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Generating ambiguity in the laboratory

  • Jack Douglas Stecher


    (Carnegie Mellon University)

  • Timothy Shields


    (Argyros School of Business & Economics, Chapman University)

  • John Dickhaut

    (Economic Science Institute, Chapman University)

This article develops a method for drawing samples from which it is impossible to infer any quantile or moment of the underlying distribution. 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 describe our method mathematically, illustrate it in simulations, and then test it in a laboratory experiment. Our technique 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.

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Paper provided by Chapman University, Economic Science Institute in its series Working Papers with number 08-10.

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Length: 44 pages
Date of creation: 2008
Date of revision:
Handle: RePEc:chu:wpaper:08-10
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