A Boundedly Rational Decision Algorithm - Gabaix, Xavier; Laibson, David (The American economic review, 2000)
Cognition requires scarce inputs, including time and concentration. Since cognition is costly, sophisticated decision-makers should use mental shortcuts, or heuristics, to reduce cognitive burdens. A model is proposed and tested that is motivated by these principles. It is believed this model achieves four goals. First, the model makes quantitative behavioral predictions and, hence, provides a precise alternative to the rational-actor hypothesis. Second, the model is psychologically plausible because it is based on the actual decisions algorithms that subjects claim to use. Third, the model is empirically testable; such a test is provided in this paper. Fourth, the model is broadly applicable, because it can be used to analyze decision problems that can be represented in tree form.