On the Equivalence of Causal Models

Understand

Scientists often use directed acyclic graphs (days) to model the qualitative structure of causal theories, allowing the parameters to be estimated from observational data.

• Two causal models are equivalent if there is no experiment which could distinguish one from the other.
• A canonical representation for causal models is presented which yields an efficient graphical criterion for deciding equivalence, and provides a theoretical basis for extracting causal structures from empirical data.
• This representation is then extended to the more general case of an embedded causal model, that is, a dag in which only a subset of the variables are observable.