Working Paper

Prime Locations

Gabriel Ahlfeldt, Thilo N. H. Albers, Kristian Behrens
CESifo, Munich, 2020

CESifo Working Paper No. 8768

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.

CESifo Category
Public Choice
Empirical and Theoretical Methods
Keywords: prime services, internal city structure, agent-based model, multiple equilibria and path dependence, transport networks
JEL Classification: R380, R520, R580