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Evaluating Counterfactuals in Structural Causal Models

Evaluating a counterfactual using a Structural Causal Model (SCM) involves three sequential steps, which are valid regardless of whether the functional relationships are linear or non-linear:

  1. Abduction: Use evidence (observations) to estimate the values of the unobserved background (exogenous) variables UU.
  2. Action: Use the do-operator to intervene on the model, setting the value of the antecedent variable (e.g., setting M=mM = m), which modifies the structural equations by removing the equations that originally determined that variable.
  3. Prediction: Use the modified structural equations and the estimated values of UU to calculate the counterfactual values of the outcome variables (e.g., YY).

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Updated 2026-06-21

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Data Science