Spatial associations within eight Southeastern Functional Economic Areas were investigated using three spatial data analysis techniques (Moran's L. G2(d) statistic and local Moran) and 1980 to 1990 population change at the country and census tract levels. Core hinterland relationships in EEAs were categorized as spread through growth, spread through decentralization, backwards or independent, based on intra regional patterns of spatial association. Findings indicate that all four of the spread backwash typologies were evident among the eight economic regions. Yet, spatial association with the core (spread or backwash) generally was limited to hinterland areas at the core's range. Spatial dependence between core and hinterland areas declined with distance from the economic region's core area. For many rural locations, changes in economic activity are independent of economic development experiences in nearby locations.
A geographical information system (GIS) is used with econometric methods to develop a small region spatial model to analyze the linkage between highway investment and new manufacturing employment in South Carolina. OLS estimates of the spatial model indicate that increases in four-lane highways, as well as interstate access, and two-lane highway density stimulate new manufacturing firm employment. Regions with higher than average employment density (a proxy for agglomeration economies) consistently influence employment gains as well, however. An implication for state and local policymakers is that the location, timing, and type of highway investment matter concerning whether highway investment serves as an economic development aid. Comparison of nonspatial and spatial model results indicates that development of small region models incorporating spatial statistical concerns should be pursued further.
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