This paper considers estimation and inference for varying-coefficient models with nonstationary regressors. We propose a nonparametric estimation method using penalized splines, which achieves the same optimal convergence rate as kernel-based methods, but enjoys computation advantages. Utilizing...

The choice of a smoothing parameter or bandwidth is crucial when applying nonparametric regression estimators. In nonparametric mean regression various methods for bandwidth selection exists. But in nonparametric quantile regression bandwidth choice is still an unsolved problem. In this paper a...