边界断点设计中的操纵检验

中文摘要 AI 辅助

我们提出了首个适用于具有一般边界形状的边界断点设计（BDD）的操纵检验方法。BDD是回归断点设计（RDD）的多维扩展，其中处理分配由多维运行变量是否穿过低维边界集决定。该检验避免了多元密度估计，基于以下观察：在无操纵的情况下，边界附近的观测值在其投影到边界所定义的任意组中应大致平均分配到处理组和控制组。我们使用一组针对边界附近观测值的二项式平衡检验来验证这一含义，组由k-means聚类形成。我们在适当的正则条件下证明了该检验的渐近有效性，还通过蒙特卡洛模拟评估了有限样本性能，并在三个实证应用中展示了该检验的效果。

英文摘要

We propose the first manipulation test designed for boundary discontinuity designs (BDDs) with general boundary shapes. A BDD is a multidimensional extension of the regression discontinuity design (RDD) in which treatment assignment is determined by whether the multidimensional running variable crosses a lower-dimensional boundary set. The test avoids multivariate density estimation and builds on the observation that, in the absence of manipulation, observations near the boundary should be approximately evenly split between treatment and control within arbitrary groups defined by their projections onto the boundary. We test this implication using a collection of binomial balance tests on observations near the boundary, with groups formed by k-means clustering. We establish the asymptotic validity of the test under suitable regularity conditions. We also evaluate finite-sample performance through Monte Carlo simulations and illustrate the test in three empirical applications.

发表机构

• Northwestern University（西北大学）
• University of California, Berkeley（加州大学伯克利分校）
• University of Minnesota（明尼苏达大学）

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