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Industry Clusters and Regional Economic Performance: A Study Across U.S. Metropolitan Statistical Areas

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  • Timothy F. Slaper
  • Karter M. Harmon
  • Barry M. Rubin

Abstract

Cluster theory provides a framework for analyzing regional industry dynamics. Definitions and categorizations of clusters vary, however, hindering the development of econometric models for cluster analysis. The authors propose empirical measures relevant to researchers and practitioners for cluster strength/specialization, cluster diversity/diversification, and identifying regional growth clusters. The latter measure uses location quotients, shift-share analysis, and other criteria to identify robust clusters that are important for thriving regions. These measures are calculated for local and traded clusters using employment data for 366 U.S. metropolitan statistical areas. Additionally, the authors estimated the relationship of their cluster performance measures to four traditional measures of economic performance: growth in gross domestic product, productivity per employee, compensation per employee, and personal income. The authors find traded cluster strength is positively related to compensation per employee growth and positively related to productivity growth, the latter being consistent with expected Marshall–Arrow–Romer externalities. Traded growth clusters are positively related to gross domestic product growth.

Suggested Citation

  • Timothy F. Slaper & Karter M. Harmon & Barry M. Rubin, 2018. "Industry Clusters and Regional Economic Performance: A Study Across U.S. Metropolitan Statistical Areas," Economic Development Quarterly, , vol. 32(1), pages 44-59, February.
    • Handle: RePEc:sae:ecdequ:v:32:y:2018:i:1:p:44-59
    DOI: 10.1177/0891242417752248
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    References listed on IDEAS

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    1. Romer, Paul M, 1986. "Increasing Returns and Long-run Growth," Journal of Political Economy, University of Chicago Press, vol. 94(5), pages 1002-1037, October.
    2. Frank Neffke & Martin Henning & Ron Boschma, 2011. "How Do Regions Diversify over Time? Industry Relatedness and the Development of New Growth Paths in Regions," Economic Geography, Taylor & Francis Journals, vol. 87(3), pages 237-265, July.
    3. Mercedes Delgado & Michael E. Porter & Scott Stern, 2010. "Clusters and entrepreneurship," Journal of Economic Geography, Oxford University Press, vol. 10(4), pages 495-518, July.
    4. Koen Frenken & Frank Van Oort & Thijs Verburg, 2007. "Related Variety, Unrelated Variety and Regional Economic Growth," Regional Studies, Taylor & Francis Journals, vol. 41(5), pages 685-697.
    5. Edward L. Glaeser & William R. Kerr, 2009. "Local Industrial Conditions and Entrepreneurship: How Much of the Spatial Distribution Can We Explain?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(3), pages 623-663, September.
    6. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    7. Michael Porter, 2003. "The Economic Performance of Regions," Regional Studies, Taylor & Francis Journals, vol. 37(6-7), pages 549-578.
    8. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    9. Christian H.M. Ketels & Olga Memedovic, 2008. "From clusters to cluster-based economic development," International Journal of Technological Learning, Innovation and Development, Inderscience Enterprises Ltd, vol. 1(3), pages 375-392.
    10. Henderson, Vernon, 1997. "Externalities and Industrial Development," Journal of Urban Economics, Elsevier, vol. 42(3), pages 449-470, November.
    11. Delgado, Mercedes & Porter, Michael E. & Stern, Scott, 2014. "Clusters, convergence, and economic performance," Research Policy, Elsevier, vol. 43(10), pages 1785-1799.
    12. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    13. Mercedes Delgado & Michael E. Porter & Scott Stern, 2016. "Defining clusters of related industries," Journal of Economic Geography, Oxford University Press, vol. 16(1), pages 1-38.
    14. Merlin M. Hackbart & Donald A. Anderson, 1975. "On Measuring Economic Diversification," Land Economics, University of Wisconsin Press, vol. 51(4), pages 374-378.
    15. Robert J. Stimson & Roger R. Stough & Brian H. Roberts, 2006. "Regional Economic Development," Springer Books, Springer, edition 0, number 978-3-540-34829-0, September.
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    2. Niki Derlukiewicz & Anna Mempel-Śnieżyk & Dominika Mankowska & Arkadiusz Dyjakon & Stanisław Minta & Tomasz Pilawka, 2020. "How do Clusters Foster Sustainable Development? An Analysis of EU Policies," Sustainability, MDPI, vol. 12(4), pages 1-15, February.

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