Binary mechanisms under privacy-preserving noise
成果类型：
Article
署名作者：
Pourbabaee, Farzad; Echenique, Federico
署名单位：
California Institute of Technology; University of California System; University of California Berkeley
刊物名称：
JOURNAL OF ECONOMIC THEORY
ISSN/ISSBN：
0022-0531
DOI：
10.1016/j.jet.2025.105965
发表日期：
2025
关键词：
摘要：
We study mechanism design for public-good provision under a noisy privacy-preserving transformation of individual agents' reported preferences. The setting is a standard binary model with transfers and quasi-linear utility. Agents report their preferences for the public good, which are randomly flipped, so that any individual report may be explained away as the outcome of noise. We study the tradeoffs between preserving the public decisions made in the presence of noise (noise sensitivity), pursuing efficiency, and mitigating the effect of noise on revenue.