Predicting insurance demand from risk attitudes

Can measured risk attitudes and associated structural models predict insurance demand? In an experiment (n = 1730), we elicit measures of utility curvature, probability weighting, loss aversion, preference for certainty use them to parameterize seventeen common (e.g., expected utility, cumulative prospect theory). Subjects also make 12 choices over different probabilities prices. The show coherence some correlation with various risk-attitude measures. Yet all the poorly, often less accurately than random predictions. This is because established opposite reactions changes more sensitivity prices people display. Approaches that temper price responsiveness promise predicting across conditions.