Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/234812 
Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
Document de travail No. 2020-12
Verlag: 
Université du Québec à Montréal, École des sciences de la gestion (ESG UQAM), Département des sciences économiques, Montréal
Zusammenfassung: 
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.
Schlagwörter: 
Prime services
internal city structure
agent-based model
multiple equilibria and path dependence
transport networks
JEL: 
R38
R52
R58
Dokumentart: 
Working Paper

Datei(en):
Datei
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