论文标题
使用协变量的复杂不连续设计：保留学校等级对智利以后生活成果的影响
Complex Discontinuity Designs Using Covariates: Impact of School Grade Retention on Later Life Outcomes in Chile
论文作者
论文摘要
回归不连续设计广泛用于观察研究中的因果推断。但是，它们通常仅限于具有简单处理规则的设置，该设置由单个运行变量确定，并带有单个截止。由于估计保留率对智利教育和青少年犯罪成果的影响的问题，我们提出了一种框架和方法，用于涵盖多个治疗规则的复杂性不连续设计。在此框架中，观察到的协变量在因果效应的识别，估计和概括中起着核心作用。识别是非参数，并且依赖于局部强的无知性假设。估计在强大的无知性下的任何观察性研究中都进行，但在运行变量的截止范围内。我们讨论基于匹配和加权的估计方法，包括互补的回归建模调整。我们提出了概括的假设；也就是说，用于识别和估计目标人群的平均治疗效果。我们还描述了选择邻居进行分析的两种方法。我们发现，智利的年级保留对未来年级的保留有负面影响，但与辍学或犯罪犯罪无关。
Regression discontinuity designs are extensively used for causal inference in observational studies. However, they are usually confined to settings with simple treatment rules, determined by a single running variable, with a single cutoff. Motivated by the problem of estimating the impact of grade retention on educational and juvenile crime outcomes in Chile, we propose a framework and methods for complex discontinuity designs that encompasses multiple treatment rules. In this framework, the observed covariates play a central role for identification, estimation, and generalization of causal effects. Identification is non-parametric and relies on a local strong ignorability assumption. Estimation proceeds as in any observational study under strong ignorability, yet in a neighborhood of the cutoffs of the running variables. We discuss estimation approaches based on matching and weighting, including complementary regression modeling adjustments. We present assumptions for generalization; that is, for identification and estimation of average treatment effects for target populations. We also describe two approaches to select the neighborhood for analysis. We find that grade retention in Chile has a negative impact on future grade retention, but is not associated with dropping out of school or committing a juvenile crime.
