The Impact of Consequence Information on Insurance Choice

Abstract Individuals frequently make insurance choices that appear sub-optimal, possibly reflecting difficulty mapping insurance contracts to their distribution of financial consequences. We develop and experimentally test a decision aid that provides this mapping in two experiments mirroring typical health insurance decisions. Compared to standard feature-based information, our distributionbased tool substantially reduces dominance violations and changes choice patterns across a range of menus. Under feature-based displays, choices can be most easily rationalized by models of heuristic choices, such as minimizing premium or deductible. With the decision aid, significantly more people have choice patterns that are better explained by expected utility theory.