The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2005) is a popular tool for …-convexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of … conventional quantile regression sub-problems which are convex and can be solved efficiently. This reformulation leads to new …

This paper provides sufficient conditions for the nonparametric identification of the regression function m(.) in a … regression model with an endogenous regressor x and an instrumental variable z. It has been shown that the identification of the … regression function from the conditional expectation of the dependent variable on the instrument relies on the completeness of …

delta method, and (3) provide results for sparsity-based estimation of regression functions for function-valued outcomes. …

special case and also covers a wide variety of classical and modern moment-condition problems in econometrics. We establish a …) regression functions, also providing practical, theoretically justified penalty choices. Each of these results is new and could …

. 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 …