甜甜圈和遥远的CATEs: RD外推的导数界

Connor Dowd
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引用次数: 4

摘要

回归不连续(RD)使用策略阈值来识别阈值处的因果处理效果。在大多数情况下,阈值处的局部平均处理效果(LATE)不是感兴趣的参数。我提供了高水平的平滑条件,在这种条件下,可以通过阈值进行外推。在这些限制下,对其他位置的LATE进行估计和推断是可能的。在某些情况下,可能需要外推法来估计阈值处的LATE。RD甜甜圈就是这样一种情况,我提供的结果也允许在这种情况下进行估计和推断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Donuts and Distant CATEs: Derivative Bounds for RD Extrapolation
Regression Discontinuity (RD) uses policy thresholds to identify causal treatment effects at the threshold. In most settings, the Local Average Treatment Effect (LATE) at the threshold is not the parameter of interest. I provide high level smoothness conditions under which extrapolation across the threshold is possible. Under these restrictions, both estimation and inference for the LATE in other locations is possible. In some situations, extrapolation may be necessary to merely estimate the LATE at the threshold. RD donuts are one such situation, and I provide results allowing estimation and inference in that setting as well.
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