Abstract

Erev, Ert, and Roth organized three choice prediction competitions focused on three related choice tasks: One shot decisions from description (decisions under risk), one shot decisions from experience, and repeated decisions from experience. Each competition was based on two experimental datasets: An estimation dataset, and a competition dataset. The studies that generated the two datasets used the same methods and subject pool, and examined decision problems randomly selected from the same distribution. After collecting the experimental data to be used for estimation, the organizers posted them on the Web, together with their fit with several baseline models, and challenged other researchers to compete to predict the results of the second (competition) set of experimental sessions. Fourteen teams responded to the challenge: The last seven authors of this paper are members of the winning teams. The results highlight the robustness of the difference between decisions from description and decisions from experience. The best predictions of decisions from descriptions were obtained with a stochastic variant of prospect theory assuming that the sensitivity to the

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