Nonmanipulable Bayesian testing

Colin Stewart

Journal of Economic Theory, 2011, vol. 146, issue 5, 2029-2041

Abstract: This paper considers the problem of testing an expert who makes probabilistic forecasts about the outcomes of a stochastic process. I show that, as long as uninformed experts do not learn the correct forecasts too quickly, a likelihood test can distinguish informed from uninformed experts with high prior probability. The test rejects informed experts on some data-generating processes; however, the set of such processes is topologically small. These results contrast sharply with many negative results in the literature.

Keywords: Probability; forecasts; Testing; Experts (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Nonmanipulable Bayesian Testing (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:146:y:2011:i:5:p:2029-2041

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