Published online by Cambridge University Press: 01 January 2022
Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackle decision-making under severe uncertainty with multiple models, and we illustrate the approach with a case study: insurance pricing using hurricane models. The confidence approach has important consequences for this case and offers a powerful framework for a wide class of problems. We end by discussing different ways in which model ensembles can feed information into the approach, appropriate to different collections of models.
We thank Tom Philp for numerous discussions about hurricane modeling and for his helpful advice on navigating the hurricane science literature. Thanks also to Jan-Willem Romeijn, Sean Gryb, Simon Dietz, and Jonathan Livengood for their comments on earlier drafts.