The rationality and efficacy of decisions under uncertainty and the value of an experiment


A decision maker faces a known prior distribution over payoff relevant states. We compare the expected utility of this individual under two scenarios. In the first, the decision maker makes a choice without further information. In the second, the decision maker has access to an experiment before choosing an action. However, the decision maker does not know the true joint distribution over states and messages. The value of the experiment as measured by the difference in the two utility levels can be negative as well as positive. We give a condition which is necessary and sufficient for the experiment to be valuable in our sense, for any decision problem.

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Correspondence to Stephen Morris.

Additional information

An earlier version of this paper was circulated under the title “Noisy Bayes Updating and the Value of Information.” We have gained from the comments of Stephen Coate, John Geanakoplos, Larry Samuelson, Timothy Van Zandt and seminar participants at Harvard Business School, Princeton, Boston University, the international conference on game theory at Stony Brook 1992 and the Winter meeting of the Econometric Society at Anaheim 1993. The first author received support for this project from NSF grant #SES-9308515 and a University of Pennsylvania Research Foundation Grant.

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Morris, S., Shin, H.S. The rationality and efficacy of decisions under uncertainty and the value of an experiment. Econ Theory 9, 309–324 (1997).

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JEL classification number

  • D81