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An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis

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Author Info
Lambert, Dayton M.
McNamara, Kevin T.
Garrett, Megan I.
Abstract

The 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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Article provided by Southern Agricultural Economics Association in its journal Journal of Agricultural and Applied Economics.

Volume (Year): 38 (2006)
Issue (Month): 01 (April)
Pages:
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Handle: RePEc:ags:joaaec:43752

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Related research
Keywords: geographically weighted regression; location determinants; location theory; manufacturing site selection; Poisson spatial generalized linear model; Agribusiness; Industrial Organization; Productivity Analysis; R1; R3;

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References listed on IDEAS
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  1. Coughlin, Cletus C & Terza, Joseph V & Arromdee, Vachira, 1991. "State Characteristics and the Location of Foreign Direct Investment within the United States," The Review of Economics and Statistics, MIT Press, vol. 73(4), pages 675-83, November. [Downloadable!] (restricted)
  2. Eberts, Randall W. & McMillen, Daniel P., 1999. "Agglomeration economies and urban public infrastructure," Handbook of Regional and Urban Economics, in: P. C. Cheshire & E. S. Mills (ed.), Handbook of Regional and Urban Economics, edition 1, volume 3, chapter 38, pages 1455-1495 Elsevier. [Downloadable!] (restricted)
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  1. Cho, Seong-Hoon & Lambert, Dayton M. & Kim, Seung Gyu & Jung, Su Hyun, 2009. "Extreme coefficients in Geographically Weighted Regression and their effects on mapping," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49117, Agricultural and Applied Economics Association. [Downloadable!]
  2. Wojan, Timothy R. & McGranahan, David A., 2007. "Ambient Returns: Creative Capital's Contribution to Local Manufacturing Competitiveness," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 36(1), April. [Downloadable!]
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