Matching Methods in Practice: Three Examples
从理论文献中提炼出匹配方法在实践中的操作建议，并通过三个详细的应用案例加以说明，帮助实证研究者正确使用匹配或倾向得分方法估计因果效应。
There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection-on-observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper, I discuss some of the lessons for practice from the theoretical literature and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.