Optimal information censorship Articles uri icon

publication date

  • July 2019

start page

  • 377

end page

  • 385

volume

  • 163

International Standard Serial Number (ISSN)

  • 0167-2681

Electronic International Standard Serial Number (EISSN)

  • 1879-1751

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.

keywords

  • bayesian persuasion; censorship