Decentralization Estimators for Instrumental Variable Quantile Regression Models
Econometrics
2021-09-14 v4
Abstract
The instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2005) is a popular tool for estimating causal quantile effects with endogenous covariates. However, estimation is complicated by the non-smoothness and non-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 identification results and to fast, easy to implement, and tuning-free estimators that do not require the availability of high-level "black box" optimization routines.
Keywords
Cite
@article{arxiv.1812.10925,
title = {Decentralization Estimators for Instrumental Variable Quantile Regression Models},
author = {Hiroaki Kaido and Kaspar Wuthrich},
journal= {arXiv preprint arXiv:1812.10925},
year = {2021}
}