17 research outputs found
Economic Valuation of Forest Ecosystem Services: Methodology and Monetary Estimates
By using ad hoc value transfer protocols, this paper offers a methodological contribution and provides accurate per hectare estimates of the economic value of some selected ecosystem services for all forest biomes in the world, identified following the Millennium Ecosystem Assessment taxonomy MEA. The research also estimates potential total economic losses from policy inaction in year 2050. Final results show that total losses are significant. The total figure is €78 billion, the greatest losses coming from North America and Mexico, followed by Africa, Russia and some Asiatic countries. Most of this loss is attributable to provisioning services and carbon sequestration, while only a minor part is due to loss of cultural services. In terms of biomes the greatest losses are from boreal and warm mixed forests, followed by tropical forests. These results may be surprising to some who argue that it is the loss of tropical forests, particularly the Amazon, that is the most significant. A detailed analysis, shows, however, that this is not the case. The best estimates point to greater losses in areas where use and non-use values are highest, which includes North America.Forest, Ecosystem Services, Biodiversity, Valuation, Value Transfer
Recommended from our members
Bayesian estimation of willingness-to-pay where respondents mis-report their preferences
We introduce a modified conditional logit model that takes account of uncertainty associated with mis-reporting in revealed preference experiments estimating willingness-to-pay (WTP). Like Hausman et al. [Journal of Econometrics (1988) Vol. 87, pp. 239-269], our model captures the extent and direction of uncertainty by respondents. Using a Bayesian methodology, we apply our model to a choice modelling (CM) data set examining UK consumer preferences for non-pesticide food. We compare the results of our model with the Hausman model. WTP estimates are produced for different groups of consumers and we find that modified estimates of WTP, that take account of mis-reporting, are substantially revised downwards. We find a significant proportion of respondents mis-reporting in favour of the non-pesticide option. Finally, with this data set, Bayes factors suggest that our model is preferred to the Hausman model