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)
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, doi:10.1162/rest_a_01168).
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