Artikel
Decentralization estimators for instrumental variable quantile regression models
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.
- Sprache
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Englisch
- Erschienen in
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Journal: Quantitative Economics ; ISSN: 1759-7331 ; Volume: 12 ; Year: 2021 ; Issue: 2 ; Pages: 443-475 ; New Haven, CT: The Econometric Society
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation
contraction mapping
fixed-point estimator
Instrumental variables
quantile regression
Wüthrich, Kaspar
- DOI
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doi:10.3982/QE1440
- Handle
- Letzte Aktualisierung
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20.09.2024, 08:24 MESZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Kaido, Hiroaki
- Wüthrich, Kaspar
- The Econometric Society
Entstanden
- 2021