The Annals of Statistics

Merging and testing opinions

Luciano Pomatto, Nabil Al-Najjar, and Alvaro Sandroni

Full-text: Open access

Abstract

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.

Article information

Source
Ann. Statist., Volume 42, Number 3 (2014), 1003-1028.

Dates
First available in Project Euclid: 20 May 2014

Permanent link to this document
https://projecteuclid.org/euclid.aos/1400592650

Digital Object Identifier
doi:10.1214/14-AOS1212

Mathematical Reviews number (MathSciNet)
MR3210994

Zentralblatt MATH identifier
1305.62025

Subjects
Primary: 62A01: Foundations and philosophical topics
Secondary: 91A40: Game-theoretic models

Keywords
Test manipulation Bayesian learning

Citation

Pomatto, Luciano; Al-Najjar, Nabil; Sandroni, Alvaro. Merging and testing opinions. Ann. Statist. 42 (2014), no. 3, 1003--1028. doi:10.1214/14-AOS1212. https://projecteuclid.org/euclid.aos/1400592650


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