Merging and testing opinions

Luciano Pomatto; Nabil Al-Najjar; Alvaro Sandroni

doi:10.1214/14-AOS1212

Merging and testing opinions

Luciano Pomatto, Nabil Al-Najjar, Alvaro Sandroni

Managerial Economics, Decision Sciences and Operations

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

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.

Original language	English (US)
Pages (from-to)	1003-1028
Number of pages	26
Journal	Annals of Statistics
Volume	42
Issue number	3
DOIs	https://doi.org/10.1214/14-AOS1212
State	Published - Jun 2014

Keywords

Bayesian learning
Test manipulation

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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AU - Sandroni, Alvaro

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Merging and testing opinions

Abstract

Keywords

ASJC Scopus subject areas

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