Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper studies the estimation of quantile treatment effects based on the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2005). I develop a class of flexible plug-in estimators based on closed-form solutions derived from the IVQR moment conditions. The proposed estimators remain tractable and root-n-consistent, while allowing for rich patterns of effect heterogeneity. Functional central limit theorems and bootstrap validity results for the estimators of the quantile treatment effects and other functionals are provided. Monte Carlo simulations demonstrate favorable finite sample properties of the proposed approach. I apply my method to reanalyze the causal effect of 401(k) plans.