We provide novel methods for inference on quantile treatment effects in both uncon- ditional and conditional (nonparametric) settings. These methods achieve high-order accuracy by using the probability integral transform and a Dirichlet (rather than Gaus- sian) reference distribution. We propose...

We propose a nonparametric method to construct confidence intervals for quantile marginal effects (i.e., derivatives of the conditional quantile function). Under certain conditions, a quantile marginal effect equals a causal (structural) effect in a general nonseparable model, or equals an...