Optimal information censorship

B-Tier
Journal: Journal of Economic Behavior and Organization
Year: 2019
Volume: 163
Issue: C
Pages: 377-385

Score contribution per author:

2.011 = (α=2.01 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper analyses Bayesian persuasion of a privately informed receiver in a linear framework. The sender is restricted to censorship, that is, to strategies in which each state is either perfectly revealed or hidden. I develop a new approach to finding optimal censorship strategies based on direct optimisation. I also show how this approach can be used to restrict the set of optimal censorship schemes, and to analyse optimal censorship under certain classes of distributions of the receiver’s type.

Technical Details

RePEc Handle
repec:eee:jeborg:v:163:y:2019:i:c:p:377-385
Journal Field
Theory
Author Count
1
Added to Database
2026-01-25