Agglomeration: A long-run panel data approach

W. Walker Hanlon*, Antonio Miscio

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

This paper studies the sources of agglomeration economies in cities. We begin by incorporating within and cross-industry spillovers into a dynamic spatial equilibrium model in order to obtain a panel data estimating equation. This gives us a framework for measuring a rich set of agglomeration forces while controlling for a variety of potentially confounding effects. We apply this estimation strategy to detailed new data describing the industry composition of 31 English cities from 1851 to 1911. Our results show that industries grew more rapidly in cities where they had more local suppliers or other occupationally-similar industries. We find no evidence of dynamic within-industry effects, i.e., industries generally did not grow more rapidly in cities in which they were already large. Once we control for these agglomeration forces, we find evidence of strong dynamic congestion forces related to city size. We also show how to construct estimates of the combined strength of the many agglomeration forces in our model. These results suggest a lower bound estimate of the strength of agglomeration forces equivalent to a city-size divergence rate of 1.6–2.3% per decade.

Original languageEnglish (US)
Pages (from-to)1-14
Number of pages14
JournalJournal of Urban Economics
Volume99
DOIs
StatePublished - May 1 2017
Externally publishedYes

Keywords

  • Agglomeration
  • City growth

ASJC Scopus subject areas

  • Economics and Econometrics
  • Urban Studies

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