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Cited by 647

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Geographic Concentration as a Dynamic Process

Dumais, Guy, Ellison, Glenn, Glaeser, Edward L.·2002·Review of Economics and Statistics
DOI 10.1162/003465302317411479
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Abstract

This paper uses data from the Census Bureau's Longitudinal Research Database to describe the dynamics of geographic concentration in U.S. manufacturing industries. Agglomeration results from a combination of the mean reversion and randomness in the growth of state-industry employment. Although industries' agglomeration levels have declined only slightly over the last quarter century, we find a great deal of movement for many geographically concentrated industries. We decompose aggregate concentration changes into portions attributable to plant births, expansions, contractions, and closures. We find that the location choices of new firms play a deagglomerating role, whereas plant closures have tended to reinforce agglomeration.

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Metadata

Authors
Dumais, G., Ellison, G., & Glaeser, E. L.
Venue
Review of Economics and Statistics
Publisher
MIT Press - Journals
Published
2002-05
Volume
84
Issue
2
Pages
193-204
ISSN
  • 0034-6535 (ISSN-L)
  • 1530-9142
DOI
10.1162/003465302317411479
OpenAlex
W2890394277
Cited by
647
References
0
FWCI
72.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Geographic Concentration as a Dynamic Process. https://app.cochat.ai/papers/10.1162/003465302317411479
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Dumais, G., Ellison, G., & Glaeser, E. L. (2002). Geographic Concentration as a Dynamic Process. Review of Economics and Statistics. https://doi.org/10.1162/003465302317411479

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.