Regression discontinuity design with multivalued treatments
研究了多值处理变量下断点回归设计的识别与估计问题，提出利用第一阶段断点异质性识别边际处理效应，并应用于评估医疗保险对医疗利用的影响。
Summary We study identification and estimation in the regression discontinuity design with a multivalued treatment. We show that heterogeneity in the first stage discontinuities can be used for the identification of the marginal treatment effects under an alternative assumption, namely, the homogeneity of the LATEs along some covariates. This assumption can often be tested and relaxed. Our estimator can be programmed as a simple two‐stage least squares regression, and packaged standard errors and tests can also be used. We apply our method to estimate the effect of Medicare insurance coverage on health care utilization.