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Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model

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Author Info

  • Cho, Seong-Hoon
  • Kim, Seung Gyu
  • Clark, Christopher D.
  • Park, William M.

Abstract

This study uses locally weighted regression to identify county-level characteristics that serve as drivers of creative employment throughout the southern United States. We found that higher per capita income, greater infrastructure investments, and the rural nature of a county tended to promote creative employment density, while higher scores on a natural amenity index had the opposite effect. We were also able to identify and map clusters of rural counties where the marginal effects of these variables on creative employment density were greatest. These findings should help rural communities to promote creative employment growth as a means of furthering rural economic development.

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File URL: http://purl.umn.edu/10163
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Bibliographic Info

Article provided by Northeastern Agricultural and Resource Economics Association in its journal Agricultural and Resource Economics Review.

Volume (Year): 36 (2007)
Issue (Month): 1 (April)
Pages:

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Handle: RePEc:ags:arerjl:10163

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Web page: http://www.narea.org/
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Related research

Keywords: creative class; locally weighted regression; natural amenities; rural economic development; Community/Rural/Urban Development;

References

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  1. Tzu-Ling Huang & Peter F. Orazem & Darin Wohlgemuth, 2002. "Rural Population Growth, 1950–1990: The Roles of Human Capital, Industry Structure, and Government Policy," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(3), pages 615-627.
  2. Marlon G. Boarnet & Saksith Chalermpong & Elizabeth Geho, 2005. "Specification issues in models of population and employment growth," Papers in Regional Science, Wiley Blackwell, vol. 84(1), pages 21-46, 03.
  3. John I. Carruthers & Alexander C. Vias, 2005. "Urban, Suburban, and Exurban Sprawl in the Rocky Mountain West: Evidence from Regional Adjustment Models," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 21-48.
  4. Byrne, John & Shen, Bo & Wallace, William, 1998. "The economics of sustainable energy for rural development: A study of renewable energy in rural China," Energy Policy, Elsevier, vol. 26(1), pages 45-54, January.
  5. Raymond J.G.M. Florax & Peter Nijkamp, 2003. "Misspecification in Linear Spatial Regression Models," Tinbergen Institute Discussion Papers 03-081/3, Tinbergen Institute.
  6. Kilkenny, Maureen, 1993. "Rural vs. Urban Effects of Terminating Farm Subsidies," Staff General Research Papers 11121, Iowa State University, Department of Economics.
  7. McGranahan, David A., 1999. "Natural Amenities Drive Rural Population Change," Agricultural Economics Reports 33955, United States Department of Agriculture, Economic Research Service.
  8. Whitener, Leslie A. & McGranahan, David A., 2003. "Rural America Opportunities and Challenges," Amber Waves, United States Department of Agriculture, Economic Research Service, February.
  9. Steven C. Deller & Tsung-Hsiu (Sue) Tsai & David W. Marcouiller & Donald B.K. English, 2001. "The Role of Amenities and Quality of Life In Rural Economic Growth," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 352-365.
  10. Mitch Renkow, 2003. "Employment Growth, Worker Mobility, and Rural Economic Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(2), pages 503-513.
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Cited by:
  1. Cho, Seong-Hoon & Lambert, Dayton M. & Roberts, Roland K. & Kim, Seung Gyu, 2008. "Moderating Urban Sprawl through Land Value Taxation," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6150, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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