In the conventional theory of causal inference, such as Rubin’s potential outcomes model or Pearl’s DAG approach, causality is modelled as a relationship of functional determination, X := f(Y). The question of interest becomes to study the properties of f, especially the difference in f across different values of Y. I would call this “effect size estimation”, because the goal is to give quantify the magnitude of an effect of one variable on another.