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 mechanisms that seek to preserve the public decisions made in the presence of noise (noise sensitivity), pursue efficiency, and mitigate the effect of noise on revenue. The paper analyzes the trade-offs between these competing considerations.
翻译:我们研究在对个别代理人所报告的偏好进行吵闹的隐私保护改造下提供公益服务的机制设计。设置是一个标准二元模式,涉及转让和准线性公用事业。代理报告他们偏爱公益,这些公益被随机地“扭曲 ”, 以便任何个人报告都可以被解释为噪音的结果。我们研究那些在噪音(噪音敏感度)面前维护公众决策的机制,追求效率,并减轻噪音对收入的影响。文件分析了这些相互竞争的考虑因素之间的权衡。