Local polynomial regression is widely used for nonparametric regression. However, the efficiency of least squares (LS) based methods is adversely affected by outlying observations and heavy tailed distributions. On the other hand, the least absolute deviation (LAD) estimator is more robust, but...

In this paper, from the estimating equation-based sufficient dimension reduction method in the literature, its robust version is proposed to alleviate the impact from outliers. To achieve this, a robust nonparametric regression estimator is suggested. The estimator is plugged in the estimating...

A comparison of hazard rates of duration outcomes before and after policy changes is hampered by non-identification if there is unobserved heteogeneity in the effects and no model structure is imposed. We develop a discontinuity approach that overcomes this by exploiting variation in the moment...