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

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. 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