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Prime locations

Author

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  • Ahlfeldt, Gabriel Peter Gabriel Martins
  • Albers, Thilo Nils Hendrix
  • Behrens, Kristian

Abstract

We harness big data to detect prime locations - large clusters of knowledge-based tradable services - in 125 global cities and track changes in the within-city geography of prime service jobs over a century. Historically smaller cities that did not develop early public transit networks are less concentrated today and have prime locations farther from their historic cores. We rationalize these findings in an agent-based model that features extreme agglomeration, multiple equilibria, and path dependence. Both city size and public transit networks anchor city structure. Exploiting major disasters and using a novel instrument - subway potential - we provide causal evidence for these mechanisms and disentangle size- from transport network effects.

Suggested Citation

  • Ahlfeldt, Gabriel Peter Gabriel Martins & Albers, Thilo Nils Hendrix & Behrens, Kristian, 2020. "Prime locations," LSE Research Online Documents on Economics 108470, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:108470
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    Cited by:

    1. is not listed on IDEAS
    2. Ahlfeldt, Gabriel M. & Barr, Jason, 2022. "The economics of skyscrapers: A synthesis," Journal of Urban Economics, Elsevier, vol. 129(C).

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    Keywords

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    JEL classification:

    • R38 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Government Policy
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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