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| Lambert, Dayton M.; McNamara, Kevin T.; Garrett, Megan I.. |
| 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. |
| Tipo: Journal Article |
Palavras-chave: Geographically weighted regression; Location determinants; Location theory; Manufacturing site selection; Poisson spatial generalized linear model; Agribusiness; Industrial Organization; Productivity Analysis; R1; R3. |
| Ano: 2006 |
URL: http://purl.umn.edu/43752 |
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| Brown, Jason P.; Lambert, Dayton M.; Florax, Raymond J.G.M.. |
| Attracting manufacturing investment is a frequently used rural development policy. Previous research in the location literature has informed policymakers which factors are most important for attracting new firm investment. Far less is known about the interaction of birth and death of establishments. A conceptual model of county-level investment in the U.S. manufacturing sector is developed from location theory and subsequent literature. Specifically, we test the relative importance of location factors influencing firm investment, and if these factors influence firm birth and death differently. Local factors include agglomeration due to localization, urbanization, and internal economies, market structure, labor quality, availability, and cost, market... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Location determinants; Manufacturing; Count models; Community/Rural/Urban Development; Research Methods/ Statistical Methods; L60; R11; R12. |
| Ano: 2009 |
URL: http://purl.umn.edu/49467 |
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