Experimenting with multi-attribute utility survey methods in a multi-dimensional valuation problem

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The use of willingness-to-pay (WTP) survey techniques based on multi-attribute utility (MAU) approaches has been recommended by some authors as a way to deal simultaneously with two difficulties that increasingly plague environmental valuation. The first of these is that, as valuation exercises come to involve less familiar and more subtle environmental effects, such as ecosystem management, lay respondents are less likely to have any idea, in advance, of the value they would attach to a described result. The second is that valuation questions may increasingly be about multi-dimensional effects (e.g. changes in ecosystem function) as opposed for example to changes in visibility from a given point. MAU has been asserted to allow the asking of simpler questions, even in the context of difficult subjects. And it is, as the name suggests, inherently multi-dimensional. This paper asks whether MAU techniques can be shown to ‘make a difference’ in the context of questions about preferences over, and valuation of differences between, alternative descriptions of a forest ecosystem. Making a difference is defined in terms of internal consistency of answers to preference and WTP questions involving three 5-attribute forest descriptions. The method involves first asking MAU-structured questions attribute-by-attribute. The responses to these questions allow researchers to infer each respondent's preferences and WTP. Second, the same respondents are asked directly about their preferences and WTPs. The answer to the making-a-difference question, based largely on comparing the inferred and stated results, is not straightforward. Overall, the inferred results are good ‘predictors’ of what is stated. But the agreement is by no means perfect. And the individual differences are not explainable by the socio-economic characteristics of the individuals. Since the technique involves creating a long, somewhat tedious, and even apparently confusing series of tasks (though each task may itself be simple), it is by no means clear that the prescription, ‘use MAU techniques’, holds the same level of practical as of theoretical promise.