We propose dual regression as an alternative to the quantile regression process for the global estimation of … quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile … regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional …

The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2005) is a popular tool for … conventional quantile regression sub-problems which are convex and can be solved efficiently. This reformulation leads to new …

A new quantile regression model for survival data is proposed that permits a positive proportion of subjects to become … proposals for quantile regression estimation of censored survival models, we propose a new "data augmentation" approach to …

Using quantile regression methods, this paper analyses the gender wage gap across the wage distribution and over time …

Using quantile regression methods, this paper analyses the gender wage gap across the wage distribution and over time …

network quantile regression. Building on the estimation results we model systemic risk spillover effects across banks by … considering the marginal effects of the quantile regression procedure. We adopt a dropout regularization procedure to remedy the …

utilising tail event information. FRM (Financial Risk Meter) is based on Lasso quantile regression designed to capture tail …