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WhatIF: R Software for Evaluating Counterfactuals

Author

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  • Stoll, Heather
  • King, Gary
  • Zeng, Langche

Abstract

WhatIf is an R package that implements the methods for evaluating counterfactuals introduced in King and Zeng (2006a) and King and Zeng (2006b). It offers easy-to-use techniques for assessing a counterfactual's model dependence without having to conduct sensitivity testing over specified classes of models. These same methods can be used to approximate the common support of the treatment and control groups in causal inference.

Suggested Citation

  • Stoll, Heather & King, Gary & Zeng, Langche, 2005. "WhatIF: R Software for Evaluating Counterfactuals," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 15(i04).
    • Handle: RePEc:jss:jstsof:v:015:i04
    DOI: http://hdl.handle.net/10.18637/jss.v015.i04
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    References listed on IDEAS

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    1. Ho, Daniel & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2011. "MatchIt: Nonparametric Preprocessing for Parametric Causal Inference," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i08).
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    Cited by:

    1. Canaydin, Ada & Fu, Chun & Balint, Attila & Khalil, Mohamad & Miller, Clayton & Kazmi, Hussain, 2024. "Interpretable domain-informed and domain-agnostic features for supervised and unsupervised learning on building energy demand data," Applied Energy, Elsevier, vol. 360(C).
    2. Michael Funke & Marc Gronwald, 2009. "A Convex Hull Approach to Counterfactual Analysis of Trade Openness and Growth," CESifo Working Paper Series 2692, CESifo.

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