Two-Stage Quantile Regression When the First Stage is Based on Quantile Regression

Abstract

We present the asymptotic properties of double-stage quantile regression estimators with random regressors, where the first stage is based on quantile regressions with the same quantile as in the second stage, which ensures robustness of the estimation procedure. We derive invariance properties with respect to the reformulation of the dependent variable. We propose a consistent estimator of the variance-covariance matrix of the new estimator. Finally, we investigate finite sample properties of this estimator by using Monte Carlo simulations.

Keywords: Two-stage estimation, Quantile regression, Endogeneity