Decision Making for Low Probability Events: A Conceptual Framework

Recent empirical evidence from field surveys and controlled laboratory experiments reveal anomalies with respect to decisions by individuals to protect themselves against low probability, high loss events. In particular, behavior is frequently at odds with what would be predicted by standard models of choice which involve benefit-cost comparisons. This paper develops a framework for analyzing decisions for low probability events and discusses their policy implications. The framework highlights the following four interrelated components: (1) Type of information collected by individuals in making their decisions (i.e., accuracy of data on losses, probabilities and protective options); (2) The decision process of individuals (e.g., expected utility maximization, threshold models); (3) Implications of policies on specific groups (e.g., affected individuals. general taxpayers); and (4) Welfare implications (e.g., equity and efficiency considerations). Examples from studies on natural hazards, health and safety problems will be used to illustrate how this framework synthesizes descriptive models of choice with policy prescription. The paper concludes by suggesting directions for future research