ccfa: Continuous Counterfactual Analysis

Contains methods for computing counterfactuals with a continuous treatment variable as in Callaway and Huang (2017) <https://ssrn.com/abstract=3078187>. In particular, the package can be used to calculate the expected value, the variance, the interquantile range, the fraction of observations below or above a particular cutoff, or other user-supplied functions of an outcome of interest conditional on a continuous treatment. The package can also be used for computing these same functionals after adjusting for differences in covariates at different values of the treatment. Further, one can use the package to conduct uniform inference for each parameter of interest across all values of the treatment, uniformly test whether adjusting for covariates makes a difference at any value of the treatment, and test whether a parameter of interest is different from its average value at an value of the treatment.

Version: 1.1.0
Depends: R (≥ 2.1.0)
Imports: quantreg, stats, pbapply, BMisc, tidyr, ggplot2, TempleMetrics, doParallel, foreach, formula.tools
Published: 2018-09-18
Author: Weige Huang [aut, cre], Brantly Callaway [aut]
Maintainer: Weige Huang <weige.huang at temple.edu>
License: GPL-2
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ccfa results

Downloads:

Reference manual: ccfa.pdf
Package source: ccfa_1.1.0.tar.gz
Windows binaries: r-devel: ccfa_1.1.0.zip, r-release: ccfa_1.1.0.zip, r-oldrel: ccfa_1.1.0.zip
OS X binaries: r-release: not available, r-oldrel: not available
Old sources: ccfa archive

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