Decision making and trade without probabilities
What is a rational decision-maker supposed to do when facing an unfamiliar problem, where there is uncertainty but no basis for making probabilistic assessments? One answer is to use a form of expected utility theory, and assume that agents assign their own subjective probabilities to each element of the (presumably known) state space. In contrast, this paper presents a model in which agents do not form subjective probabilities over the elements of the state space, but nonetheless use new information to update their beliefs about what the elements of the state space are. This model is shown to lead to different predictions about trading behavior in a simple asset market under uncertainty. A controlled laboratory experiment tests the predictions of this model against those of expected utility theory and against the hypothesis that subjects act na¨ıvely and non-strategically. The results suggest that a lack of subjective probabilities does not imply irrational or unpredictable behavior, but instead allows individuals to use both what they know and knowledge of what they do not know in their decision making. Comment un décideur rationnel est-il censé réagir face à un problème qui ne lui est pas familier lorsqu'il existe une certaine incertitude, et en l'absence d'une base sur laquelle effectuer des estimations probabilistes? Une solution consiste à utiliser une forme de la théorie de l'utilité espérée et de présumer que les agents attribuent leurs propres probabilités subjectives à chaque élément de la représentation d'état (sans doute connue). Par contraste, notre article présente un modèle où les agents ne forment pas de probabilités subjectives sur les éléments de la représentation d'état, mais utilisent de nouveaux renseignements afin de mettre à jour leurs croyances sur les éléments formant la représentation d'état. Le comportement des échanges avec ce modèle dans un marché d'actifs simple et incertain nous mène à des prédictions différentes. En utilisant une expé
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Volume (Year): 48 (2011)
Issue (Month): 2 (October)
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