wfe: Weighted Linear Fixed Effects Regression Models for Causal Inference

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This R package provides a computationally efficient way of fitting weighted linear fixed effects estimators for causal inference with various weighting schemes. Imai and Kim (2012) show that weighted linear fixed effects estimators can be used to estimate the average treatment effects under different identification strategies. This includes stratified randomized experiments, matching and stratification for observational studies, first differencing, and difference-in-differences. The package also provides various robust standard errors and a specification test for standard linear fixed effects estimators.

Author
In Song Kim <insong@mit.edu>, Kosuke Imai <kimai@Princeton.edu>
Date of publication
2014-08-11 05:56:52
Maintainer
In Song Kim <insong@mit.edu>
License
GPL (>= 2)
Version
1.3

View on CRAN

Man pages

pwfe
Fitting the Weighted Fixed Effects Model with Propensity...
wfe
Fitting the Weighted Fixed Effects Model for Causal Inference

Files in this package

wfe
wfe/src
wfe/src/Makevars
wfe/src/vector.c
wfe/src/vector.h
wfe/src/wfe.c
wfe/src/wfe.h
wfe/NAMESPACE
wfe/Changelog
wfe/R
wfe/R/onAttach.R
wfe/R/wfe.R
wfe/R/pwfe.R
wfe/R/functions.R
wfe/MD5
wfe/DESCRIPTION
wfe/man
wfe/man/wfe.Rd
wfe/man/pwfe.Rd