A Bayesian Semiparametric Method For Estimating Causal Quantile Effects. (arXiv:2211.01591v1 [stat.ME])

Standard causal inference characterizes treatment effect through averages,
but the counterfactual distributions could be different in not only the central
tendency but also spread and shape. To provide a comprehensive evaluation of
treatment effects, we focus on estimating quantile treatment effects (QTEs).
Existing methods that invert a nonsmooth estimator of the cumulative
distribution functions forbid inference on probability density functions
(PDFs), but PDFs can reveal more nuanced characteristics of the counterfactual
distributions. We adopt a semiparametric conditional distribution regression
model …

arxiv bayesian effects quantile