Title: Direction estimation in single-index quantile regressions via martingale difference divergence
Authors: Jicai Liu - Shanghai Normal University (China) [presenting]
Abstract: A novel estimation method based on the martingale difference divergence in single index quantile models is proposed. Our approach does not require any nonparametric estimation and enjoys a model free property. Under regularity conditions, we show that our estimator is root-n consistent and asymptotically normal. We compare the performance of our method with the single index estimation method by simulations and show that our method is very competitive and robust across a number of models. Finally, we analyze a real data set to demonstrate the efficacy of our method.