Comparing Treatments across Labor Markets: An Assessment of Nonexperimental Multiple-Treatment Strategies
研究了利用多个地点实施的不同项目数据，通过非实验方法调整个体特征和当地经济条件差异，以比较项目在不同地点的效果，发现两地维度上充分重叠至关重要。
Abstract We study the effectiveness of nonexperimental strategies in adjusting for comparison group differences when using data from several programs, each implemented at a different location, to compare their effect if implemented at alternative locations. First, we adjust for individual characteristics differences simultaneously across all groups using unconfoundedness-based and conditional difference-in-difference methods for multiple treatments. Second, we adjust for differences in local economic conditions and stress their role after program participation. Our results show that it is critical to have sufficient overlap across locations in both dimensions and illustrate the difficulty of adjusting for local economic conditions that differ greatly across locations.