This paper presents identification results for the probability of causation when there is sample selection. We show that the probability of causation is partially identified for individuals who are always observed regardless of treatment status and derive sharp bounds under three increasingly restrictive sets of assumptions. The first set imposes an exogenous treatment and a monotone sample selection mechanism. To tighten these bounds, the second set also imposes the monotone treatment response assumption, while the third set additionally imposes a stochastic dominance assumption. Finally, we use experimental data from the Colombian job training program J\'ovenes en Acci\'on to empirically illustrate our approach's usefulness. We find that, among individuals who are always employed regardless of treatment, at least 12% and at most 19% transition to the formal labor market because of this training program.
翻译:本文介绍了在抽样选择时因果关系概率的确定结果。 我们显示,对于无论治疗状况如何总是被观察的个人,因果关系概率是部分确定的,并且根据三套日益严格的假设得到了清晰的界限。 第一套设定了一种外源治疗和单一色素抽样选择机制。为了收紧这些界限,第二套设定了单质治疗反应假设,而第三套设定了一种随机优势假设。最后,我们用哥伦比亚职业培训方案J\'ovenes en Accial的实验数据来从经验上说明我们的方法的效用。我们发现,在无论治疗方式如何总是被雇用的人中,至少有12%,最多是19%,因为这一培训方案而过渡到正规劳动力市场。