README.md
In QTE.RD: Quantile Treatment Effects under the Regression Discontinuity Design

QTE.RD

The goal of QTE.RD is to provide comprehensive tools for testing, estimating, and conducting uniform inference on quantile treatment effects (QTEs) in sharp regression discontinuity (RD) designs. When treatment effects vary across covariate-groups, QTE.RD facilitates the estimation, testing, and visualization of heterogeneous effects by incorporating covariates and applying the robust bias correction methods developed by Qu, Yoon, and Perron (2024, ).

The package is available on CRAN and can be loaded by

library(QTE.RD)

The following example demonstrates how to use the rd.qte function from the QTE.RD package, using data from Duflo, Dupas, and Kremer (2011, AER). It estimates the quantile treatment effects of tracking on student achievement.

data(ddk_2011)
yc <- ddk_2011$ts_std[ddk_2011$tracking==1]
xc <- ddk_2011$percentile[ddk_2011$tracking==1]
dc <- ddk_2011$highstream[ddk_2011$tracking==1]

A <- rd.qte(y=yc,x=xc,d=dc,x0=50,z0=NULL,tau=(1:9/10),bdw=20,bias=1)
summary(A,alpha=0.1)
#> 
#> 
#>                                  QTE                                   
#> ---------------------------------------------------------------------- 
#>              Bias cor.    Pointwise         Uniform      
#>     Tau         Est.     Robust S.E.    90% Conf. Band  
#>      0.1      -0.104       0.137      -0.430       0.221
#>      0.2      -0.001       0.146      -0.348       0.346
#>      0.3      -0.068       0.155      -0.437       0.302
#>      0.4      -0.074       0.158      -0.451       0.303
#>      0.5      -0.157       0.178      -0.581       0.267
#>      0.6      -0.069       0.216      -0.584       0.445
#>      0.7      -0.020       0.267      -0.655       0.616
#>      0.8      -0.023       0.310      -0.762       0.715
#>      0.9      -0.003       0.269      -0.644       0.639