Is Imprecise Knowledge Better than Conflicting Expertise? Evidence from Insurers’ Decisions in the United States

This paper reports the results of the first experiment in the United States designed to distinguish two sources of ambiguity: imprecise ambiguity (expert groups agree on a range of probability, but not on any point estimate) versus conflict ambiguity (each expert group provides precise probability estimates which differ from one group to another). The specific context is whether risk professionals (here, insurers) behave differently under risk and different types of ambiguity when pricing catastrophic risks (floods and hurricanes) and noncatastrophic risks (home fires). The data show that insurers charge higher premiums when faced with ambiguity than when the probability of a loss is well specified (risk). Furthermore, they tend to charge more for conflict ambiguity than imprecise ambiguity for flood and hurricane hazards, but less in the case of fire. The source of ambiguity also impacts causal inferences insurers make to reduce their uncertainty.