A Location-Invariant Estimator of Extremal Quantile Treatment Effects for Heavy-Tailed Distributions
重尾分布下位置不变的极端分位数处理效应估计
Quantile treatment effects (QTEs) measure the effect of a treatment on the distribution of an outcome, and their estimation at extreme quantile levels is of central interest in applications where the target quantiles lie far beyond the range of the data. For heavy-tailed potential outcomes, existing extremal QTE estimators rely on extrapolation combined with a causal extreme value index (EVI) estimator, but the resulting estimator is not invariant under a common location…