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Regional Structure and Economic Development: Growth Empirics for U.S. Metropolitan Areas
Abstract
This chapter investigates several aspects of how local economic development and growth are shaped by regional differences in industrial structure on the one hand and interregional linkages on the other hand. The author begins by proposing an alternative regional classification of regions for U.S. Metropolitan Statistical Areas (MSAs) on the basis of clusters that were formed by principal component analysis from economic variables that are relevant for regional growth. These variables include labor productivity growth, measures of local industry mix, human capital, entrepreneurship, and innovation. He then uses these growth-based regional clusters to control the presence of cluster-specific fixed-effects when explaining the spatial characteristics of urban specialization and concentration in the United States. The empirical validity of these new economic regions are evaluated against alternative established classifications such as the BEA Regions, Crone’s (2005) Economic Regions, the Census Regions, and the Federal Reserve Districts. Looking specifically at the empirics of regional growth both in a traditional ß-convergence setting as well as a dynamic panel setting, the author examines the explanatory power of regional differences in economic structure such as industry concentration, employment specialization, and sectoral diversity.
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