qte: Quantile Treatment Effects

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 covariates (selection on observables) using the methods of Firpo (2007) <doi:10.1111/j.1468-0262.2007.00738.x>, and (iii) identification is based on a Difference in Differences assumption, with support for several varieties including Athey and Imbens (2006) <doi:10.1111/j.1468-0262.2006.00668.x>, Callaway and Li (2019) <doi:10.3982/QE935>, and Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>. Version 2.0 adds a unified staggered treatment adoption API (built on 'ptetools') for all DiD-based estimators, as well as a new lagged-outcome unconfoundedness estimator ('lou_qtt').

Version: 2.0.0
Depends: R (≥ 3.5)
Imports: parallel, quantreg, BMisc, formula.tools, ggplot2, rlang, pbapply, data.table, ptetools (≥ 1.0.1)
Suggests: rmarkdown, knitr, msm, testthat (≥ 3.0.0), did, quarto
Published: 2026-07-23
DOI: 10.32614/CRAN.package.qte
Author: Brantly Callaway [aut, cre]
Maintainer: Brantly Callaway <brantly.callaway at uga.edu>
BugReports: https://github.com/bcallaway11/qte/issues
License: GPL-3
URL: https://bcallaway11.github.io/qte/, https://github.com/bcallaway11/qte
NeedsCompilation: no
Citation: qte citation info
Materials: README, NEWS
CRAN checks: qte results

Documentation:

Reference manual: qte.html , qte.pdf
Vignettes: Quantile Treatment Effects in R (source, R code)
Panel Data Estimators for Quantile Treatment Effects (source, R code)
Staggered Treatment Adoption with the qte Package (source, R code)

Downloads:

Package source: qte_2.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available
Old sources: qte archive

Reverse dependencies:

Reverse suggests: sccic

Linking:

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