论文标题
极端连续的治疗效果：措施，估计和推断
Extreme Continuous Treatment Effects: Measures, Estimation and Inference
论文作者
论文摘要
本文涉及对对应于连续价值治疗的不可观察的潜在结果的反事实分布的估计和对治疗效果的推断。我们考虑了深尾特征的两种措施：极端分位数和尾巴平均函数定义为有条件均值的均值。然后，我们定义了极端分元治疗效果（EQTE）和极高平均治疗效果（EATE），可以通过通常采用的不满足条件来识别，并借助极值理论估算。我们的局限性理论是针对一组分位数索引的EQTE和食用过程，因此有助于统一的推断。模拟表明，我们的方法在有限样本中很好地工作，并且经验应用说明了其实际优点。
This paper concerns estimation and inference for treatment effects in deep tails of the counterfactual distribution of unobservable potential outcomes corresponding to a continuously valued treatment. We consider two measures for the deep tail characteristics: the extreme quantile function and the tail mean function defined as the conditional mean beyond a quantile level. Then we define the extreme quantile treatment effect (EQTE) and the extreme average treatment effect (EATE), which can be identified through the commonly adopted unconfoundedness condition and estimated with the aid of extreme value theory. Our limiting theory is for the EQTE and EATE processes indexed by a set of quantile levels and hence facilitates uniform inference. Simulations suggest that our method works well in finite samples and an empirical application illustrates its practical merit.
