Isotonic Regression Discontinuity Designs
Isotonic Regression Discontinuity Designs
复制标题
等渗回归不连续性设计
DOI：
10.2139/ssrn.3458127
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Rohit Kumar
中科院分区：
文献类型：
--
作者：
Andrii Babii;Rohit Kumar
在保序回归不连续性设计中，平均结果和治疗分配概率在运行变量中是单调的。我们介绍了新的非参数估计尖锐和模糊设计的基础上的带宽自由保序回归。引入的估计量的大样本分布是由布朗运动驱动的，从零开始，向相反的方向移动。由于这些分布是不关键的，我们还介绍了一种新的修剪野生自助程序，这是免费的非参数平滑，通常需要在这样的设置，并显示其一致性。我们在Lee（2008）的著名数据集上说明了我们的方法，估计了美国众议院选举中的在职效应。
In isotonic regression discontinuity designs, the average outcome and the treatment assignment probability are monotone in the running variable. We introduce novel nonparametric estimators for sharp and fuzzy designs based on the bandwidth-free isotonic regression. The large sample distributions of introduced estimators are driven by Brownian motions originating from zero and moving in opposite directions. Since these distributions are not pivotal, we also introduce a novel trimmed wild bootstrap procedure, which is free from nonparametric smoothing, typically needed in such settings, and show its consistency. We illustrate our approach on the well-known dataset of Lee (2008), estimating the incumbency effect in the U.S. House elections.