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arXiv · 1812.10925

Decentralization Estimators for Instrumental Variable Quantile Regression Models

Hiroaki Kaido·Kaspar Wuthrich
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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.

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BibTeXRIS

Hiroaki Kaido, Kaspar Wuthrich. 2018-12-28. Decentralization Estimators for Instrumental Variable Quantile Regression Models. https://arxiv.org/abs/1812.10925

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