Regional income club convergence in US BEA economic areas: a spatial switching regression approach

Abstract

This study empirically applies the spatial switching regression method to an analysis of regional income club convergence across the 177 economic areas in the contiguous US states over the period from 1969 to 2008. As functionally defined, these economic areas represent the relevant regional markets for labor, products and information. The result of spatial switching regression reveals that the initial gaps between economic areas relative to average global initial per capita income appear to have declined, but the two spatial clubs exhibit a significant difference in their income convergence processes over the period. The estimated coefficient of the convergence parameter for the peripheral spatial regime is negative and highly significant, indicating that a convergence process exists in this spatial regime. However, there is no statistically significant evidence of convergence in the core spatial regime, implying the possibility of different patterns in the growth dynamics of the core spatial regime.