Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model
Seong-Hoon Cho (),
SeungGyu Kim,
Christopher Clark and
William M. Park
Agricultural and Resource Economics Review, 2007, vol. 36, issue 1, 24-38
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.
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
Related works:
Journal Article: Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model (2007) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cup:agrerw:v:36:y:2007:i:01:p:24-38_00
Access Statistics for this article
More articles in Agricultural and Resource Economics Review from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().