From Subjective Probabilities to Decision Weights: The Effect of Asymmetric Loss Functions on the Evaluation of Uncertain Outcomes and Events

Abstract

Much of decision aiding uses a divide-and-conquer strategy to help people with risky decisions. Assessing the utility of outcomes and one's degree of belief in their likelihood are assumed to be separable tasks, the results of which can then be combined to determine the preferred alternative. Evidence from different areas of psychology now provides a growing consensus that this assumption is too simplistic. Observed dependencies in the evaluation of uncertain outcomes and the likelihood of the events giving rise to them are frequent and systematic. Dependencies seem to derive from general strategic processes that take into consideration asymmetric costs of over- vs. underestimates of uncertain quantities. This asymmetric-loss-function interpretation provides a psychological explanation for observed judgments and decisions under uncertainty and links them to other judgment tasks. The decision weights estimated when applying dependent-utility models to choices are not simply reflections of perceived subjective probability but a response to several constraints, all of which modify the weight of risky or uncertain outcomes.