Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31221 
Year of Publication: 
2004
Series/Report no.: 
Discussion Paper No. 1385
Publisher: 
Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science, Evanston, IL
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 or 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.
JEL: 
D83
C14
C50
Document Type: 
Working Paper

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