A Location-Invariant Estimator of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions

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On September 7, 2026, arXiv cs.LG published a paper titled “A Location-Invariant Estimator of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions”. This study proposed a location-invariant estimator for extremal quantile treatment effects in heavy-tailed distributions, aiming to address the challenges faced by traditional methods when dealing with such data.

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A arXiv cs.LG en 2026-09-07 12:00

本文提出了一种针对重尾分布的极值分位数处理效应（QTE）位置不变估计器。现有极端 QTE 估计器虽依赖因果极值指数（EVI）外推，但在潜在结果分布发生共同位置偏移时缺乏位置不变性。作者首先利用逆倾向得分加权将位置不变的 Fraga EVI 估计器适配至因果设定，随后用基于差分的方案替代原外推公式以消除位置参数影响。研究建立了所提极端 QTE 估计器的一致性与渐近正态性，并提供了渐近有效推断的方差估计器；模拟研究证实了该方法的位置不变性、阈值稳定性及覆盖率。