We develop a distribution regression model under endogenous sample selection. This model is a semiparametric … probit regression for the selection equation and the second step consists of multiple distribution regressions with selection …

We develop a distribution regression model under endogenous sample selection. This model is a semi …

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for … rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions. …

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for … rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions. …

. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment … or policy variable) in a high-dimensional approximately sparse regression model, for average treatment effect (ATE) and … heteroscedastic and non-Gaussian errors are implemented. Moreover, joint/ simultaneous confidence intervals for regression …

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The … impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR …-series framework, covering many regressors as a special case, for performing inference on the entire conditional quantile function and …

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for … rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions. …