Instrumental Variables Estimation of Quantile Treatment Effects

31 Pages Posted: 15 Sep 2000 Last revised: 19 Aug 2010

See all articles by Alberto Abadie

Alberto Abadie

Harvard University - Harvard Kennedy School (HKS); National Bureau of Economic Research (NBER)

Joshua D. Angrist

Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

Guido W. Imbens

Stanford Graduate School of Business

Date Written: March 1998

Abstract

This paper introduces an instrumental variables estimator for the effect of a binary treatment on the quantiles of potential outcomes. The quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile regression as a special case when treatment status is exogenous. Asymptotic distribution theory and computational methods are derived. QTE minimizes a piecewise linear objective function for which a local minimum can be obtained using a modified Barrodale-Roberts algorithm. The QTE estimator is illustrated by estimating the effect of childbearing on the distribution of family income.

Suggested Citation

Abadie, Alberto and Angrist, Joshua and Imbens, Guido W., Instrumental Variables Estimation of Quantile Treatment Effects (March 1998). NBER Working Paper No. t0229. Available at SSRN: https://ssrn.com/abstract=226639

Alberto Abadie (Contact Author)

Harvard University - Harvard Kennedy School (HKS) ( email )

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Joshua Angrist

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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National Bureau of Economic Research (NBER)

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IZA Institute of Labor Economics

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Guido W. Imbens

Stanford Graduate School of Business ( email )

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Stanford, CA 94305-5015
United States

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