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

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  • 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.

Suggested Citation

  • Cho, Seong-Hoon & Kim, Seung Gyu & Clark, Christopher D. & Park, William M., 2007. "Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model," Agricultural and Resource Economics Review, Cambridge University Press, vol. 36(1), pages 24-38, April.
    • Handle: RePEc:cup:agrerw:v:36:y:2007:i:01:p:24-38_00
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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).
    2. Suhyun Jung & Seong-Hoon Cho & Roland K. Roberts, 2015. "The impact of government funding of poverty reduction programmes," Papers in Regional Science, Wiley Blackwell, vol. 94(3), pages 653-675, August.
    3. repec:rre:publsh:v:37:y:2007:i:2:p:251-78 is not listed on IDEAS

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