,http://dx.doi.org/10.1098/rsif.2015.0937 (2016).

    Article PubMed PubMed Central  Google Scholar 

  33. Bettencourt, L. M., Samaniego, H. & Youn, H. Professional diversity and the productivity of cities.Sci. Rep.4, 5393 (2014).

    Article CAS PubMed PubMed Central  Google Scholar 

  34. Auerswald, P., Kauffman, S., Lobo, J. & Shell, K. The production recipes approach to modeling technological innovation: an application to learning by doing.J. Econ. Dynam. Control24, 389–450 (2000).

    Article  Google Scholar 

  35. Amabile, T.Creativity in Context (Westview, 1996).

    Google Scholar 

  36. Athens, L. H.The Creation of Dangerous Violent Criminals (Univ. Illinois Press, 1992).

    Google Scholar 

  37. Weitzman, M. L. Recombinant growth.Q. J. Econ.113, 331–360 (1998).

    Article MathSciNet  Google Scholar 

  38. Gomez-Lievano, A., Youn, H. & Bettencourt, L. M. A. The statistics of urban scaling and their connection to Zipf’s Law.PLoS ONE7, e40393 (2012).

    Article CAS PubMed PubMed Central  Google Scholar 

  39. Shalizi, C. R. Scaling and hierarchy in urban economies. Preprint athttp://arxiv.org/abs/1102.4101 (2011).

  40. Bettencourt, L. M. A., Lobo, J. & Youn, H. The hypothesis of urban scaling: formalization, implications and challenges. Preprint athttp://arxiv.org/abs/1301.5919v1 (2013).

  41. Mantovani, M. C., Ribeiro, H. V., Lenzi, E. K., Picoli, S. & Mendes, R. S. Engagement in the electoral processes: scaling laws and the role of political positions.Phys. Rev. E88, 024802 (2013).

    Article CAS  Google Scholar 

  42. Arcaute, E. et al. Constructing cities, deconstructing scaling laws.J. R. Soc. Interf.12, 20140745 (2014).

    Article  Google Scholar 

  43. Patterson-Lomba, O., Goldstein, E., Gómez-Liévano, A., Castillo-Chavez, C. & Towers, S. Per capita incidence of sexually transmitted infections increases systematically with urban population size: a cross-sectional study.Sex. Transm. Infect.91, 610–614 (2015).

    Article PubMed  Google Scholar 

  44. Neffke, F. & Henning, M. Skill relatedness and firm diversification.Strateg. Manag. J.34, 297–316 (2013).

    Article  Google Scholar 

  45. Duong, T. ks: kernel density estimation and kernel discriminant analysis for multivariate data in R.J. Stat. Softw.21, 1–16 (2007).

    Article  Google Scholar 

  46. Centers for Disease Control and Prevention.Sexually Transmitted Disease Surveillance 2012 (US Department of Health and Human Services, 2013).

  47. Florida, R.The Rise of the Creative Class: And How It’s Transforming Work, Leisure, Community and Everyday Life (Basic Books, 2004).

    Google Scholar 

Download references

Acknowledgements

We thank A.-L. Barabasi, J. Lobo, L. M. A. Bettencourt, F. Neffke, S. Valverde, D. Diodato and C. Brummitt for their comments on this work. We also thank M. Akmanalp and W. Strimling for their suggestions about aesthetics. This work was funded by the MasterCard Center for Inclusive Growth, and Alejandro Santo Domingo. O.P-L. acknowledges support by National Institutes of Health (NIH) grant T32AI007358-26. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Center for International Development, Harvard University, Cambridge, 02138, Massachusetts, USA

    Andres Gomez-Lievano & Ricardo Hausmann

  2. Harvard T.H. Chan School of Public Health, Harvard University, Boston, 02115, Massachusetts, USA

    Oscar Patterson-Lomba

  3. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, 87501, New Mexico, USA

    Ricardo Hausmann

  4. Harvard Kennedy School, Harvard University, Cambridge, 02138, Massachusetts, USA

    Ricardo Hausmann

Authors
  1. Andres Gomez-Lievano
  2. Oscar Patterson-Lomba
  3. Ricardo Hausmann

Contributions

A.G-L. and O.P-L. collected the data, and conceived and designed the study. A.G-L. conducted the analyses. A.G-L. and R.H. developed the model. A.G-L., O.P-L. and R.H. wrote the manuscript. All three authors reviewed and approved the paper.

Corresponding author

Correspondence toAndres Gomez-Lievano.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary Information

Supplementary Discussion, Supplementary Figures 1–7, Supplementary Data, Supplementary References. (PDF 2714 kb)

Supplementary Data

The file contains a set of single files, one for each urban phenomenon we studied (except for Sexually Transmitted Diseases, which we kept in a separate file), a README file, and an Excel file, which lists the different phenomena we used in our analysis with other parameters and field descriptions. (ZIP 364 kb)

Rights and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gomez-Lievano, A., Patterson-Lomba, O. & Hausmann, R. Explaining the prevalence, scaling and variance of urban phenomena.Nat Hum Behav1, 0012 (2017). https://doi.org/10.1038/s41562-016-0012

Download citation

This article is cited by

Access through your institution
Buy or subscribe

Associated content

Collection

Economics at Nature Research

Urban studies: Diverse cities, successful cities

  • Michael Batty
Nature Human BehaviourNews & Views

Advertisement

Search

Advanced search

Quick links

Nature Briefing

Sign up for theNature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox.Sign up for Nature Briefing

[8]ページ先頭

©2009-2026 Movatter.jp