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Counterfactual analysis in R: a vignette

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Listed:
  • Mingli Chen
  • Victor Chernozhukov
  • Ivan Fernandez-Val
  • Blaise Melly

Abstract

The R package Counterfactual implements the estimation and inference methods of Chernozhukov et al. (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 vignette serves as an introduction to the package and displays basic functionality of the commands contained within.

Suggested Citation

  • Mingli Chen & Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2017. "Counterfactual analysis in R: a vignette," CeMMAP working papers 64/17, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:64/17
    DOI: 10.1920/wp.cem.2017.6417
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
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    3. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    4. Hong H. & Chernozhukov V., 2002. "Three-Step Censored Quantile Regression and Extramarital Affairs," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 872-882, September.
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