A distributional synthetic control method for policy evaluation
将合成控制法扩展到评估政策干预的分布效应，通过匹配处理单位干预前的分位数残差与对照组的凸组合来识别反事实，并控制可能的不良匹配。
Summary We extend the synthetic control method to evaluate the distributional effects of policy intervention in the possible presence of poor matching. The counterfactuals (or intervention effects) are identified by matching a vector of pre‐intervention quantile residuals of the treated unit and a convex combination of its potential‐control counterparts. The residuals are orthogonal to a set of observable common factors that control for the potentially poor matching. We also apply our method to a set of case studies that explore the distributional effects of state‐level minimum‐wage hikes in the USA.