Understanding treatment effects in extreme regimes is important for characterizing risks associated with different interventions. This is hindered by the unavailability of counterfactual outcomes and the rarity and difficulty of collecting extreme data in practice. To address this issue, we propose a new framework based on extreme value theory for estimating treatment effects in extreme regimes. We quantify these effects using variations in tail decay rates of potential outcomes in the presence and absence of treatments. We establish algorithms for calculating these quantities and develop related theoretical results. We demonstrate the efficacy of our approach on various standard synthetic and semi-synthetic datasets.

翻译：理解极端机制下的处理效应对于刻画不同干预措施相关风险至关重要。然而，反事实结果的不可得性以及极端数据在实践中收集的罕见性与困难性阻碍了相关研究。为解决这一问题，我们提出一种基于极值理论的新框架，用于估计极端机制下的处理效应。我们通过量化处理存在与不存在时潜在结果尾部衰减率的变化来表征这些效应。我们建立了计算这些量的算法，并发展了相关的理论结果。我们在多种标准合成与半合成数据集上验证了所提方法的有效性。