This paper considers identification and estimation of the causal effect of the time Z until a subject is treated on a survival outcome T. The treatment is not randomly assigned, T is randomly right censored by a random variable C and the time to treatment Z is right censored by min(T,C) The endogeneity issue is treated using an instrumental variable explaining Z and independent of the error term of the model. We study identification in a fully nonparametric framework. We show that our specification generates an integral equation, of which the regression function of interest is a solution. We provide identification conditions that rely on this identification equation. For estimation purposes, we assume that the regression function follows a parametric model. We propose an estimation procedure and give conditions under which the estimator is asymptotically normal. The estimators exhibit good finite sample properties in simulations. Our methodology is applied to find evidence supporting the efficacy of a therapy for burn-out.

翻译：本文件考虑确定和估计Z时间的因果关系,直到一个对象在求生结果 T 上得到治疗。治疗不是随机分配的。T 随机右经随机变数C检查,Z 治疗时间由分钟(T,C) 右经检查。处理内分泌问题时使用一种工具变量解释Z,独立于模型的错误术语。我们在一个完全非对称的框架内研究识别。我们显示,我们的规格产生了一个整体方程,其中利息的回归功能是一个解决方案。我们提供了依赖这一识别方程的识别条件。为了估算目的,我们假设回归函数遵循一个参数模型。我们建议了一个估算程序,并给出了使估计者处于同样正常状态的条件。估计者在模拟中展示了良好的有限样本属性。我们采用的方法是为了寻找证据支持燃烧治疗的效果。