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Small sample inference for regression quantiles

Publication

Abstract

New test which can be used to make inference in regression quantiles models is derived. It is extremely accurate even in moderate to small samples and is nonparametric in that it does not rely on underlying distributional assumptions for the errors.

Its theoretical properties are presented and its behavior is compared by Monte Carlo simulation with standard asymptotic procedures under several distributional assumptions for the errors.