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Productivity and the Density of Economic Activity
Open accessAbstract
To explain the large differences in labor productivity across U.S. states, the authors estimate two models--one based on local geographical externalities and the other on the diversity of local intermediate services--where spatial density results in aggregate increasing returns. Both models lead to a relation between county employment density and productivity at the state level. Using data on gross state output, the authors find that a doubling of employment density increases average labor productivity by around 6 percent. More than half of the variance of output per worker across states can be explained by differences in the density of economic activity. Copyright 1996 by American Economic Association.
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Citations
Cited by
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Keller, W. (2002) · American Economic Review · doi:10.1257/000282802760015630 · Cited by 1,227
The Determinants of Agglomeration
Rosenthal, S. S., & Strange, W. C. (2001) · Journal of Urban Economics · doi:10.1006/juec.2001.2230 · Cited by 1,161
THE MAGNITUDE AND CAUSES OF AGGLOMERATION ECONOMIES
Puga, D. (2010) · Journal of Regional Science · doi:10.1111/j.1467-9787.2009.00657.x · Cited by 939
The Determinants of Regional Variation in New Firm Formation
Armington, C., & Acs, Z. J. (2002) · Regional Studies · doi:10.1080/00343400120099843 · Cited by 837
“Market Structure and Productivity: A Concrete Example”
Syverson, C. (2004) · Journal of Political Economy · doi:10.1086/424743 · Cited by 683
Metadata
- Authors
- Ciccone, A., & Hall, R.
- Venue
- National Bureau of Economic Research
- Publisher
- National Bureau of Economic Research
- Published
- 1993-04
- OpenAlex
- W2161648066
- Cited by
- 2,046
- References
- 0
- Type
- report
- Language
- en
- Open access
- green
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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.
