search query: @freeterm forests / total: 4
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| Author: | Leon-Gonzalez, R. Scarpa, R. |
| Title: | Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer |
| Journal: | Journal of Environmental Economics and Management
2008 : JUL, VOL. 56:1, p. 50-68 |
| Index terms: | Irish Republic United Kingdom models methodology |
| Freeterms: | benefit transfers non-market valuation willingness-to-pay forests |
| Language: | eng |
| Abstract: | A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. A more expensive alternative to estimate WTP is to only analyze data from one site while ignoring information from other sites. This study makes use of the fact that these two choices can be viewed as a model selection problem. The set of models is extended to allow for the hypothesis that the benefit function is applicable only to a subset of sites. It is shown how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models. The Bayesian algorithm method is illustrated using a sample of more than 40 forests from U.K. and Ireland. It is found that BMA benefit function transfer produces reliable estimates, being able to increase about 8 times the information content of a small sample when the forest is 'poolable'. |
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