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 (2019) <https://ssrn.com/abstract=3013341>, Callaway, Li, and Oka (2018) <doi:10.1016/j.jeconom.2018.06.008>).

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Description file content

Package
qte
Title
Quantile Treatment Effects
Version
1.3.0
Date
2019-06-09
Description
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) , (iii) Identification is based on a Difference in Differences assumption (several varieties are available in the package e.g. Athey and Imbens (2006) Callaway and Li (2019) , Callaway, Li, and Oka (2018) ).
Depends
R (>= 2.10)
Imports
Hmisc, parallel, quantreg, BMisc, formula.tools, ggplot2, texreg, pbapply, knitr, msm
License
GPL-2
LazyData
true
RoxygenNote
6.1.1
Encoding
UTF-8
Suggests
rmarkdown
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2019-06-09 23:12:56 UTC; brant
Author
Brantly Callaway [aut, cre]
Maintainer
Brantly Callaway
Repository
CRAN
Date/Publication
2019-06-10 05:30:03 UTC

install.packages('qte')

1.3.0

6 days ago

Brantly Callaway

GPL-2

Depends on

R (>= 2.10)

Imports

Hmisc, parallel, quantreg, BMisc, formula.tools, ggplot2, texreg, pbapply, knitr, msm

Suggests

rmarkdown

Discussions