GTAP Resources: Resource Display
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"Modeling Recreational Demand for Land" by Antoine, Blandine, Angelo Gurgel and John Reilly Abstract We represent recreational demand for land in a CGE framework and apply it to investigate the potential of second generation biofuels production under possibilities of land use conversion from natural areas to agricultural land in the U.S, considering the recreational value of forests. We introduce recreational benefits of natural forests through “household” production sectors for hunting and fishing, for wildlife viewing in reserved areas, and wildlife viewing in other forest areas, based on extensive data available in the U.S. about those activities. We test the model assessing the land use changes and welfare impacts from a U.S. climate policy scenario. The new approach resulted in similar land use change as earlier work where land conversion was limited by an elasticity based on observed land supply response. The advantage of the new approach built here using recreation data is that it provides an obviously improved measure of welfare cost of policies that lead to land use change, because the preservation value of the land offsets the increased cost of the policy due to the restriction on use. The results are sensitive to the representation of people’s willingness to substitute other inputs for natural land in their recreation experience, parameter not being well investigated empirically. The main contribution of the paper is not for its insights on biofuels potential but for the improved representation of welfare changes from models where the land supply response limits conversion. |
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- Climate change policy - Renewable energy - Dynamic modeling - North America |
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If you have trouble accessing any of the attachments below due to disability, please contact the authors listed above.
Public Access  2009 Conference Paper (219.1 KB) Replicated: 0 time(s)Restricted Access No documents have been attached. Special Instructions No instructions have been specified. |
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Last Modified: 9/15/2023 1:05:45 PM
