Regret-free truth-telling voting rules

Agustín Bonifacio, R. Pablo Arribillaga and Marcelo Fernández

No 4543, Asociación Argentina de Economía Política: Working Papers from Asociación Argentina de Economía Política

Abstract: We study the ability of different classes of voting rules to induce agents to report their preferences truthfully, if agents want to avoid regret. First, we show that regret-free truth-telling is equivalent to strategy-proofness among tops-only rules. Then, we focus on three important families of (non-tops-only) voting methods: maxmin, scoring, and Condorcet consistent ones. We prove positive and negative results for both neutral and anonymous versions of maxmin and scoring rules. In several instances we provide necessary and sufficient conditions. We also show that Condorcet consistent rules that satisfy a mild monotonicity requirement are not regret-free truth-telling. Successive elimination rules fail to be regret-free truth-telling despite not satisfying the monotonicity condition. Lastly, we provide two characterizations for the case of three alternatives and two agents.

JEL-codes: D7 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2022-11
New Economics Papers: this item is included in nep-des and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://aaep.org.ar/works/works2022/4543.pdf (application/pdf)

Related works:
Working Paper: Regret-free truth-telling voting rules (2025)
Working Paper: Regret-Free Truth-Telling Voting Rules (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aep:anales:4543

Access Statistics for this paper

More papers in Asociación Argentina de Economía Política: Working Papers from Asociación Argentina de Economía Política Contact information at EDIRC.
Bibliographic data for series maintained by Juan Manuel Quintero ().