论文标题
操纵稳定回归不连续性设计
Manipulation-Robust Regression Discontinuity Designs
论文作者
论文摘要
我们使用潜在的结果框架来操纵运行变量的潜在结果框架，介绍了简单的低水平条件，用于在回归不连续设计中识别。使用此框架，我们用对操作的两个限制替换了现有的标识声明。我们的框架突出了运行变量连续密度在识别中的关键作用。特别是，我们建立了诊断密度测试的低水平辅助假设，该假设可以检测到对识别的操纵，因此是操纵的。
We present simple low-level conditions for identification in regression discontinuity designs using a potential outcome framework for the manipulation of the running variable. Using this framework, we replace the existing identification statement with two restrictions on manipulation. Our framework highlights the critical role of the continuous density of the running variable in identification. In particular, we establish the low-level auxiliary assumption of the diagnostic density test under which the design may detect manipulation against identification and hence is manipulation-robust.
