We consider estimation of the causal effect of a binary treatment on an outcome, conditionally on covariates, from observational studies or natural experiments in which there is a binary instrument for treatment. We describe a doubly robust, locally efficient estimator of the parameters indexing a model for the local average treatment effect conditionally on covariates V when randomization of the instrument is only true conditionally on a high dimensional vector of covariates X, possibly bigger than V. We discuss the surprising result that inference is identical to inference for the parameters of a model for an additive treatment effect on the treated conditionally on V that assumes no treatment-instrument interaction. We illustrate our methods with the estimation of the local average effect of participating in 401(k) retirement programs on savings by using data from the US Census Bureau's 1991 Survey of Income and Program Participation.

中文翻译：

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对局部平均治疗效果曲线的双稳健估计。

我们考虑从观察性研究或自然实验（其中存在用于治疗的二元工具）来评估二元治疗对结局的因果效应（有条件地针对协变量）。当仪器随机化仅在协变量X的高维矢量（可能大于V）上有条件地满足时，我们描述了参数的双稳健，局部高效估计量，该参数索引了模型对条件下对协变量V的局部平均处理效果的模型。令人惊讶的结果是，推论与模型参数有关的推论完全相同，该模型参数假定在不存在任何治疗仪器相互作用的情况下，对有条件地治疗V的累加治疗效果。