double_selection_ate: Estimate average treatment effect (ATE) with double selection...

In jackcollison/causality: Tools for Performing Causal Inference with Observational Data

Description

Estimate average treatment effect (ATE) with double selection methodology.

Usage

double_selection_ate(data, x, y, w, nfolds = 5)

Arguments

data	a dataframe object containing the variables and values.
x	a list of character vectors specifying variables to be included in the model (columns in the data). If unspecified, then it is assumed to be all columns in the data besides y and w.
y	a character vector specifying the response variable.
w	a character vector specifying the treatment status.
nfolds	integer describing number of folds to use in k-fold cross-validation; preset to 5

Details

Estimates the average treatment effect τ using the methodology developed in Belloni, Chernozhukov, and Hansen (2014), which they term the “post-double-selection" method. The general procedure performed here is as follows:

1. Predict the treatment W_i using the covariates X_i using lasso regression (where λ is tuned using cross-validation). Select the covariates that have non-zero coefficients in the lasso model.

2. Predict the outcome Y_i using the covariates X_i using lasso regression (where λ is tuned using cross-validation). Select the covariates that have non-zero coefficients in the lasso model.

3. Estimate the treatment effect τ by the linear regression of Y_i on the treatment W_i and the union of the set of variables selected in the two covariate selection steps.

Value

numeric estimate of the average treatment effect.

References

Belloni, Alexandre, Victor Chernozhukov, and Christian Hansen. 2014. “High-Dimensional Methods and Inference on Structural and Treatment Effects." Journal of Economic Perspective. Vol. 28, Num. 2, Spring 2014. pgs. 29–50. https://www.aeaweb.org/articles?id=10.1257/jep.28.2.29

Examples

data("lalonde")
ate <- double_selection_ate(data = lalonde, y = "re78", w = "treat")

jackcollison/causality documentation built on Dec. 20, 2021, 8:05 p.m.