Decentralization estimators for instrumental variable quantile regression models

Artikel

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 nonsmoothness and nonconvexity of the IVQR GMM objective function. This paper shows that the IVQR estimation problem can be decomposed into a set of conventional quantile regression subproblems 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: Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 12 ; Year: 2021 ; Issue: 2 ; Pages: 443-475 ; New Haven, CT: The Econometric Society

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: bootstrap ; contraction mapping ; fixed-point estimator ; Instrumental variables ; quantile regression

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Kaido, Hiroaki ; Wüthrich, Kaspar
• Event: Veröffentlichung
• (who): The Econometric Society
• (where): New Haven, CT
• (when): 2021

Further information

• DOI: doi:10.3982/QE1440
• Handle: http://hdl.handle.net/10419/253599
• Last update: 10.03.2025, 11:41 AM CET