Mechanism Design for Personalized Policy: A Field Experiment Incentivizing Exercise
中文摘要
个性化政策在理论上能够提升政策效果。然而,当个体类型不可观测且政策制定者与个体的偏好不一致时,个性化难以实现,这可能导致个体谎报其类型。机制设计提供了一种克服该问题的策略:提供一个“激励相容”的政策选项菜单,促使参与者选择为其类型所设计的方案。我们利用一项在印度城市地区针对6,800名患有糖尿病和高血压的成年人对锻炼激励进行个性化的田野实验,发现相对于“一刀切”基准,采用激励相容的选择菜单进行个性化能显著改善项目绩效,使激励对锻炼的处理效应提高80%,同时不增加激励成本。提供选择所实现的效果与利用大量可观测变量进行个性化相近,但无需同等的数据要求。
Abstract
Personalizing policies can theoretically increase their effectiveness. However, personalization is difficult when individual types are unobservable and the preferences of policymakers and individuals are not aligned, which could cause individuals to misreport their type. Mechanism design offers a strategy to overcome this issue: offer an “incentive‐compatible” menu of policy choices designed to induce participants to select the variant intended for their type. Using a field experiment that personalized incentives for exercise among 6,800 adults with diabetes and hypertension in urban India, we show that personalizing with an incentive‐compatible choice menu substantially improves program performance, increasing the treatment effect of incentives on exercise by 80% without increasing incentive costs relative to a one‐size‐fits‐all benchmark. Offering choice achieves similar performance to personalizing with an extensive set of observable variables, but without the same data requirements.