QTE.RD - Quantile Treatment Effects under the Regression Discontinuity Design - Methods and inference

Sep 4, 2026

Comprehensive methods for testing, estimating, and conducting uniform inference on quantile treatment effects (QTEs) in sharp regression discontinuity (RD) designs are provided, including approaches that incorporate covariates and robust bias correction. The package supports estimation of QTEs with uniform confidence bands, hypothesis testing for treatment significance and directionality, and bandwidth selection via cross-validation or MSE-optimal rules. Visualization tools summarize treatment effects and conditional quantile processes.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages17

Reading Time43 min

AccessFree to download

QTE.RD-package

ddk_2011

plot.qte

rd.qte

rdq

rdq.band

rdq.bandwidth

rdq.bias

rdq.condf

rdq.test

summary.qte

Index

Package ‘QTE.RD’ May 7, 2026 Title Quantile Treatment Effects under the Regression Discontinuity Design Version 1.2.0 Author Zhongjun Qu [aut, cph], Jungmo Yoon [aut, cre, cph] Maintainer Jungmo Yoon <[jmyoon@hanyang.ac.kr](jmyoon@hanyang.ac.kr)> Description Provides comprehensive methods for testing, estimating, and conducting uniform inference on quantile treatment effects (QTEs) in sharp regression discontinuity (RD) designs, incorporating covariates and implementing robust bias correction methods of Qu, Yoon, Perron (2024) . Encoding UTF-8 RoxygenNote 7.3.2 Imports quantreg, plotrix, stats License GPL (>= 3) Suggests knitr, rmarkdown, spelling, testthat (>= 3.0.0) Language en-US Depends R (>= 2.10) LazyData true Config/testthat/edition 3 VignetteBuilder knitr NeedsCompilation no Repository CRAN Date/Publication 2025-08-30 04:20:02 UTC Contents QTE.RD-package ...................................... 2 ddk_2011 .......................................... 3 plot.qte ........................................... 4 rd.qte ............................................ 5 2 QTE.RD-package rdq .............................................. 7 [rdq.band ...........................................](rdq.band ........................................... 8)[ 8](rdq.band ........................................... 8) [rdq.bandwidth ........................................](rdq.bandwidth ........................................ 10)[ 10](rdq.bandwidth ........................................ 10) [rdq.bias ...........................................](rdq.bias ........................................... 11)[ 11](rdq.bias ........................................... 11) [rdq.condf ..........................................](rdq.condf .......................................... 12)[ 12](rdq.condf .......................................... 12) [rdq.test ...........................................](rdq.test ........................................... 13)[ 13](rdq.test ........................................... 13) [summary.qte .........................................](summary.qte ......................................... 15)[ 15](summary.qte ......................................... 15) Index 17 | QTE.RD-package | QTE. RD: Quantile Treatment Effects under the Regression Discontinuity Design | | --- | --- | Description Provides comprehensive methods for testing, estimating, and conducting uniform inference on quantile treatment effects (QTEs) in sharp regression discontinuity (RD) designs, incorporating covariates and implementing robust bias correction methods of Qu, Yoon, Perron (2024) doi:10.1162/ rest_a_01168. Details The package QTE .RD includes four main functions: • rd.qte estimates QTEs and provides uniform confidence bands, with or without covariates, and with or without robust bias correction. • rdq.test conducts tests for three hypotheses, related to the significance of treatment effects, homogeneous treatment effects, and uniformly positive or negative treatment effects. • rdq.bandwidth implements two bandwidth selection rules: the cross-validation bandwidth and the MSE optimal bandwidth. • plot.qte generates figures summarizing the treatment effects along with their confidence bands. Author(s) • [Zhongjun Qu](Zhongjun Qu qu@bu.edu)[ qu@bu.edu](Zhongjun Qu qu@bu.edu) • [Jungmo Yoon](Jungmo Yoon jmyoon@hanyang.ac.kr)[ jmyoon@hanyang.ac.kr](Jungmo Yoon jmyoon@hanyang.ac.kr) References Zhongjun Qu, Jungmo Yoon, Pierre Perron (2024), "Inference on Conditional Quantile Processes in Partially Linear Models with Applications to the Impact of Unemployment Benefits," The Review of Economics and Statistics; doi:10 . 1162/rest_a_01168 Zhongjun Qu and Jungmo Yoon (2019), "Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs," Journal of Business and Economic Statistics, 37(4), 625–647; doi:10.1080/07350015.2017.

FAQs

What does the QTE.RD package provide for sharp regression discontinuity designs?

It provides methods to test and estimate quantile treatment effects (QTEs) and to conduct uniform inference, including options with covariates and robust bias correction.

Which functions are included for QTE estimation, testing, and visualization?

rd.qte estimates QTEs and uniform confidence bands, rdq.test performs tests on treatment-related hypotheses, and plot.qte generates plots summarizing QTE estimates and confidence bands.

How are bandwidths selected in rdq.bandwidth?

Two bandwidth selection rules are implemented: cross-validation bandwidth and MSE-optimal bandwidth selection.

Sep 4, 2026

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