The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools
指出，由于考试成绩中的暂时性噪声和均值回归，传统方法会高估基于学校平均成绩分配资源的项目效果，并展示如何用回归断点设计纠正偏差。以智利900学校项目为例，发现其实际效果远小于普遍认知。
Many programs reward or penalize schools based on students' average performance. Mean reversion is a potentially serious hindrance to the evaluation of such interventions. Chile's 900 Schools Program (P-900) allocated resources based on cutoffs in schools' mean test scores. This paper shows that transitory noise in average scores and mean reversion lead conventional estimation approaches to overstate the impacts of such programs. It further shows how a regressiondiscontinuity design can be used to control for reversion biases. It concludes that P-900 had significant effects on test score gains, albeit much smaller than is widely believed