The relationship between risk attitudes and heuristics in search tasks: A laboratory experiment

Abstract

Experimental studies of search behavior suggest that individuals stop searching earlier than the optimal, risk-neutral stopping rule predicts. Two different classes of
decision rules could generate this behavior: rules that are optimal conditional on utility functions departing from risk neutrality, or heuristics derived from limited cognitive processing capacities and satisficing. To discriminate between these possibilities, we conduct an experiment that consists of a search task as well as a lottery task designed to elicit utility functions. We find that search heuristics are not related to measures of risk aversion, but to measures of loss aversion.