连接局部与总体因果效应：一种近端工具变量方法
Bridging Local and Population Causal Effects: A Proximal Instrumental Variable Approach
- Department of Statistics and Actuarial Science（统计与精算学系）
- University of Hong Kong（香港大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对工具变量仅能识别局部平均处理效应的问题，提出近端工具变量框架，利用代理变量调整依从加权，结合双重稳健表示恢复总体平均处理效应，并给出有效估计与理论保证。
AI中文摘要：
工具变量（IV）方法解决了治疗内生性问题，但在不依从和异质性治疗效应存在的情况下，二元工具通常识别的是依从者中的局部平均治疗效应（LATE），而非总体平均治疗效应（ATE）。当治疗效应和依从概率通过潜在因子异质且相互依赖时，仅靠IV变异不一定能识别ATE。我们开发了一个近端工具变量框架，利用这些因子的代理变量来调整LATE中的依从加权，从而恢复ATE。我们证明，ATE可以通过捕捉潜在治疗效应异质性的结果桥或表示逆依从概率的依从桥来识别，将两者结合可得到双重稳健表示。我们在已知和未知工具倾向得分下推导了有效影响函数。在估计方面，我们提出了正则化核极小极大桥估计器，对估计的倾向得分使用正交化条件矩，并采用三向序贯交叉拟合方案。我们建立了投影桥风险界，并给出了渐近正态性和半参数有效性的条件。该框架提供了一条基于代理的路径，从局部IV效应到潜在治疗效应和依从异质性下的总体因果效应。
英文摘要：
Instrumental variable (IV) methods address treatment endogeneity, but with non-compliance and heterogeneous treatment effects a binary instrument generally identifies the local average treatment effect (LATE) among compliers rather than the population average treatment effect (ATE). When treatment effects and compliance probabilities are heterogeneous and dependent through latent factors, the ATE need not be identified by IV variation alone. We develop a proximal instrumental variable framework that uses proxies for these factors to adjust for the compliance weighting in LATE and recover the ATE. We show that the ATE is identified through either an outcome bridge capturing latent treatment effect heterogeneity or a compliance bridge representing inverse compliance probabilities, and combining the two yields a doubly robust representation. We derive the efficient influence function under known and unknown instrument propensities. For estimation, we propose regularized kernel minimax bridge estimators, with orthogonalized conditional moments for estimated propensity, and a three-way sequential cross-fitting scheme. We establish projected bridge-risk bounds, and give conditions for asymptotic normality and semiparametric efficiency. The framework provides a proxy-based route from local IV effects to population causal effects under latent treatment effect and compliance heterogeneity.
