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Abstract
Environmental intervention is often seen as being high risk and high return. Traditional scientific
hypothesis testing provides limited guidance to policy makers unless there is a high level of
certainty in the supporting scientific evidence. Traditional cost-benefit analysis under uncertainty
has shortcomings when considering high-risk investment, largely due to the choice of how to
discount uncertainty outcomes. A corollary is that traditional cost-benefit analysis does not place a
value on increased certainty, an important outcome of successful scientific research. A fiducial costbenefit
methodology is presented in this paper, which integrates hypothesis testing and traditional
cost-benefit analysis. The fiducial approach is one way of objectively placing a value on changes in
the level of uncertainty that does not depend on an assumption about a decision maker's attitudes
towards variability in returns. This has two important implications. First, there is a level of
uncertainty at which we would reject an investment with a positive expected net rate of return on
the basis that the uncertainty associated with the outcome is too great. Second, it is possible to value
a program of research that reduces the uncertainty about a critical decision parameter. An example
based on data from a weather modification experiment conducted in South Australia is presented.
The approach is the generalised using more traditional statistical methodology.