On the veil-of-ignorance principle: welfare-optimal information disclosure in Voting
Karine van der Straeten and
Takuro Yamashita
Additional contact information
Karine van der Straeten: TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CNRS - Centre National de la Recherche Scientifique
Working Papers from HAL
Abstract:
Voters' voting decisions crucially depend on their information. Thus, it is an important question how much / what kind of information they should know, as a normative guidance of the optimal extent of transparency. We consider a simple two-alternative majority voting environment, and study the optimal information disclosure policy by a utilitarian social planner. Although full transparency is sometimes (informally) argued as ideal, we show that full transparency is often strictly suboptimal. This is related to the well-known potential mis-match between what a majority wants and what is socially optimal. Under certain conditions, in order to alleviate this mismatch, the op-timal policy discloses just the "anonymized" information about the value of the alternatives to the voters, placing them effectively behind a partial "veil of ignorance".
Date: 2024-12-16
Note: View the original document on HAL open archive server: https://hal.science/hal-04841216v1
References: Add references at CitEc
Citations:
Downloads: (external link)
https://hal.science/hal-04841216v1/document (application/pdf)
Related works:
Working Paper: On the veil-of-ignorance principle: welfare-optimal information disclosure in Voting (2025) 
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:hal:wpaper:hal-04841216
Access Statistics for this paper
More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().