Quantile Treatment Effects
bootiter
bootstrap
bounds
BoundsObj
ci.qte
ci.qtet
Change in Changes
compute.ci.qte
compute.ci.qtet
athey.imbens
compute.ddid2
compute.MDiD
compute.panel.qtet
Quantile Difference in Differences
compute.spatt
computeDiffSE
computeSE
ddid2
diffQ
DR
getlb
getub
ggqte
Lalonde's Panel Experimental Dataset
Lalonde's Experimental Dataset
Lalonde's Experimental Dataset
Lalonde's Observational Dataset
Mean Difference in Differences
panel.checks
panel.qtet
panelize.data
Plot Bounds
plot.QTE
print.matrix1
print.matrix2
Print a summary.BoundsObj
Quantile Difference in Differences
qte: A package for computating quantile treatment effects
QTEparams
qtes2mat
diffQ
SE
setupData
spatt
Summary of BoundsObj
Summary
Provides several methods for computing the Quantile Treatment Effect (QTE) and Quantile Treatment Effect on the Treated (QTT). The main cases covered are (i) Treatment is randomly assigned, (ii) Treatment is as good as randomly assigned after conditioning on some covariates (also called conditional independence or selection on observables) using the methods developed in Firpo (2007) <doi:10.1111/j.1468-0262.2007.00738.x>, (iii) Identification is based on a Difference in Differences assumption (several varieties are available in the package e.g. Athey and Imbens (2006) <doi:10.1111/j.1468-0262.2006.00668.x> Callaway and Li (2019) <doi:10.3982/QE935>, Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>).