摘要翻译：
为了从观察数据中提出明智的政策建议，我们必须能够从随机噪声和混杂效应中识别真实的治疗效果。根据预处理结果将处理单元与控制单元匹配的差中差技术，如综合控制方法，已被作为解释混杂的原则性方法提出。然而，我们表明，使用合成对照或其他匹配程序可以引入对平均(RTM)偏差的回归，以估计对被治疗者的平均治疗效果。通过仿真，我们发现RTM偏差可以导致膨胀的类型I错误率，以及降低功率在典型的策略评估设置。此外，我们提供了一种新的RTM偏置校正方法，可以减少偏置并获得适当的I型错误率。此校正可用于执行灵敏度分析，以确定RTM如何影响结果。我们使用我们提出的校正和敏感性分析重新分析关于加州99号提案的影响数据，这是一个大规模的烟草控制计划，对全州吸烟率的影响。
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英文标题：
《Regression to the Mean's Impact on the Synthetic Control Method: Bias
  and Sensitivity Analysis》
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作者：
Nicholas Illenberger, Dylan S. Small, Pamela A. Shaw
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最新提交年份：
2019
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分类信息：

一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  To make informed policy recommendations from observational data, we must be able to discern true treatment effects from random noise and effects due to confounding. Difference-in-Difference techniques which match treated units to control units based on pre-treatment outcomes, such as the synthetic control approach have been presented as principled methods to account for confounding. However, we show that use of synthetic controls or other matching procedures can introduce regression to the mean (RTM) bias into estimates of the average treatment effect on the treated. Through simulations, we show RTM bias can lead to inflated type I error rates as well as decreased power in typical policy evaluation settings. Further, we provide a novel correction for RTM bias which can reduce bias and attain appropriate type I error rates. This correction can be used to perform a sensitivity analysis which determines how results may be affected by RTM. We use our proposed correction and sensitivity analysis to reanalyze data concerning the effects of California's Proposition 99, a large-scale tobacco control program, on statewide smoking rates.
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PDF链接：
https://arxiv.org/pdf/1909.04706