  Identification of causal effects is one of the most fundamental tasks of
causal inference. We consider an identifiability problem where some
experimental and observational data are available but neither data alone is
sufficient for the identification of the causal effect of interest. Instead of
the outcome of interest, surrogate outcomes are measured in the experiments.
This problem is a generalization of identifiability using surrogate experiments
and we label it as surrogate outcome identifiability. We show that the concept
of transportability provides a sufficient criteria for determining surrogate
outcome identifiability for a large class of queries.
