The Rubin Causal Model frames the causal inference question as the problem of inferring missing potential outcomes (what the outcome would have been if a unit had received a different treatment) in order to estimate the causal effects of hypothetical treatments/interventions.

It seems like an intuitive and very general framework. When is this approach most likely to fail in practice? Why isn't it more widely used?

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    $\begingroup$ What do you mean by fail? $\endgroup$ – Carlos Cinelli Nov 2 '18 at 3:37

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