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June 2014 Merging and testing opinions
Luciano Pomatto, Nabil Al-Najjar, Alvaro Sandroni
Ann. Statist. 42(3): 1003-1028 (June 2014). DOI: 10.1214/14-AOS1212


We study the merging and the testing of opinions in the context of a prediction model. In the absence of incentive problems, opinions can be tested and rejected, regardless of whether or not data produces consensus among Bayesian agents. In contrast, in the presence of incentive problems, opinions can only be tested and rejected when data produces consensus among Bayesian agents. These results show a strong connection between the testing and the merging of opinions. They also relate the literature on Bayesian learning and the literature on testing strategic experts.


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Luciano Pomatto. Nabil Al-Najjar. Alvaro Sandroni. "Merging and testing opinions." Ann. Statist. 42 (3) 1003 - 1028, June 2014.


Published: June 2014
First available in Project Euclid: 20 May 2014

zbMATH: 1305.62025
MathSciNet: MR3210994
Digital Object Identifier: 10.1214/14-AOS1212

Primary: 62A01
Secondary: 91A40

Keywords: Bayesian learning , Test manipulation

Rights: Copyright © 2014 Institute of Mathematical Statistics


Vol.42 • No. 3 • June 2014
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