Data Science, Statistics, Causality, Machine Learning, Analytics.
be one of the backbones of econometrics. We are concerned with this DAG: U is an unobserved confounder. We want to estimate the causal effect of Y on Z, Y → Z. By this DAG, we can estimate X → Y and X → Z. Assuming linearity, we have X → Z = (X → Y) (Y → Z) and we can solve for Y → Z algebraically.