Industry Clusters and Regional Economic Performance: A Study Across U.S. Metropolitan Statistical Areas. Issue 1 (February 2018)

• Record Type: Journal Article
• Authors: Slaper, Timothy F.; Harmon, Karter M.; Rubin, Barry M.
• Is Part Of: Economic development quarterly. Volume 32:Issue 1(2018)
• Page Start: 44
• Page End: 59
• Publication Date: 2018-02
• Subjects: cluster growth -- regional economic performance -- regional analysis -- econometrics -- agglomeration economies; Economic development -- Periodicals; Economics -- Periodicals; United States -- Economic conditions -- Periodicals; 330.973
• DOI: 10.1177/0891242417752248
• Languages: English
• ISSNs: 0891-2424

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.