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首页> 外文期刊>Evaluation review >Understanding the Impact of Career Academy Attendance: An Application of the Principal Stratification Framework for Causal Effects Accounting for Partial Compliance
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Understanding the Impact of Career Academy Attendance: An Application of the Principal Stratification Framework for Causal Effects Accounting for Partial Compliance

机译:了解职业学院出勤的影响:因果合规的主要分层框架对部分合规性会计的应用

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摘要

Background: Results from MDRC's longitudinal, random-assignment evaluation of career-academy high schools reveal that several years after high-school completion, those randomized to receive the academy opportunity realized a $ 175 (11 %) increase in monthly earnings, on average. Objectives: In this paper, I investigate the impact of duration of actual academy enrollment, as nearly half of treatment group students either never enrolled or participated for only a portion of high school. Research Design: I capitalize on data from this experimental evaluation and utilize a principal stratification framework and Bayesian inference to investigate the causal impact of academy participation. Subjects: This analysis focuses on a sample of 1,306 students across seven sites in the MDRC evaluation. Measures: Participation is measured by number of years of academy enrollment, and the outcome of interest is average monthly earnings in the period of four to eight years after high school graduation. Results: I estimate an average causal effect of treatment assignment on subsequent monthly earnings of approximately $588 among males who remained enrolled in an academy throughout high school and more modest impacts among those who participated only partially. Conclusions: Different from an instrumental variables approach to treatment non-compliance, which allows for the estimation of linear returns to treatment take-up, the more general framework of principal stratification allows for the consideration of non-linear returns, although at the expense of additional model-based assumptions.
机译:背景:MDRC对职业学校高中进行的纵向随机分配评估结果显示,在高中毕业后的几年内,那些随机获得该大学机会的人平均每月收入增加了175美元(11%)。目标:在本文中,我调查了实际入学时间的影响,因为将近一半的治疗组学生从未入学或仅参加了一部分高中。研究设计:我利用这次实验评估中的数据,并利用主要的分层框架和贝叶斯推理来研究学院参与的因果关系。主题:本分析着重于MDRC评估中七个站点的1,306名学生的样本。衡量标准:参与程度是根据入学年限来衡量的,感兴趣的结果是高中毕业后四到八年的平均月收入。结果:我估计,在整个高中期间仍就读于一所学院的男性中,治疗分配对随后每月收入的平均因果影响约为588美元,而对仅部分参与的男性影响较小。结论:不同于用于治疗不依从的工具变量方法,该方法允许估计接受治疗的线性收益,而更主要的主分层框架则考虑了非线性收益,尽管以其他基于模型的假设。

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