  The practical importance of inference with robustness against large
bandwidths for causal effects in regression discontinuity and kink designs is
widely recognized. Existing robust methods cover many cases, but do not handle
uniform inference for CDF and quantile processes in fuzzy designs, despite its
use in the recent literature in empirical microeconomics. In this light, this
paper extends the literature by developing a unified framework of inference
with robustness against large bandwidths that applies to uniform inference for
quantile treatment effects in fuzzy designs, as well as all the other cases of
sharp/fuzzy mean/quantile regression discontinuity/kink designs. We present
Monte Carlo simulation studies and an empirical application for evaluations of
the Oklahoma pre-K program.
