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.

Getting started

Package details

AuthorWeige Huang [aut, cre], Brantly Callaway [aut]
MaintainerWeige Huang <weige.huang@temple.edu>
LicenseGPL-2
Version1.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("ccfa")

Try the ccfa package in your browser

Any scripts or data that you put into this service are public.

ccfa documentation built on May 2, 2019, 7:28 a.m.