Designing Information for Opportunistic Voters

14 Pages Posted: 5 May 2020

See all articles by Volker Britz

Volker Britz

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich

Akaki Mamageishvili

Offchain Labs

Date Written: April 8, 2020

Abstract

We model an election with two alternatives in a continuum electorate. Each citizen may either vote for their preferred alternative, or abstain. Their incentives are such that they find it optimal to turn out if and only if they expect their preferred alternative to win. Voters form beliefs about the prospects of winning, based on information they obtain from media outlets. We assume that these media outlets are partisan: They wish to maximize the probability that the supporters of their preferred alternative turn out. Media outlets cannot \lie," but they can choose what information to pass on to voters. More specifically, we assume they commit to informing voters if they learn that popular support for a particular alternative passes some threshold, in the spirit of the information design literature. We distinguish two cases: Voters listen to both sides' media outlets, or voters listen only to their own side's partisan media. In the former case, media inform citizens perfectly, and there is an equilibrium where voters learn which side is in the majority so that only that side votes. In the latter case, the media supporting the disadvantaged side provides information. This gives rise to equilibria in which, with positive probability, voters on both sides are confident of winning and thus turn out.

Suggested Citation

Britz, Volker and Mamageishvili, Akaki, Designing Information for Opportunistic Voters (April 8, 2020). Available at SSRN: https://ssrn.com/abstract=3571781 or http://dx.doi.org/10.2139/ssrn.3571781

Volker Britz

ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich ( email )

Zürichbergstrasse 18
Zurich, 8092
Switzerland

Akaki Mamageishvili (Contact Author)

Offchain Labs ( email )

Zurich
Switzerland

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
73
Abstract Views
451
Rank
643,219
PlumX Metrics