Individual Treatment Effects in Extreme Regimes
Ahmed Aloui Ali Hasan Yuting Ng Miroslav Pajic Vahid Tarokh
Understanding individual treatment effects in extreme regimes is important
for characterizing risks associated with different interventions. This is
hindered by the fact that extreme regime data may be hard to collect, as it is
scarcely observed in practice. In addressing this issue, we propose a new
framework for estimating the individual treatment effect in extreme regimes
(ITE$_2$). Specifically, we quantify this effect by the changes in the tail
decay rates of potential outcomes in the presence or absence of the treatment.
Subsequently, we establish conditions under which ITE$_2$ may be calculated and
develop algorithms for its computation. We demonstrate the efficacy of our
proposed method on various synthetic and semi-synthetic datasets.