Weighted Linear Fixed Effects Estimators for Causal Inference
Description
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 (2011)
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.