A Note on Covariance Matrix Estimation in Quantile Regressions

This note discusses some issues related to bandwidth selection based on moment expansions of the mean squared error (MSE) of the regression quantile estimator. We use higher order expansions to provide a way to distinguish among asymptotically equivalent nonparametric estimators. We derive approximations to the (standardized) MSE of the covariance matrix estimation. This facilitates a comparison of different estimators at the second order level, where differences do occur and depend on the bandwidth choice. A method of bandwidth selection is defined by minimizing the second order effect in the mean squared error.