Decentralization estimators for instrumental variable quantile regression models

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: cemmap working paper ; No. CWP42/19

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
• Subject: instrumental variables ; quantile regression ; contraction mapping ; fixed pointestimator ; bootstrap

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kaido, Hiroaki ; Wüthrich, Kaspar
• Event: Veröffentlichung
• (who): Centre for Microdata Methods and Practice (cemmap)
• (where): London
• (when): 2019

Further information

• DOI: doi:10.1920/wp.cem.2019.4219
• Handle: http://hdl.handle.net/10419/211135
• Last update: 10.03.2025, 11:43 AM CET