Skip to main content

Thank you for visiting 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.

Complex economic activities concentrate in large cities


Human activities, such as research, innovation and industry, concentrate disproportionately in large cities. The ten most innovative cities in the United States account for 23% of the national population, but for 48% of its patents and 33% of its gross domestic product. But why has human activity become increasingly concentrated? Here we use data on scientific papers, patents, employment and gross domestic product, for 353 metropolitan areas in the United States, to show that the spatial concentration of productive activities increases with their complexity. Complex economic activities, such as biotechnology, neurobiology and semiconductors, concentrate disproportionately in a few large cities compared to less--complex activities, such as apparel or paper manufacturing. We use multiple proxies to measure the complexity of activities, finding that complexity explains from 40% to 80% of the variance in urban concentration of occupations, industries, scientific fields and technologies. Using historical patent data, we show that the spatial concentration of cutting-edge technologies has increased since 1850, suggesting a reinforcing cycle between the increase in the complexity of activities and urbanization. These findings suggest that the growth of spatial inequality may be connected to the increasing complexity of the economy.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Spatial concentration of activities.
Fig. 2: Urban concentration increases with knowledge complexity.
Fig. 3: Evolution of the urban scaling of technologies.

Data availability

The data that support the findings of this study are available from the corresponding author upon request.

Code availability

The code that supports the findings of this study is available from the corresponding author upon request.


  1. 1.

    Florida, R. The New Urban Crisis: How Our Cities Are Increasing Inequality, Deepening Segregation, and Failing the Middle Class—and What We Can Do About It (Basic Books, 2017).

  2. 2.

    Diamond, R. The determinants and welfare implications of US workers’ diverging location choices by skill: 1980–2000. Am. Econ. Rev. 106, 479–524 (2016).

    Article  Google Scholar 

  3. 3.

    Berry, C. R. & Glaeser, E. L. The divergence of human capital levels across cities. Pap. Reg. Sci. 84, 407–444 (2005).

    Article  Google Scholar 

  4. 4.

    Hidalgo, C. A. & Hausmann, R. The building blocks of economic complexity. Proc. Natl Acad. Sci. USA 106, 10570–10575 (2009).

    CAS  Article  Google Scholar 

  5. 5.

    Balland, P.-A. & Rigby, D. The geography of complex knowledge. Econ. Geogr. 93, 1–23 (2017).

    Article  Google Scholar 

  6. 6.

    Hidalgo, C. Why Information Grows: The Evolution of Order, from Atoms to Economies (Basic Books, 2015).

  7. 7.

    Hausmann, R. et al. The Atlas of Economic Complexity: Mapping Paths to Prosperity (MIT Press, 2014).

  8. 8.

    Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C. & West, G. B. Growth, innovation, scaling, and the pace of life in cities. Proc. Natl Acad. Sci. USA 104, 7301–7306 (2007).

    CAS  Article  Google Scholar 

  9. 9.

    Bettencourt, L. & West, G. A unified theory of urban living. Nature 467, 912–913 (2010).

    CAS  Article  Google Scholar 

  10. 10.

    Bettencourt, L. M. A. The origins of scaling in cities. Science 340, 1438–1441 (2013).

    CAS  Article  Google Scholar 

  11. 11.

    Youn, H. et al. Scaling and universality in urban economic diversification. J. R. Soc. Interface 13, 20150937 (2016).

    Article  Google Scholar 

  12. 12.

    Warsh, D. Knowledge and the Wealth of Nations: A Story of Economic Discovery (W. W. Norton & Co., 2007).

  13. 13.

    Jones, B. F. The burden of knowledge and the “Death of the Renaissance Man”: is innovation getting harder? Rev. Econ. Stud. 76, 283–317 (2009).

    Article  Google Scholar 

  14. 14.

    Scott, A. J. & Storper, M. The nature of cities: the scope and limits of urban theory. Int. J. Urban Reg. Res. 39, 1–15 (2015).

    Article  Google Scholar 

  15. 15.

    Gans, J. S. & Stern, S. The product market and the market for “ideas”: commercialization strategies for technology entrepreneurs. Res. Policy 32, 333–350 (2003).

    Article  Google Scholar 

  16. 16.

    Feldman, M. P. & Audretsch, D. B. Innovation in cities: science-based diversity, specialization and localized competition. Eur. Econ. Rev. 43, 409–429 (1999).

    Article  Google Scholar 

  17. 17.

    Glaeser, E. L., Kallal, H. D., Scheinkman, J. A. & Shleifer, A. Growth in cities. J. Political Econ. 100, 1126–1152 (1992).

    Article  Google Scholar 

  18. 18.

    Hidalgo, C. A. et al. in Unifying Themes in Complex Systems IX (eds Morales, A. J. et al.) 451–457 (Springer, 2018).

  19. 19.

    Hidalgo, C. A., Klinger, B., Barabási, A.-L. & Hausmann, R. The product space conditions the development of nations. Science 317, 482–487 (2007).

    CAS  Article  Google Scholar 

  20. 20.

    Zheng, S., Sun, W., Wu, J. & Kahn, M. E. The birth of edge cities in China: measuring the effects of industrial parks policy. J. Urban Econ. 100, 80–103 (2017).

    Article  Google Scholar 

  21. 21.

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

    Article  Google Scholar 

  22. 22.

    Jara-Figueroa, C., Jun, B., Glaeser, E. L. & Hidalgo, C. A. The role of industry-specific, occupation-specific, and location-specific knowledge in the growth and survival of new firms. Proc. Natl Acad. Sci. USA 115, 12646–12653 (2018).

    CAS  Article  Google Scholar 

  23. 23.

    Park, J. et al. Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters. Nat. Commun. 10, 3449 (2019).

    CAS  Article  Google Scholar 

  24. 24.

    Klepper, S. Employee startups in high‐tech industries. Ind. Corp. Change 10, 639–674 (2001).

    Article  Google Scholar 

  25. 25.

    Breschi, S. & Lissoni, F. in Handbook of Quantitative Science and Technology Research: The Use of Publication and Patent Statistics in Studies of S&T Systems (eds Moed, H. F. et al.) 613–643 (Springer, 2005).

  26. 26.

    Feldman, M. P. & Florida, R. The geographic sources of innovation: technological infrastructure and product innovation in the united states. Ann. Assoc. Am. Geogr. 84, 210–229 (1994).

    Article  Google Scholar 

  27. 27.

    Romer, P. M. Endogenous technological change. J. Political Econ. 98, S71–S102 (1990).

    Article  Google Scholar 

  28. 28.

    Moretti, E. The New Geography of Jobs (Houghton Mifflin Harcourt, 2012).

  29. 29.

    Fleming, L. & Sorenson, O. Technology as a complex adaptive system: evidence from patent data. Res. Policy 30, 1019–1039 (2001).

    Article  Google Scholar 

  30. 30.

    Mukherjee, S., Romero, D. M., Jones, B. & Uzzi, B. The nearly universal link between the age of past knowledge and tomorrow’s breakthroughs in science and technology: the hotspot. Sci. Adv. 3, e1601315 (2017).

    Article  Google Scholar 

  31. 31.

    Wuchty, S., Jones, B. F. & Uzzi, B. The increasing dominance of teams in production of knowledge. Science 316, 1036–1039 (2007).

    CAS  Article  Google Scholar 

  32. 32.

    Wu, L., Wang, D. & Evans, J. A. Large teams develop and small teams disrupt science and technology. Nature 566, 378–382 (2019).

    CAS  Article  Google Scholar 

  33. 33.

    Polanyi, M. The Tacit Dimension (Univ. Chicago Press, 2009).

  34. 34.

    Collins, H. Tacit and Explicit Knowledge (Univ. Chicago Press, 2010).

  35. 35.

    Friedman, T. L. The World Is Flat 3.0: A Brief History of the Twenty-First Century (Picador, 2007).

  36. 36.

    Florida, R. The world is spiky. Atl. Mon. 296, 48–51 (2005).

    Google Scholar 

  37. 37.

    He, C. & Zhu, S. Evolutionary Economic Geography in China (Springer, 2019).

  38. 38.

    Zhu, S., He, C. & Zhou, Y. How to jump further and catch up? Path-breaking in an uneven industry space. J. Econ. Geogr. 17, 521–545 (2017).

    Google Scholar 

  39. 39.

    Alshamsi, A., Pinheiro, F. L. & Hidalgo, C. A. Optimal diversification strategies in the networks of related products and of related research areas. Nat. Commun. 9, 1328 (2018).

    Article  Google Scholar 

  40. 40.

    Lee, K. & Lim, C. Technological regimes, catching-up and leapfrogging: findings from the Korean industries. Res. Policy 30, 459–483 (2001).

    Article  Google Scholar 

  41. 41.

    Lee, K. & Malerba, F. Catch-up cycles and changes in industrial leadership: windows of opportunity and responses of firms and countries in the evolution of sectoral systems. Res. Policy 46, 338–351 (2017).

    Article  Google Scholar 

  42. 42.

    Petralia, S., Balland, P.-A. & Rigby, D. L. Unveiling the geography of historical patents in the United States from 1836 to 1975. Sci. Data 3, 160074 (2016).

    CAS  Article  Google Scholar 

  43. 43.

    Hall, B. H., Jaffe, A. B. & Trajtenberg, M. The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools (National Bureau of Economic Research, 2001).

  44. 44.

    Nomaler, Ö., Frenken, K. & Heimeriks, G. On scaling of scientific knowledge production in U.S. metropolitan areas. PLoS One 9, e110805 (2014).

    Article  Google Scholar 

  45. 45.

    Patience, G. S., Patience, C. A., Blais, B. & Bertrand, F. Citation analysis of scientific categories. Heliyon 3, e00300 (2017).

    Article  Google Scholar 

Download references


We thank Ö. Nomaler, K. Frenken and G. Heimeriks for providing the data on scientific publications used in the main text, and G. Patience, C. Patience, B. Blais and F. Bertrand for providing the data on the age of references listed in scientific publications. We also thank R. Boschma, K. Frenken, M. Storper, A. J. Scott, T. Broekel, B. Jun, F. Pinheiro, A. Alshamsi and F. Neffke for useful comments and suggestions. Financial support from the Regional Studies Association through the Early Career Grant awarded to P.-A.B. is gratefully acknowledged. C.A.H. acknowledges support from the MIT Media Lab consortia, from the MIT-Skoltech seed grant and from the MIT-Masdar initiative. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information




P.-A.B., C.J.-F., S.G.P., M.P.A.S., D.L.R. and C.A.H. all contributed equally to the work and have supervised it jointly.

Corresponding author

Correspondence to Pierre-Alexandre Balland.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editors: Mary Elizabeth Sutherland; Stavroula Kousta.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–29 and Supplementary Tables 1–4.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Balland, PA., Jara-Figueroa, C., Petralia, S.G. et al. Complex economic activities concentrate in large cities. Nat Hum Behav 4, 248–254 (2020).

Download citation

Further reading


Quick links

Nature Briefing

Sign up for the Nature 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