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Prime locations

Gabriel M. Ahlfeldt, Thilo Albers and Kristian Behrens

CEP Discussion Papers from Centre for Economic Performance, LSE

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.

Keywords: prime services; internal city structure; agent-based model; multiple equilibria and path dependence; transport networks; cities; economic geography (search for similar items in EconPapers)
JEL-codes: R38 R52 R58 (search for similar items in EconPapers)
Date: 2020-10-05
New Economics Papers: this item is included in nep-cmp, nep-geo and nep-ure
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Citations: View citations in EconPapers (2) Track citations by RSS feed

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https://cep.lse.ac.uk/pubs/download/dp1725.pdf (application/pdf)

Related works:
Working Paper: Prime Locations (2020) Downloads
Working Paper: Prime locations (2020) Downloads
Working Paper: Prime locations (2020) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:cep:cepdps:dp1725

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