Abstract:
The existing evidence from laboratory experiments suggests that relatively simple heuristics describe observed search behavior better than the optimal stopping rule derived under risk neutrality. Such behavior could be generated by two entirely di®erent classes of decision rules: (i) rules that are optimal conditional on utility functions that depart from risk neutrality or (ii) heuristics that derive from limited cognitive processing capacities and satisfycing. In this paper, we develop and test search models that depart from the standard assumption of risk neutrality in order to distinguish these two possi- bilities. In our experiment, we present subjects not only with a standard search task, but also with a series of lottery tasks that serve to elicit the shape of their utility functions. We do not ¯nd a relationship between behavior in the search task and measures of risk aversion. Our data suggest, however, that loss aversion is important for explaining search behavior.