We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also...

In this study, we investigate the estimation and inference on a low-dimensional causal parameter in the presence of high-dimensional controls in an instrumental variable quantile regression. Our proposed econometric procedure builds on the Neyman-type orthogonal moment conditions of a previous...

In this study, we estimate the effect of industry distress on recovery rates by using the unconditional quantile regression (UQR) proposed in Firpo, Fortin, and Lemieux (2009). The UQR provides better interpretative and thus policy-relevant information on the marginal effect of the covariates...