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Over the past 25 years social scientists attempting to explain the dramatic changes in the relative distribution of urban and rural population growth have gravitated toward two competing explanations. The regional restructuring hypothesis holds that changes in the spatial distribution of employment opportunities have been dominant whereas the deconcentration hypothesis attributes these changes to changes in residential preferences of workers and consumers. We develop an empirical test of these two explanations based on whether commuting and migration are positively or negatively related after controlling for other economic factors. Our econometric results support the deconcentration hypothesis.

In this paper we investigate industry characteristics associated with the clustering of establishments in three-digit SIC manufacturing industries in nonmetropolitan areas. The dispersion parameter k of the negative binomial distribution is selected as the measure of industry spatial concentration. Associations between industry characteristics and spatial concentration are investigated using OLS regression analysis. Our findings indicate that the spatial clustering of establishments is positively related to industry average establishment size, reliance on natural resource inputs, labor intensity, cost shares of professional and technical employees, and cost shares of low-skilled workers. Agglomeration is negatively related to multiplant structure, employment in precision production, and reliance on local product and input markets.

Canonical correlation analysis (CCA) has the ability to deal with two sets of multivariate variables simultaneously and to produce both structural and spatial meanings. In view of the valuable insights to be gained, in this paper I examine the potential applications of CCA in regional science by describing its algorithm in a regional or spatial context. Next, I apply CCA to explore the mutually interdependent relationship between transport and development in China's Zhujiang Delta. The results highlight the utility of CCA in revealing the structural and spatial patterns of two dominant and four subdominant transport-development relationships in this growing region of China.