摘要翻译：
当二值化处理包含测量误差时，我们对局部平均处理效应进行了点辨识。由于测量误差是结构上的非经典误差，标准的工具变量估计器对参数不一致。我们通过使用外生变量甚至可以是二元协变量来识别测量误差的分布来纠正这个问题。由辨识得到的矩条件导致广义矩估计方法具有渐近有效的推论。蒙特卡罗模拟和一个经验例子证明了所提出的程序的有效性。
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英文标题：
《Inference on Local Average Treatment Effects for Misclassified Treatment》
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作者：
Takahide Yanagi
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最新提交年份：
2018
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  We develop point-identification for the local average treatment effect when the binary treatment contains a measurement error. The standard instrumental variable estimator is inconsistent for the parameter since the measurement error is non-classical by construction. We correct the problem by identifying the distribution of the measurement error based on the use of an exogenous variable that can even be a binary covariate. The moment conditions derived from the identification lead to generalized method of moments estimation with asymptotically valid inferences. Monte Carlo simulations and an empirical illustration demonstrate the usefulness of the proposed procedure.
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PDF链接：
https://arxiv.org/pdf/1804.03349