48 Pages Posted: 18 Jan 2016 Last revised: 16 Mar 2017
Date Written: January 13, 2016
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. We 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, we estimate the relationship of our cluster performance measures to four traditional measures of economic performance: growth in GDP, productivity per employee, compensation per employee and personal income. We 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 GDP growth.
Keywords: Cluster theory, urban economic development, regional analysis, multivariate regression
Suggested Citation: Suggested Citation
Slaper, Timothy F. and Harmon, Karter Mycroft and Rubin, Barry, Industry Clusters and Regional Economic Performance: A Study Across U.S. Metropolitan Statistical Areas (January 13, 2016). Kelley School of Business Research Paper No. 16-15; Indiana University, Bloomington School of Public & Environmental Affairs Research Paper. Available at SSRN: https://ssrn.com/abstract=2715263 or http://dx.doi.org/10.2139/ssrn.2715263