Asymptotic expansions are developed for Wald test statistics in cointegrating regression models. These expansions provide an opportunity to reduce size distortion in testing by suitable bandwidth selection, and automated rules for doing so are calculated. Band spectral regression methods and...

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...

In this paper we study risk management based on the quantile regression. Unlike the traditional VaR estimation methods, the quantile regression approach allows for a general treatment on the error distribution and is robust to distributions with heavy tails. We estimate the VaRs of five...

We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum...