Simulating counterfactuals

Juha Karvanen; Santtu Tikka; Matti Vihola

doi:10.1613/jair.1.15579

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arXiv · 2306.15328

Simulating counterfactuals

Juha Karvanen·Santtu Tikka·Matti Vihola

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Abstract

Counterfactual inference considers a hypothetical intervention in a parallel world that shares some evidence with the factual world. If the evidence specifies a conditional distribution on a manifold, counterfactuals may be analytically intractable. We present an algorithm for simulating values from a counterfactual distribution where conditions can be set on both discrete and continuous variables. We show that the proposed algorithm can be presented as a particle filter leading to asymptotically valid inference. The algorithm is applied to fairness analysis in credit-scoring.

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BibTeX RIS

Juha Karvanen, Santtu Tikka, Matti Vihola. 2023-06-27. Simulating counterfactuals. https://doi.org/10.1613/jair.1.15579

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