The synthetic control method (SCM) allows estimating the causal effect of an intervention in settings where panel data on a small number of treated and control units are available. We show that the existing SCM, as well as its extensions, can be easily modified to estimate how much of the ``total'' effect goes through observed causal channels. Our new mediation analysis synthetic control (MASC) method requires additional assumptions that are arguably mild in many settings. We illustrate the implementation of MASC in an empirical application estimating the direct and indirect effects of an anti-smoking intervention (California's Proposition 99).
翻译:合成控制方法(合成控制方法)可以估计在小组掌握少量处理和控制单位的数据的情况下进行干预的因果关系,我们表明,现有的合成控制方法及其扩展可以很容易地加以修改,以估计“总”影响有多少是通过观察到的因果关系渠道产生的。我们新的调解分析合成控制方法需要额外的假设,在许多情况下,这些假设可以说是轻微的。我们用经验性应用来估计反吸烟干预的直接和间接影响(加利福尼亚州第99号提案)来说明MASC的实施情况。