Hiroaki Kaido, Kaspar Wuthrich
arXiv 28 Dec 2018 · Econometrics · publishedQuantitative Economics (2021) · 17 citations (OpenAlex)
arXiv:1812.10925 · PDF · DOI · OpenAlex · Extracted main text
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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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chernozhukov and Hansen (2005) An IV Model of Quantile Treatment Effects | 1.000 | 6 | 3 | 100% |
| 2 | Chernozhukov and Hansen (2006) Instrumental quantile regression inference for structural and treatment effects models | 0.937 | 17 | 8 | 82% |
| 3 | Chernozhukov and Hansen (2004) The Effects of 401(k) Participation on the Wealth Distribution: An Instrumental Quantile Regression Analysis | 0.874 | 8 | 2 | 100% |
| 4 | Andrews and Mikusheva (2016) Conditional Inference With a Functional Nuisance Parameter | 0.737 | 4 | 3 | 50% |
| 5 | Chernozhukov and Hansen (2013) Quantile Models with Endogeneity | 0.737 | 3 | 2 | 100% |
| 6 | Chernozhukov, Hansen, and Wüthrich (2017) Instrumental Variable Quantile Regression | 0.737 | 3 | 2 | 100% |
| 7 | Koenker (2017) Computational Methods for Quantile Regression | 0.737 | 3 | 2 | 100% |
| 8 | Dominitz and Sherman (2005) Some convergence theory for iterative estimation procedures with an application to semiparametric estimation | 0.659 | 7 | 2 | 43% |
| 9 | R Core Team (2019) R: A Language and Environment for Statistical Computing | 0.644 | 4 | 1 | 100% |
| 10 | Kaplan and Sun (2017) Smoothed Estimation Equations for Instrumental Variables Quantile Regression | 0.644 | 2 | 2 | 100% |
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