Shpitser’s algorithm for finding each and every causal effect does not eliminate the need for the do-calculus. In fact, we need it even more, and for several independent reasons. First, we need it in order to go beyond observational studies. Suppose that worst comes to worst, and our causal model does not permit estimation of the causal effect P(Y | do(X)) from observations alone. Perhaps we also cannot conduct a randomized experiment with random assignment of X. A clever researcher might ask whether we might estimate P(Y | do(X)) by randomizing some other variable, say Z, that is more
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