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The agglomeration of R&D labs

  • Carlino, Gerald A.
  • Carr, Jake
  • Hunt, Robert M.
  • Smith, Tony E.

This paper has been superseded by WP 15-03. The authors document the spatial concentration of more than 1,000 research and development (R&D) labs located in the Northeast corridor of the U.S. using point pattern methods. These methods allow systematic examination of clustering at different spatial scales. In particular, Monte Carlo tests based on Ripley's (1976) K-functions are used to identify clusters of labs — at varying spatial scales — that represent statistically significant departures from random locations reflecting the underlying distribution of economic activity (employment). Using global K-functions, they first identify significant clustering of R&D labs at two different spatial scales. This clustering is by far most significant at very small spatial scales (a quarter of a mile), with significance attenuating rapidly during the first half mile. The authors also observe statistically significant clustering at distances of about 40 miles. This corresponds roughly to the size of the four major R&D clusters identified in the second stage of their analysis — one each in Boston, New York-Northern New Jersey, Philadelphia-Wilmington, and Virginia (including the District of Columbia). In this second stage of the analysis, explicit clusters are identified by a new procedure based on local K-functions, which they designate as the multiscale core-cluster approach. This new approach yields a natural nesting of clusters at different scales. The authors' global finding of clustering at two spatial scales suggests the possibility of two distinct forms of spillovers. First, the rapid attenuation of significant clustering at small spatial scales is consistent with the view that knowledge spillovers are highly localized. Second, the scale at which larger clusters are found is roughly comparable to that of local labor markets, suggesting that such markets may be the source of additional spillovers (e.g., input sharing or labor market matching externalities).

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File URL: http://www.philadelphiafed.org/research-and-data/publications/working-papers/2010/wp10-33.pdf
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Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 10-33.

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Length: 1 pages
Date of creation: 2010
Date of revision:
Handle: RePEc:fip:fedpwp:10-33
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  1. William R. Kerr & Scott Duke Kominers, 2010. "Agglomerative Forces and Cluster Shapes," NBER Working Papers 16639, National Bureau of Economic Research, Inc.
  2. Carlino, Gerald A. & Chatterjee, Satyajit & Hunt, Robert M., 2007. "Urban density and the rate of invention," Journal of Urban Economics, Elsevier, vol. 61(3), pages 389-419, May.
  3. Yasusada Murata & Ryo Nakajima & Ryosuke Okamoto & Ryuichi Tamura, 2011. "Localized knowledge spillovers and patent citations: A distance-based approach," Tsukuba Economics Working Papers 2010-010, Economics, Graduate School of Humanities and Social Sciences, University of Tsukuba.
  4. Holmes, Thomas J. & Stevens, John J., 2004. "Spatial distribution of economic activities in North America," Handbook of Regional and Urban Economics, in: J. V. Henderson & J. F. Thisse (ed.), Handbook of Regional and Urban Economics, edition 1, volume 4, chapter 63, pages 2797-2843 Elsevier.
  5. Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2007. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," Harvard Business School Working Papers 07-064, Harvard Business School.
  6. Hall, Bronwyn H & Jaffe, Adam B & Trajtenberg, Manuel, 2001. "The NBER Patent Citations Data File: Lessons, Insights and Methodological Tools," CEPR Discussion Papers 3094, C.E.P.R. Discussion Papers.
  7. Kristy Buzard & Gerald Carlino, 2009. "The geography of research and development activity in the U.S," Working Papers 09-16, Federal Reserve Bank of Philadelphia.
  8. Colin Webb & Hélène Dernis & Dietmar Harhoff & Karin Hoisl, 2005. "Analysing European and International Patent Citations: A Set of EPO Patent Database Building Blocks," OECD Science, Technology and Industry Working Papers 2005/9, OECD Publishing.
  9. Gilles Duranton & Henry G. Overman, 2005. "Testing for localization using micro-geographic data," LSE Research Online Documents on Economics 581, London School of Economics and Political Science, LSE Library.
  10. Sergey Lychagin & Joris Pinkse & Margaret E. Slade & John Van Reenen, 2010. "Spillovers in Space: Does Geography Matter?," CEP Discussion Papers dp0991, Centre for Economic Performance, LSE.
  11. Tomoya Mori & Tony E. Smith, 2009. "A Probabilistic Modeling Approach to the Detection of Industrial Agglomerations," KIER Working Papers 682, Kyoto University, Institute of Economic Research.
  12. Shihe Fu, 2005. "Smart Cafe Cities: Testing Human Capital Externalities in the Boston Metropolitan Area," Working Papers 05-24, Center for Economic Studies, U.S. Census Bureau.
  13. repec:bla:restud:v:75:y:2008:i:4:p:1011-1038 is not listed on IDEAS
  14. Paulo Guimar�es & Octávio Figueiredo & Douglas Woodward, 2007. "Measuring The Localization Of Economic Activity: A Parametric Approach," Journal of Regional Science, Wiley Blackwell, vol. 47(4), pages 753-774.
  15. Gerald Carlino & Robert Hunt, 2009. "What explains the quantity and quality of local inventive activity?," Working Papers 09-12, Federal Reserve Bank of Philadelphia.
  16. Agrawal, Ajay & Kapur, Devesh & McHale, John, 2008. "How do spatial and social proximity influence knowledge flows? Evidence from patent data," Journal of Urban Economics, Elsevier, vol. 64(2), pages 258-269, September.
  17. Giuseppe Arbia & Giuseppe Espa & Diego Giuliani & Andrea Mazzitelli, 2009. "Clusters of firms in space and time," Department of Economics Working Papers 0902, Department of Economics, University of Trento, Italia.
  18. J. Vernon Henderson & Mohammad Arzaghi, 2005. "Networking Off Madison Avenue," Working Papers 05-15, Center for Economic Studies, U.S. Census Bureau.
  19. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
  20. Giuseppe Arbia & Giuseppe Espa & Danny Quah, 2007. "A class of spatial econometric methods in the empirical analysis of clusters of firms in the space," Department of Economics Working Papers 0705, Department of Economics, University of Trento, Italia.
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