Selecting the Most Effective Nudge: Evidence From a Large‐Scale Experiment on Immunization
Econometrica · 2025 · Abhijit Banerjee、Arun G. Chandrasekhar、Suresh Dalpath、Esther Duflo、John Floretta、Matthew O. Jackson
中文摘要
政策制定者往往会选择由不同干预措施以不同剂量组合而成的政策组合。我们开发了一种新方法——处理变体聚合（TVA）——用于从大型析因设计中选择政策。TVA将不存在实质性差异的政策变体合并，并剔除被判定为无效的变体。这使我们能够将关注范围限定于聚合后的政策变体，一致估计其对结果的影响，并在对赢家诅咒进行调整后估计最优政策的效应。我们将TVA应用于一项大型随机对照试验，该试验检验了在印度哈里亚纳邦刺激免疫接种需求的干预措施。所考察的政策包括提醒、激励以及负责社区动员的当地大使。对这些干预措施进行交叉随机化，并为每项干预设置不同剂量或类型，共产生75种组合。影响最大的政策（将激励措施、作为信息枢纽的大使与提醒相结合）与现状相比，使免疫接种次数增加44%。成本效益最高的政策（信息枢纽型大使与短信提醒，但不提供激励措施）与现状相比，使每美元对应的免疫接种次数增加9.1%。
Abstract
Policymakers often choose a policy bundle that is a combination of different interventions in different dosages. We develop a new technique— treatment variant aggregation (TVA)—to select a policy from a large factorial design. TVA pools together policy variants that are not meaningfully different and prunes those deemed ineffective. This allows us to restrict attention to aggregated policy variants, consistently estimate their effects on the outcome, and estimate the best policy effect adjusting for the winner's curse. We apply TVA to a large randomized controlled trial that tests interventions to stimulate demand for immunization in Haryana, India. The policies under consideration include reminders, incentives, and local ambassadors for community mobilization. Cross‐randomizing these interventions, with different dosages or types of each intervention, yields 75 combinations. The policy with the largest impact (which combines incentives, ambassadors who are information hubs, and reminders) increases the number of immunizations by 44% relative to the status quo. The most cost‐effective policy (information hubs, ambassadors, and SMS reminders, but no incentives) increases the number of immunizations per dollar by 9.1% relative to the status quo.