Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Prime Locations

Ahlfeldt, Gabriel ; Albers, Thilo LU and Behrens, Kristian (2020) In CEPR Discussion Paper
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
; and
publishing date
type
Working paper/Preprint
publication status
published
subject
in
CEPR Discussion Paper
issue
15470
ISSN
0265-8003
language
English
LU publication?
no
id
680e498d-41f7-4737-8014-b3ac2487a9d7
alternative location
http://cepr.org/active/publications/discussion_papers/dp.php?dpno=15470
date added to LUP
2020-12-10 16:23:50
date last changed
2020-12-10 16:46:10
@misc{680e498d-41f7-4737-8014-b3ac2487a9d7,
  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.}},
  author       = {{Ahlfeldt, Gabriel and Albers, Thilo and Behrens, Kristian}},
  issn         = {{0265-8003}},
  language     = {{eng}},
  note         = {{Working Paper}},
  number       = {{15470}},
  series       = {{CEPR Discussion Paper}},
  title        = {{Prime Locations}},
  url          = {{http://cepr.org/active/publications/discussion_papers/dp.php?dpno=15470}},
  year         = {{2020}},
}