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
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.
Citation
Download CitationLuciano Pomatto. Nabil Al-Najjar. Alvaro Sandroni. "Merging and testing opinions." Ann. Statist. 42 (3) 1003 - 1028, June 2014. https://doi.org/10.1214/14-AOS1212
Information
Published: June 2014
First available in Project Euclid: 20 May 2014
Digital Object Identifier: 10.1214/14-AOS1212
Subjects:
Primary: 62A01
Secondary: 91A40
Keywords: Bayesian learning , Test manipulation
Rights: Copyright © 2014 Institute of Mathematical Statistics
JOURNAL ARTICLE
26 PAGES
Vol.42 • No. 3 • June 2014
