A Correction for Regression Discontinuity Designs With Group-Specific Mismeasurement of the Running Variable
A Correction for Regression Discontinuity Designs With Group-Specific Mismeasurement of the Running Variable
复制标题
具有特定组运行变量误测的回归不连续性设计的修正
DOI：
10.1080/07350015.2020.1737081
复制
发表时间：
2020
影响因子：
3
通讯作者：
S. Dieterle
中科院分区：
文献类型：
--
作者：
Otávio Bartalotti;Quentin Brummet;S. Dieterle
摘要当回归不连续性设计中的运行变量被测量时，局部平均处理效应的识别通常会失败。虽然这种测量误差的形式在不同的应用中有所不同，但在许多情况下，测量误差结构在不同的观测组中是异构的。我们开发了一种新的测量误差校正程序，能够解决异构误测量结构，利用辅助信息。我们还提供了调整后的渐近方差和标准误差，考虑到由滋扰参数估计引入的变异性，以及诚实的置信区间，考虑到潜在的误指定。模拟提供的证据表明，所提出的程序纠正了异质测量误差引入的偏差，并实现了比“天真”替代方案更接近名义测试大小的经验覆盖率。两个实证例证表明，修正测量误差既可以加强研究结果，也可以为数据提供新的实证视角。
Abstract When the running variable in a regression discontinuity (RD) design is measured with error, identification of the local average treatment effect of interest will typically fail. While the form of this measurement error varies across applications, in many cases the measurement error structure is heterogeneous across different groups of observations. We develop a novel measurement error correction procedure capable of addressing heterogeneous mismeasurement structures by leveraging auxiliary information. We also provide adjusted asymptotic variance and standard errors that take into consideration the variability introduced by the estimation of nuisance parameters, and honest confidence intervals that account for potential misspecification. Simulations provide evidence that the proposed procedure corrects the bias introduced by heterogeneous measurement error and achieves empirical coverage closer to nominal test size than “naive” alternatives. Two empirical illustrations demonstrate that correcting for measurement error can either reinforce the results of a study or provide a new empirical perspective on the data.