A True Expert Knows which Question Should Be Asked

Yossi Feinberg and Eddie Dekel
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Yossi Feinberg: Stanford U

Research Papers from Stanford University, Graduate School of Business

Abstract: We suggest a test for discovering whether a potential expert is informed of the distribution of a stochastic process. In a non-Bayesian non-parametric setting, the expert is asked to make a prediction which is tested against a single realization of the stochastic process. It is shown that by asking the expert to predict a "small" set of sequences, the test will assure that any informed expert can pass the test with probability one with respect to the actual distribution. Moreover, for the uninformed non-expert it is impossible to pass this test, in the sense that for any choice of a "small" set of sequences, only a "small" set of measures will assign a positive probability to the given set. Hence for "most" measures, the non-expert will surely fail the test. We define small as category 1 sets, described in more detail in the paper.

Date: 2004-06
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Working Paper: A True Expert Knows which Question Should be Asked (2006)
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Persistent link: https://EconPapers.repec.org/RePEc:ecl:stabus:1856

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