
This paper evaluates the role of regional cluster composition in the economic performance of industries, clusters and regions. On the one hand, diminishing returns to specialization in a location can result in a convergence effect: the growth rate of an industry within a region may be declining in the level of activity of that industry. At the same time, positive spillovers across complementary economic activities provide an impetus for agglomeration: the growth rate of an industry within a region may be increasing in the size and “strength” (i.e., relative presence) of related economic sectors. Building on Porter (1998, 2003), we develop a systematic empirical framework to identify the role of regional clusters – groups of closely related and complementary industries operating within a particular region – in regional economic performance. We exploit newly available data from the US Cluster Mapping Project to disentangle the impact of convergence at the region-industry level from agglomeration within clusters. We find that, after controlling for the impact of convergence at the narrowest unit of analysis, there is significant evidence for cluster-driven agglomeration. Industries participating in a strong cluster register higher employment growth as well as higher growth of wages, number of establishments, and patenting. Industry and cluster level growth also increases with the strength of related clusters in the region and with the strength of similar clusters in adjacent regions. Importantly, we find evidence that new regional industries emerge where there is a strong cluster environment. Our analysis also suggests that the presence of strong clusters in a region enhances growth opportunities in other industries and clusters. Overall, these findings highlight the important role of cluster-based agglomeration in regional economic performance.
jel: jel:L26, jel: jel:R30, jel: jel:R11
jel: jel:L26, jel: jel:R30, jel: jel:R11
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
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