This paper develops a sensitivity analysis of the surrogacy assumption for the surrogate index approach in Athey et al. [2025b]. We introduce "Weighted Surrogate Indices (WSIs)," the analog of the surrogate index under the surrogacy assumption. We show that under comparability, the ATE on WSI identifies the ATE on the long-term outcome when a copula of the treatment and the long-term outcome conditional on baseline covariates and surrogates is known. When the copula is unknown, we establish the identified set of the ATE on the long-term outcome. Furthermore, we construct debiased estimators of the ATE for any given copula and develop asymptotically valid inference in both point-identified and partially identified cases. Using data from a poverty alleviation program in Pakistan, we demonstrate the importance of sensitivity checks as well as the usefulness of our approach.
Exact Trend Control in Estimating Treatment Effects Using Panel Data with Heterogenous Trends
对于Abadie等人（2010）考虑的面板模型，Abadie等人构建的反事实结果，Hsiao et al.（2012）和Doudchenko and Imbens（2017）都可能受到不受控制的异质性趋势的混淆。基于精确匹配的趋势预测，我提出了新的方法来估计模型特定的处理效应，这是免费的异质性趋势。当应用于Abadie et al.新的估计表明，加州烟草控制计划的影响要小得多。
Statistical Power for Estimating Treatment Effects Using Difference-in-Differences and Comparative Interrupted Time Series Designs with Variation in Treatment Timing
The University of Hong Kong（香港大学）；University of California, Davis（加州大学戴维斯分校）；Boston University, Questrom School of Business（波士顿大学奎斯特伦商学院）；Tencent, Inc.（腾讯公司）
