Elicitation methods aim to build participants' distributions about a parameter of interest. In most elicitation studies this parameter is rarely known in advance and hinders an objective comparison between elicitation methods. In two experiments, participants were first presented with a fixed random sequence of images and numbers and subsequently their subjective distributions of percentages of one of those numbers was elicited. Importantly, the true percentage was set in advance. The first experiment tested whether receiving instructions as to the elicitation method (...) would assist in estimating a true value more accurately than receiving no instructions and whether accuracy was determined by the numerical skills of the participants. The second experiment sought to compare the elicitation method used in the first experiment with a variation of a graphical elicitation method. The results indicate that (i) receiving instructions as to the elicitation method does assist in producing estimates closer to a true percentage value, (ii) the level of numerical skills does not play a part in the accuracy of the estimation (Experiment 1), and (iii) although the average estimates of the betting and graphical method are not significantly different, the betting method leads to more precise estimations than the graphical method (Experiment 2). Both studies featured statistical procedures (functional data analysis and a novel clustering technique) not considered in past research on the elicitation of subjective distributions. The implications of these results are discussed in relation to a recent key study. (shrink)

Scientists are often asked to advise political institutions on pressing risk-related questions, like climate change or the authorization of medical drugs. Given that deliberation will often not eliminate all disagreements between scientists, how should their risk assessments be aggregated? I argue that this problem is distinct from two familiar and well-studied problems in the literature: judgment aggregation and probability aggregation. I introduce a novel decision-theoretic model where risk assessments are compared with acceptability thresholds. Majority voting is then defended by means (...) of robustness considerations. (shrink)

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.