Year: 2024
Type: article
Abstract: Experts in a population hold (a) beliefs over a state and (b) beliefs over the population’s belief distribution. If these are generated via Bayesian updating from a common prior using signal observations from a fixed information structure, a linear regression using the experts’ beliefs identifies the information structure, provided there are no more states than signals. Furthermore, an eigenvector equation derived from the experts’ beliefs identifies the prior. Thus, the ex ante informational environment (i.e., how signals are generated) can be determined using ex post data (i.e., the experts’ beliefs). I interpret these findings and also discuss identification when states outnumber signals.
DOI: 10.1086/733781
Author: Jonathan Libgober
Institution: University of Southern California
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4403823879