Landowner attitudes and willingness to accept compensation from forest carbon offsets: Application of best-worst choice modeling in Florida USA

Little is known about institutional preferences and barriers for non-industrial private forest landowner participation in carbon (C) offset programs - factors that influence participation in such programs. To address this, we used Florida (U.S.) as a case study, and identified barriers to forest landowner participation in a hypothetical carbon-offset program and landowner willingness-to-accept compensation for enrollment. Preferences were elicited via survey methods and a recent innovation to best-worst scaling (BWS), called best-worst choice (BWC), which retains the analytical features of scaling while enabling measurements in a traditional discrete-choice framework. Results indicate that NIPF landowners are more influenced by revenue than early withdrawal penalty or contract duration, but will exchange revenue for other contract features. We estimate that programs offering $20 or $30 per-acre-per-year have significantly stronger impacts on enrollment than $5 or $10. The least preferred feature was a 100-year commitment. Overall our BWC approach is novel in that it circumvents BWS' limitation by providing an ability to estimate actual willingness-to-pay/accept. The U.S. has a new policy to cut 32% of 2005 power plant carbon emissions by 2030 and allow forest C offsets. Thus, results can also be used to inform state-level policies that compensate landowners for capturing C emissions. © 2015 Elsevier B.V.

• Fecha de publicación: 2016
• Institución: Universidad del Rosario
• Repositorio: Repositorio EdocUR - U. Rosario
• Idioma: eng
• OAI Identifier: oai:repository.urosario.edu.co:10336/24073
• Acceso en línea: https://doi.org/10.1016/j.forpol.2015.12.004; https://repository.urosario.edu.co/handle/10336/24073
• Palabra clave: C (programming language); Economics; Best-worst scaling; Carbon offsets; Choice model; Discrete choice; Nonindustrial private forests; Willingness to accept; Forestry; Best-worst scaling; Carbon offsets; Choice modeling; Discrete choice; Non-industrial private forest; Willingness to accept
• License: Abierto (Texto Completo)