论文标题
一种识别治疗效果的计算方法，以进行政策评估
A Computational Approach to Identification of Treatment Effects for Policy Evaluation
论文作者
论文摘要
对于反事实的政策评估，重要的是要确保治疗参数与有关政策有关。在未观察到的异质性下，这尤其具有挑战性，正如局部平均治疗效果的定义（晚期）的定义中所特有的。在本质上是本地的，已知晚期缺乏反事实环境中的外部有效性。本文研究了仪器变量仅二进制时，研究了将局部治疗效果推送到不同反事实环境的可能性。我们提出了一个新颖的框架，以系统地计算各种与策略相关的治疗参数的尖锐非参数界限，这些治疗参数定义为边缘治疗效果（MTE）的加权平均值。我们的框架足够灵活，可以完全纳入工具的统计独立性（而不是平均独立性），并在先前研究中考虑了超出形状限制的大量假设菜单。我们采用我们的方法来了解医疗保险政策对使用医疗服务的影响。
For counterfactual policy evaluation, it is important to ensure that treatment parameters are relevant to policies in question. This is especially challenging under unobserved heterogeneity, as is well featured in the definition of the local average treatment effect (LATE). Being intrinsically local, the LATE is known to lack external validity in counterfactual environments. This paper investigates the possibility of extrapolating local treatment effects to different counterfactual settings when instrumental variables are only binary. We propose a novel framework to systematically calculate sharp nonparametric bounds on various policy-relevant treatment parameters that are defined as weighted averages of the marginal treatment effect (MTE). Our framework is flexible enough to fully incorporate statistical independence (rather than mean independence) of instruments and a large menu of identifying assumptions beyond the shape restrictions on the MTE that have been considered in prior studies. We apply our method to understand the effects of medical insurance policies on the use of medical services.
