Prime Locations
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 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.
Year of publication: |
2020
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Authors: | Ahlfeldt, Gabriel ; Albers, Thilo N. H. ; Behrens, Kristian |
Publisher: |
Munich : Center for Economic Studies and Ifo Institute (CESifo) |
Subject: | prime services | internal city structure | agent-based model | multiple equilibria and path dependence | transport networks |
Saved in:
freely available
Series: | CESifo Working Paper ; 8768 |
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Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Working Paper |
Language: | English |
Other identifiers: | 1743352441 [GVK] hdl:10419/229586 [Handle] RePec:ces:ceswps:_8768 [RePEc] |
Classification: | R38 - Government Policy ; R52 - Land Use and Other Regulations ; R58 - Regional Development Policy |
Source: |
Persistent link: https://www.econbiz.de/10012425674