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Matching and Learning in Cities: Urban Density and the Rate of Invention

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  • Gerald Carlino
  • Satyajit Chatterjee
  • Robert Hunt

Abstract

This paper examines the role local labor markets play in the production of innovations. The authors appeal to a labor market matching model (á la Berliant, Reed, and Wang 2004) to argue that in dense urban areas, workers are more selective in their matches and are therefore more productive. They find that, all else equal, patent intensity (patents per capita) is 20 percent higher in a metropolitan area with an employment density (jobs per square mile) twice that of another metropolitan area. Since local employment density doubles nearly four times across their sample, the implied gains in inventive output are substantial. In addition, the authors find evidence of an optimal employment density, i.e., one that maximizes patent intensity, of about 2,150 jobs per square mile–roughly the level of Baltimore or Philadelphia. They also find that, all else equal, a city with a more competitive market structure, or one that is not too large (a population less than 1 million) will have a higher patent intensity. These findings confirm the widely held view that the nation's densest locations play an important role in creating the flow of ideas that generate innovation and growth. ; Superseded by Working Paper 06-14

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Paper provided by UCLA Department of Economics in its series Levine's Bibliography with number 784828000000000160.

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Date of creation: 29 Jun 2005
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Handle: RePEc:cla:levrem:784828000000000160

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  1. Griliches, Zvi, 1990. "Patent Statistics as Economic Indicators: A Survey," Journal of Economic Literature, American Economic Association, vol. 28(4), pages 1661-1707, December.
  2. James E. Rauch, 1991. "Productivity Gains From Geographic Concentration of human Capital: Evidence From the Cities," NBER Working Papers 3905, National Bureau of Economic Research, Inc.
  3. Peter Thompson & Melanie Fox-Kean, 2005. "Patent Citations and the Geography of Knowledge Spillovers: A Reassessment," American Economic Review, American Economic Association, vol. 95(1), pages 450-460, March.
  4. Marcus Berliant & Robert R. Reed III & Ping Wang, 2005. "Knowledge Exchange, Matching, and Agglomeration," Urban/Regional, EconWPA 0506013, EconWPA, revised 07 Jul 2005.
  5. Glaeser, Edward Ludwig & Kallal, Hedi D. & Scheinkman, Jose A. & Shleifer, Andrei, 1992. "Growth in Cities," Scholarly Articles 3451309, Harvard University Department of Economics.
  6. Anselin, Luc, 1990. "Some robust approaches to testing and estimation in spatial econometrics," Regional Science and Urban Economics, Elsevier, vol. 20(2), pages 141-163, September.
  7. Jaffe, A.B. & Trajtenberg, M., 1992. "Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations," Papers, Tel Aviv 14-92, Tel Aviv.
  8. Bronwyn H. Hall & Adam B. Jaffe & Manuel Trajtenberg, 2001. "The NBER Patent Citation Data File: Lessons, Insights and Methodological Tools," NBER Working Papers 8498, National Bureau of Economic Research, Inc.
  9. J. Vernon Henderson & Ari Kuncoro & Matthew Turner, 1992. "Industrial Development in Cities," NBER Working Papers 4178, National Bureau of Economic Research, Inc.
  10. Lucas, Robert Jr., 1988. "On the mechanics of economic development," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 3-42, July.
  11. Audretsch, David B. & Feldman, Maryann P., 2004. "Knowledge spillovers and the geography of innovation," Handbook of Regional and Urban Economics, Elsevier, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 61, pages 2713-2739 Elsevier.
  12. Feldman, Maryann P. & Audretsch, David B., 1999. "Innovation in cities:: Science-based diversity, specialization and localized competition," European Economic Review, Elsevier, vol. 43(2), pages 409-429, February.
  13. Rosenthal, Stuart S. & Strange, William C., 2004. "Evidence on the nature and sources of agglomeration economies," Handbook of Regional and Urban Economics, Elsevier, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 49, pages 2119-2171 Elsevier.
  14. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 94(5), pages 1002-37, October.
  15. Zvi Griliches, 1998. "Productivity, R&D, and the Data Constraint," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 347-374 National Bureau of Economic Research, Inc.
  16. Helsley, Robert W. & Strange, William C., 2004. "Knowledge barter in cities," Journal of Urban Economics, Elsevier, vol. 56(2), pages 327-345, September.
  17. Duranton, Gilles & Puga, Diego, 2003. "Microfoundations of Urban Agglomeration Economies," CEPR Discussion Papers 4062, C.E.P.R. Discussion Papers.
  18. Edward L. Glaeser & Matthew E. Kahn, 2001. "Decentralized Employment and the Transformation of the American City," Harvard Institute of Economic Research Working Papers 1912, Harvard - Institute of Economic Research.
  19. Anselin, Luc & Hudak, Sheri, 1992. "Spatial econometrics in practice : A review of software options," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 509-536, September.
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  21. repec:fth:harver:1473 is not listed on IDEAS
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Cited by:
  1. Sherrill Shaffer & Robert N. Collender, 2008. "Rural Economic Performance And Federal Credit Programs," CAMA Working Papers 2008-26, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  2. Bettencourt, Luis M.A. & Lobo, Jose & Strumsky, Deborah, 2007. "Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size," Research Policy, Elsevier, vol. 36(1), pages 107-120, February.
  3. Dani Shefer & Haim Aviram, 2005. "Incorporating Agglomeration Economies In Cost-Benefit Analysis Of Transport Projects," ERSA conference papers ersa05p133, European Regional Science Association.

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