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Semiparametric estimation of quantile treatment effects with endogeneity

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  • Kaspar W thrich

Abstract

This paper studies estimation of conditional and unconditional quantile treatment effects based on the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2004, 2005, 2006). I introduce a class of semiparametric plug-in estimators based on closed form solutions derived from the IVQR moment conditions. These estimators do not rely on separability of the structural quantile function, while retaining computational tractability and root-n-consistency. Functional central limit theorems and bootstrap validity results for the estimators of the quantile treatment effects and other functionals are provided. I apply my method to reanalyze the effect of 401(k) plans on individual savings behavior.

Suggested Citation

  • Kaspar W thrich, 2015. "Semiparametric estimation of quantile treatment effects with endogeneity," Diskussionsschriften dp1509, Universitaet Bern, Departement Volkswirtschaft.
    • Handle: RePEc:ube:dpvwib:dp1509
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    References listed on IDEAS

    as
    1. Kaspar Wüthrich, 2020. "A Comparison of Two Quantile Models With Endogeneity," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 443-456, April.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    instrumental variables; quantile treatment effects; distribution regression; functional central limit theorem; Hadamard differentiability; exchangeable bootstrap;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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