Counterfactual: An R Package for Counterfactual Analysis
Mingli Chen, Victor Chernozhukov, Iv\'an Fern\'andez-Val, and Blaise, Melly
TL;DR
The paper introduces the Counterfactual R package, which implements advanced methods for counterfactual analysis, allowing researchers to estimate effects of distributional changes on outcomes.
Contribution
It provides an accessible implementation of Chernozhukov et al.'s methods for counterfactual distribution estimation in R, facilitating empirical analysis.
Findings
Enables estimation of quantile treatment effects
Supports wage decomposition analysis
Provides user-friendly R functions for counterfactual inference
Abstract
The Counterfactual package implements the estimation and inference methods of Chernozhukov, Fern\'andez-Val and Melly (2013) for counterfactual analysis. The counterfactual distributions considered are the result of changing either the marginal distribution of covariates related to the outcome variable of interest, or the conditional distribution of the outcome given the covariates. They can be applied to estimate quantile treatment effects and wage decompositions. This paper serves as an introduction to the package and displays basic functionality of the commands contained within.
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