An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis
AbstractThe influence product markets, agglomeration, labor, infrastructure, and government fiscal attributes had on manufacturing investment flows in Indiana between 2000 and 2004 were estimated using Poisson regression, geographically weighted regression, and a spatial general linear model. Counties with access to urbanization economies, product markets, available labor, a high-quality workforce, and transport infrastructure were more likely to attract manufacturing investment. These effects were magnified to some extent when inter-county spatial effects were modeled. The distributional assumptions of the spatial models are different, but both methods are useful for understanding the spatial context of the factors influencing manufacturing investment flows.
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Bibliographic InfoArticle provided by Southern Agricultural Economics Association in its journal Journal of Agricultural and Applied Economics.
Volume (Year): 38 (2006)
Issue (Month): 01 (April)
geographically weighted regression; location determinants; location theory; manufacturing site selection; Poisson spatial generalized linear model; Agribusiness; Industrial Organization; Productivity Analysis; R1; R3;
Find related papers by JEL classification:
- R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
- R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location
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