In other cases, controlling for a non-confounding variable may cause underestimation of the true causal effect of the explanatory variables on an outcome (e.g. when controlling for a mediator or its descendant). Counterfactual reasoning mitigates the influence of confounders without this drawback.
Controlling for confounding variables, especially mediators or their descendants, can lead to underestimation of causal effects. Counterfactual reasoning offers a way to address this problem without relying on controlling for confounders directly.