Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States
Abstract This paper investigates the spatial heterogeneity of landowners’ willingness to supply three bioenergy crops: switchgrass, Miscanthus, and willow, in the northeastern United States. Spatial heterogeneity might arise for several reasons. For example, landowners closer to bioenergy processing...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-09-01
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| Series: | GCB Bioenergy |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/gcbb.12617 |
| _version_ | 1811269033231646720 |
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| author | Wei Jiang Katherine Y. Zipp Matthew H. Langholtz Michael G. Jacobson |
| author_facet | Wei Jiang Katherine Y. Zipp Matthew H. Langholtz Michael G. Jacobson |
| author_sort | Wei Jiang |
| collection | DOAJ |
| description | Abstract This paper investigates the spatial heterogeneity of landowners’ willingness to supply three bioenergy crops: switchgrass, Miscanthus, and willow, in the northeastern United States. Spatial heterogeneity might arise for several reasons. For example, landowners closer to bioenergy processing plants might be more likely to be willing to supply bioenergy crops, and landowners who are more willing to supply bioenergy crops may be spatially clustered because they share similar land attributes, demographics, experiences, and/or values. Using high‐resolution GIS data related to the location of pellet plants utilizing bioenergy crops and survey data related to landowners’ characteristics including spatial location, we estimate a spatial probit model to explain the variation in individual‐specific reservation prices (RPs)—the feedstock price at which landowners become willing to supply a bioenergy crop. We find that respondents’ RP is lower the closer they live to their nearest pellet plant and spatial dependency is only present for switchgrass supply. We also identify three economic hotspots (areas with high potential supply and low RPs) for each bioenergy crop. We believe that bioenergy supply chains could be developed around these hotspots. |
| first_indexed | 2024-04-12T21:33:49Z |
| format | Article |
| id | doaj.art-8e272b5fb63345da832d70b6f0ac15c9 |
| institution | Directory Open Access Journal |
| issn | 1757-1693 1757-1707 |
| language | English |
| last_indexed | 2024-04-12T21:33:49Z |
| publishDate | 2019-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | GCB Bioenergy |
| spelling | doaj.art-8e272b5fb63345da832d70b6f0ac15c92022-12-22T03:15:58ZengWileyGCB Bioenergy1757-16931757-17072019-09-011191086109710.1111/gcbb.12617Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United StatesWei Jiang0Katherine Y. Zipp1Matthew H. Langholtz2Michael G. Jacobson3Athenium Analytics Washington District of ColumbiaDepartment of Agricultural Economics, Sociology and Education Pennsylvania State University University Park PennsylvaniaOak Ridge National Lab Oak Ridge TennesseeDepartment of Ecosystem Science and Management Pennsylvania State University University Park PennsylvaniaAbstract This paper investigates the spatial heterogeneity of landowners’ willingness to supply three bioenergy crops: switchgrass, Miscanthus, and willow, in the northeastern United States. Spatial heterogeneity might arise for several reasons. For example, landowners closer to bioenergy processing plants might be more likely to be willing to supply bioenergy crops, and landowners who are more willing to supply bioenergy crops may be spatially clustered because they share similar land attributes, demographics, experiences, and/or values. Using high‐resolution GIS data related to the location of pellet plants utilizing bioenergy crops and survey data related to landowners’ characteristics including spatial location, we estimate a spatial probit model to explain the variation in individual‐specific reservation prices (RPs)—the feedstock price at which landowners become willing to supply a bioenergy crop. We find that respondents’ RP is lower the closer they live to their nearest pellet plant and spatial dependency is only present for switchgrass supply. We also identify three economic hotspots (areas with high potential supply and low RPs) for each bioenergy crop. We believe that bioenergy supply chains could be developed around these hotspots.https://doi.org/10.1111/gcbb.12617bioenergy cropseconomic hotspotPOLYSYSrenewable energyreservation pricespatial dependence |
| spellingShingle | Wei Jiang Katherine Y. Zipp Matthew H. Langholtz Michael G. Jacobson Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States GCB Bioenergy bioenergy crops economic hotspot POLYSYS renewable energy reservation price spatial dependence |
| title | Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States |
| title_full | Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States |
| title_fullStr | Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States |
| title_full_unstemmed | Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States |
| title_short | Modeling spatial dependence and economic hotspots in landowners’ willingness to supply bioenergy crops in the northeastern United States |
| title_sort | modeling spatial dependence and economic hotspots in landowners willingness to supply bioenergy crops in the northeastern united states |
| topic | bioenergy crops economic hotspot POLYSYS renewable energy reservation price spatial dependence |
| url | https://doi.org/10.1111/gcbb.12617 |
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