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Prime locations

Gabriel Ahlfeldt, Thilo Albers and Kristian Behrens

No 15470, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We harness big data to detect prime locations---large clusters of know-ledge-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 away 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: agent-based model; internal city structure; multiple equilibria and path dependence; Prime services; transport networks (search for similar items in EconPapers)
JEL-codes: R38 R52 R58 (search for similar items in EconPapers)
Date: 2020-11
New Economics Papers: this item is included in nep-cmp and nep-ure
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Working Paper: Prime locations (2020) Downloads
Working Paper: Prime Locations (2020) Downloads
Working Paper: Prime locations (2020) Downloads
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