QTE.RD-package {QTE.RD}

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 [e-mail]

• Jungmo Yoon [e-mail]

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; https://doi.org/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; https://doi.org/10.1080/07350015.2017.1407323