摘要翻译：
在研究随机对照试验（RCTs）的文献中，通常假设参与试验的单位的潜在结果是确定性的。这一假设不太可能成立，因为在实验过程中可能会发生随机冲击。在本文中，我们考虑了一个具有个体水平治疗分配的RCT的情况，我们考虑了个体水平和集群水平（例如村水平）的冲击来影响潜在的结果。我们表明，我们可以在两个条件下得出推论：ATE条件于簇级冲击的实现，使用异方差-鲁棒标准差；ATE使用聚类稳健标准误差来抵消这些冲击。通过聚类，研究人员可以测试如果实验期间发生的随机冲击不同，治疗是否仍然有效果。然后，决定是否集群取决于一个人希望达到的外部有效性水平。
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英文标题：
《Clustering and External Validity in Randomized Controlled Trials》
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作者：
Antoine Deeb, Cl\'ement de Chaisemartin
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最新提交年份：
2021
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分类信息：

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：
  In the literature studying randomized controlled trials (RCTs), it is often assumed that the potential outcomes of units participating in the experiment are deterministic. This assumption is unlikely to hold, as stochastic shocks may take place during the experiment. In this paper, we consider the case of an RCT with individual-level treatment assignment, and we allow for individual-level and cluster-level (e.g. village-level) shocks to affect the potential outcomes. We show that one can draw inference on two estimands: the ATE conditional on the realizations of the cluster-level shocks, using heteroskedasticity-robust standard errors; the ATE netted out of those shocks, using cluster-robust standard errors. By clustering, researchers can test if the treatment would still have had an effect, had the stochastic shocks that occurred during the experiment been different. Then, the decision to cluster or not depends on the level of external validity one would like to achieve.
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PDF链接：
https://arxiv.org/pdf/1912.01052