Generating Ambiguity in the Laboratory
This article develops a method for drawing samples from a distribution with no finite quantiles or moments. The method provides researchers with a way to give subjects the experience of ambiguity. In any experiment, learning the distribution from experience is impossible for the subjects, essentially because it is impossible for the experimenter. We characterize our method, illustrate it in simulations, and then test it in a laboratory experiment. Our method does not withhold sampling information, does not assume that the subject is incapable of making statistical inferences, is replicable across experiments, and requires no special apparatus. We compare our method to the techniques used in related experiments that attempt to produce an ambiguous experience for the subjects. This paper was accepted by Peter Wakker, decision analysis.
Volume (Year): 57 (2011)
Issue (Month): 4 (April)
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- Mohammed Abdellaoui & Aurelien Baillon & Laetitia Placido & Peter P. Wakker, 2011.
"The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation,"
American Economic Review,
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- Mohammed Abdellaoui & Laetitia Placido & Aurélien Baillon & P.P. Wakker, 2011. "The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00609214, HAL.
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