Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model
| dc.creator | Cho, Seong-Hoon | |
| dc.creator | Kim, Seung Gyu | |
| dc.creator | Clark, Christopher D. | |
| dc.creator | Park, William M. | |
| dc.date | 2017-04-01T19:33:43Z | |
| dc.date.accessioned | 2026-07-09T02:58:01Z | |
| dc.description | 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. | |
| dc.identifier | doi:10.22004/ag.econ.10163 | |
| dc.identifier | https://ageconsearch.umn.edu/record/10163/files/36010024.pdf | |
| dc.identifier | http://ageconsearch.umn.edu/record/10163 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/523838 | |
| dc.language | eng | |
| dc.publisher | ||
| dc.source | http://ageconsearch.umn.edu/record/10163 | |
| dc.title | Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model | |
| dc.type | Text |