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The practical importance of inference with robustness against largebandwidths for causal effects in regression discontinuity and kink designs iswidely recognized. Existing robust methods cover many cases, but do not handleuniform inference for CDF and quantile processes in fuzzy designs, despite itsuse in the recent literature in empirical microeconomics. In this light, thispaper extends the literature by developing a unified framework of inferencewith robustness against large bandwidths that applies to uniform inference forquantile treatment effects in fuzzy designs, as well as all the other cases ofsharp/fuzzy mean/quantile regression discontinuity/kink designs. We presentMonte Carlo simulation studies and an empirical application for evaluations ofthe Oklahoma pre-K program.

Robust Uniform Inference for Quantile Treatment Effects in Regression Discontinuity Designs