评估随机阈值设计中的阈值政策：回归不连续设计的一个警示性案例
Evaluating Threshold Policies in Randomized Threshold Designs: A Cautionary Tale for Regression Discontinuity Designs
- Graduate School of Economics, Kyoto University（京都大学经济学研究科）
- Graduate School of Economics, The University of Tokyo（东京大学经济学研究科）
- Graduate School of Economics, Hitotsubashi University（一桥大学经济学研究科）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出利用随机阈值变化识别处理分配与激励反应效应，实证显示传统RD估计为正而激励效应为负且更大，警示阈值政策评估需谨慎。
AI中文摘要：
许多政策根据得分是否跨越阈值来决定是否给予处理。回归不连续（RD）设计能够识别处理分配的效果，但阈值政策本身也可能重塑个体的激励，诱发行为反应，即使在处理状态保持不变的情况下也会影响结果——这是传统RD设计无法捕捉的渠道。我们开发了一个框架，利用政策阈值的随机变化，结合秩不变型约束，来识别处理分配效应和激励反应效应。我们利用马拉维一项基于成绩的奖学金实验的数据，说明了这一区分的实证相关性。在该示例中，传统RD估计为正，而激励反应效应为负，且其幅度是前者的两倍多。这些发现表明，阈值政策可能产生意外的负面行为反应，可能反映了高要求阈值所导致的挫败感，并警示在评估阈值政策时不要仅依赖传统RD估计。
英文摘要：
Many policies assign treatment according to whether a score crosses a cutoff. Regression discontinuity (RD) designs identify the effect of treatment assignment, but the threshold policy itself may also reshape individuals' incentives, inducing behavioral responses that affect outcomes even holding treatment status fixed---a channel that conventional RD designs cannot capture. We develop a framework that exploits randomized variation in policy thresholds, together with rank-invariance-type restrictions, to identify the treatment-assignment and incentive-response effects. We illustrate the empirical relevance of this distinction using data from a merit-based scholarship experiment in Malawi. In this illustration, the conventional RD estimate is positive, while the incentive-response effect is negative and more than twice as large in magnitude. These findings suggest that threshold policies may generate unintended adverse behavioral responses, potentially reflecting discouragement induced by demanding thresholds, and caution against relying solely on conventional RD estimates when evaluating threshold policies.
