Causation and decision: On Dawid’s “Decision theoretic foundation of statistical causality”

Abstract

In a recent issue of this journal, Philip Dawid (2021) proposes a framework for causal inference that is based on statistical decision theory and that is, in many aspects, compatible with the familiar framework of causal graphs (e.g., Directed Acyclic Graphs (DAGs)). This editorial compares the methodological features of the two frameworks as well as their epistemological basis.

Keywords

• directed acyclic graphs
• conditional independence
• potential outcome
• ladder of causation
• causal bayesian network
• decision theory
• structural causal models
• do-calculus
• 62a01
• 62c99