overestimation, ranging from 8.3% to 89.5%. According to the quantile regression results, the level of wage penalties for over …

improvements. Using both panel estimation and quantile regression methods on household travel diary data collected in Germany … Vance (2008), but are substantially larger than those obtained from other studies. Furthermore, our quantile regression …

Composite quantile regression with randomly censored data is studied. Moreover, adaptive LASSO methods for composite … quantile regression with randomly censored data are proposed. The consistency, asymptotic normality and oracle property of the …

quantile regression, is consistent in variable selection. In particular, due to the recent interest in penalized likelihood for …-penalized estimator. Although similar results have been proved for linear regression, the results obtained here are new for quantile … regression, which imposes extra technical difficulties compared to mean regression, since no closed-form solution exists. …

by estimating growth regressions, using the novel semiparametric smooth coefficient quantile regression method in which …

–2004 across the entire wage distribution. Quantile regression analysis reveals that the effects of many covariates are not … quantile regression decomposition suggests that the increase in returns has been the driving force behind the increase in wages …

sources to construct a new micro-dataset for an emerging Chinese city, Changsha, and it incorporates quantile regression with …