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 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 (2017) <https://ssrn.com/abstract=3013341>, Callaway, Li, and Oka (2017) <arXiv:1702.03618>).

Version: 1.2.2
Depends: R (≥ 2.10)
Imports: Hmisc, parallel, quantreg, BMisc, formula.tools, ggplot2, texreg, pbapply
Suggests: knitr, rmarkdown
Published: 2018-04-30
Author: Brantly Callaway [aut, cre]
Maintainer: Brantly Callaway <brantly.callaway at temple.edu>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: qte results

Downloads:

Reference manual: qte.pdf
Vignettes: ddid2
panel.qtet
Package source: qte_1.2.2.tar.gz
Windows binaries: r-devel: qte_1.2.2.zip, r-release: qte_1.2.2.zip, r-oldrel: qte_1.2.2.zip
OS X binaries: r-release: qte_1.2.2.tgz, r-oldrel: qte_1.2.2.tgz
Old sources: qte archive

Reverse dependencies:

Reverse imports: csabounds

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