论文标题
差异差异很少的单位和空间相关性的推断
Inference in Difference-in-Differences with Few Treated Units and Spatial Correlation
论文作者
论文摘要
当几乎没有处理的单位和错误相关时,我们考虑了差异差异的推断问题(DID)。我们首先表明,当有一个经过处理的单元时,某些现有的推理方法是为几乎没有处理的设置而设计的,而当错误依赖较弱时,许多对照单位渐近地有效。但是,这些方法可能没有多个处理的单元无效。我们提出的替代方案在这种情况下渐近有效,即使不可用的相关距离指标。
We consider the problem of inference in Difference-in-Differences (DID) when there are few treated units and errors are spatially correlated. We first show that, when there is a single treated unit, some existing inference methods designed for settings with few treated and many control units remain asymptotically valid when errors are weakly dependent. However, these methods may be invalid with more than one treated unit. We propose alternatives that are asymptotically valid in this setting, even when the relevant distance metric across units is unavailable.