On Recoding Ordered Treatments as Binary Indicators
研究了研究者将有序处理变量重新编码为是否接受任何处理的二元指标时，在特定假设下该估计量的含义，并应用于俄勒冈健康保险实验分析处理异质性。
Abstract Researchers using instrumental variables to investigate ordered treatments often recode treatment into an indicator for any exposure. We investigate this estimand under the assumption that the instruments shift compliers from no treatment to some but not from some treatment to more. We show that when there are extensive margin compliers only (EMCO) this estimand captures a weighted average of treatment effects that can be partially unbundled into each complier group's potential outcome means. We also establish an equivalence between EMCO and a two-factor selection model and apply our results to study treatment heterogeneity in the Oregon Health Insurance Experiment.