A practical generalized propensity-score estimator for quantile continuous treatment effects. (June 2020)

• Record Type: Journal Article
• Authors: Alejo, Javier; Galvao, Antonio F.; Montes-Rojas, Gabriel
• Is Part Of: Stata journal. Volume 20:Number 2(2020)
• Page Start: 276
• Page End: 296
• Publication Date: 2020-06
• Subjects: st0597 -- qcte -- continuous treatment -- quantile treatment effects -- quantile regression; Statistics -- Periodicals; Statistics -- Computer programs -- Periodicals; 001.422
• DOI: 10.1177/1536867X20930997
• Languages: English
• ISSNs: 1536-867X

Abstract

In this article, we present a new command, qcte, that implements several methods for estimation and inference for quantile treatment-effects models with a continuous treatment. We propose a semiparametric two-step estimator, where the first step is based on a flexible Box–Cox model, as the default model of the command. We develop practical statistical inference procedures using bootstrap. We implement some simulations to show that the proposed methods perform well. Finally, we applyqcte to a survey of Massachusetts lottery winners to estimate the unconditional quantile effects of the prize amount, as a proxy of nonlabor income changes, on subsequent labor earnings from U.S. Social Security records. The empirical results reveal strong heterogeneity across unconditional quantiles.