摘要翻译：
本研究提出了一种在不依从性随机实验中不受排除限制识别治疗效果的方法。利用随机实验中常见的基线调查，我分解了内源性治疗状态条件下的意图治疗效果。然后我识别这些参数来理解分配和治疗的效果。关键的假设是基线变量保持与控制结果相似的秩序。我还揭示了在变化中变化的策略可能在没有重复结果的情况下工作。最后，我提出了一个新的估计，灵活地纳入协变量，并证明了它的性质通过两个实验研究。
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英文标题：
《Noncompliance in randomized control trials without exclusion
  restrictions》
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作者：
Masayuki Sawada
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最新提交年份：
2021
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
  This study proposes a method to identify treatment effects without exclusion restrictions in randomized experiments with noncompliance. Exploiting a baseline survey commonly available in randomized experiments, I decompose the intention-to-treat effects conditional on the endogenous treatment status. I then identify these parameters to understand the effects of the assignment and treatment. The key assumption is that a baseline variable maintains rank orders similar to the control outcome. I also reveal that the change-in-changes strategy may work without repeated outcomes. Finally, I propose a new estimator that flexibly incorporates covariates and demonstrate its properties using two experimental studies.
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PDF链接：
https://arxiv.org/pdf/1910.03204