Valuation of Biodiversity Benefits (OECD)

Implications for non-market valuation studies of services of biological resourcesPolicy impacts on biological resources usually affect multiple services of these resources.Some other services can change as a result of non-policy-related causes, for example: the extinction oftigers could independently occur while implementing a programme to preserve the lynx. As shown inprevious sections, people’s values for one service depend on the levels of other services. This hasimportant consequences for the implementation of valuation techniques for multiple-servicebiodiversity policies.(1) First, the best way to estimate multidimensional policy benefits is valuing exactly thesame multiple-service change in one single step. This ‘automatically’ takes into account substitutioneffects.(2) Second, when the interest is to value a change in one single service (e.g. habitat forspecies A), we should need to specify not only the change in the service we want to value, but also thelevels of other services (e.g. habitat for species B and C) and whether these are to changesimultaneously with the service to be valued. That is: other services are also part of the relevantcontext for the valuation task, even when the interest is valuing a single service.(2a) The implication of this second consequence for CV is immediate: levels of those otherservices should be included in the scenarios presented to CV survey respondents [see Mitchell andCarson (1989) and Arrow et al. (1993)]. Other stated-preference techniques, such as choiceexperiments, are rather flexible in this respect, as they allow researchers to ask respondents to value avariety of service changes at the same time.(2b) For revealed preference techniques, the implication is to include other services’ levels inthe behavioural models used to infer values people hold for a specific resource.(2c) When benefit estimates are to be transferred from past studies, the implication is tomake sure that levels of other services in the original study (from which we want to transfer benefitestimates) are similar to those levels in the policy context (for which we want to transfer thoseestimates). This coincidence is highly unlikely, which may lead to important biases in transferringbenefit estimates for policy evaluation [Boyle and Bergstrom (1992)].The best solution (1) is rarely possible in practice, as it would imply carrying out an originalstudy for each policy evaluation problem. The other implications are straightforward in principle butraise an enormous number of difficult practical implementation problems. For example, how best todescribe multiple-service changes in a short CV interview? How to secure data about simultaneouschanges in travel cost models?Implications for benefit aggregation across multiple services of biological resourcesFor most applied policy analyses, analysts rely on WTP estimates transferred from paststudies to build benefit estimates for the policy under evaluation. In general, past studies are searchedfor WTP estimates supposedly applying to each service that is changed by the policy under evaluation(that is: WTP for recreational fishing, for landscape amenities, for existence values for a wildlifespecies). Eventually all these transferred WTP estimates are aggregated across services to provide abenefit estimate for the overall multiple-service policy [Desvousges et al. (1998)]. As shown inprevious sections, this aggregation procedure is prone to IVS bias, which (we have reasons to suppose)86