A Boundedly Rational Decision Algorithm

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 achiev...

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Bibliographic Details
Published inThe American economic review Vol. 90; no. 2; pp. 433 - 438
Main Authors Gabaix, Xavier, Laibson, David
Format Journal Article
LanguageEnglish
Published Menasha, Wis American Economic Association 01.05.2000
Subjects
Algorithms
Cognition
Cognition & reasoning
Cognitive models
Decision making
Decision trees
Discounting
Economic models
Economic theory
Expected values
Experimental data
Game theory
Heuristic
Heuristics
Modeling
Preferences, Behavior, and Welfare
Rationality
Studies
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ISSN0002-8282
1944-7981
DOI10.1257/aer.90.2.433

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Summary: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.
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ISSN:0002-8282
1944-7981
DOI:10.1257/aer.90.2.433