Weighted-Average Quantile Regression

In this paper, we introduce the weighted-average quantile regression model. We argue that this model is of interest in many applied settings and develop an estimator for parameters of this model. We show that our estimator is √T-consistent and asymptotically normal with mean zero under weak conditions, where T is the sample size. We demonstrate the usefulness of our estimator in two empirical settings. First, we study the factor structures of the expected shortfalls of the industry portfolios. Second, we study inequality and social welfare dependence on individual characteristics.