Ecosystem services

Economic valuation of ecosystem goods and services: a review for decision makers

There is increasing interest in the use of economic valuation of ecosystem goods and services for a wide variety of purposes. These include relatively familiar uses in project appraisal and more novel applications in advocacy, performance tracking and accounting in public and private settings. Decision makers who use valuation information need to understand the background, strengths and weaknesses of these approaches. The methods have a strong foundation in economic theory and offer a rapidly growing evidence base, improving ability to evaluate a broad range of ecosystem goods and services. Nevertheless, there are theoretical and practical limitations that need to be understood and kept in mind when interpreting results. In this paper, we briefly review the economic valuation methods and situate them in their historical and theoretical contexts. We assess the main critiques, attempts at resolving them, and implications for the usefulness of the methods in different contexts. We examine the main barriers and opportunities for wider uses of valuation evidence, and draw conclusions on the appropriate role of valuation in future, as a tool for aiding reflection and deliberation processes.

Disentangling the influence of knowledge on attribute non-attendance

We seek to disentangle the effect of knowledge about an environmental good on respondents' propensity to ignore one or more attributes on the choice cards in a discrete choice experiment eliciting people's preferences for increased protection of cold-water corals in Norway. We hypothesize that a respondent's level of knowledge influences the degree to which she ignores attributes. Respondents participated in a quiz on cold-water coral prior to the valuation task and we use the result of the quiz as an ex-ante measure of their knowledge. Our results suggests that a high level of knowledge, measured by a high quiz score, is associated with higher probabilities of attendance to the three non-cost attributes, although this effect is only significant for one of them. A higher quiz score is also associated with a significantly lower probability of attending to the cost attribute. Furthermore, although being told your score has mixed directional effects on attribute non-attendance, it does not significantly affect the probability of attending to any of the attributes. Finally, allowing for attribute non-attendance leads to substantially lower conditional willingness-to-pay estimates. This highlights the importance of measuring how much people know about the goods over which they are choosing, and underlines that more research is needed to understand how information influences the degree to which respondents ignore attributes.