Estimating the Supply of Forest Carbon Offsets: A Comparison of Best- Worst and Discrete Choice Valuation Methods

Jose R. Soto and Damian Adams

No 124830, 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington from Agricultural and Applied Economics Association

Abstract: The use of carbon markets to regulate greenhouse gasses has been promoted as a cost-effective tool to deal with global warming. These markets often encourage forest landowners to capture carbon in exchange for compensation, by using different platforms that vary in terms of contract length, penalties for withdrawal, etc. These differences in available carbon programs send signals to both consumers, and potential producers of carbon credits, which often cause confusion, price variations, and potential barriers to participation. This study uses one of the most comprehensive lists of Florida non-industrial private forest landowners to implement two different conjoint choice tasks (best worst choice and discrete choice experimentation), which offer multiple options to estimate attitudes of landowners towards different carbon programs, as well as various avenues to estimate willingness to accept. Results indicate that landowners would need between $20 to $30 acre-per-year to be positively affected by revenue, while the inclusion of penalty for early withdrawal increases cost of participation by approximately $4.45 to $10.41 acre-per-year. In addition, this study compares the performance of best worst choice with the traditional discrete choice experimentation method, and finds similar estimates of willingness to accept from both models, but disagreement with overall attribute impact estimates.

Keywords: Environmental Economics and Policy; Resource/Energy Economics and Policy (search for similar items in EconPapers)
Pages: 22
Date: 2012
New Economics Papers: this item is included in nep-dcm and nep-env
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:aaea12:124830

DOI: 10.22004/ag.econ.124830

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