标题： 对误分类处理的局部平均处理效应的推断 显示英文标题

标题： Inference on Local Average Treatment Effects for Misclassified Treatment

摘要： 我们为局部平均处理效应开发了点识别，当二元处理变量包含测量误差时。 标准的工具变量估计量对于该参数是不一致的，因为根据构造，测量误差是非经典的。 我们通过基于使用一个外生变量来识别测量误差的分布来纠正这个问题，该变量甚至可以是一个二元协变量。 从识别中得出的矩条件导致了广义矩估计方法，并具有渐近有效的推断。 蒙特卡洛模拟和一个实证例子证明了所提出程序的实用性。 显示英文摘要

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.