Minimal sufficient causation and directed acyclic graphs

TL;DR

This paper integrates minimal sufficient causation concepts into directed acyclic graphs, enabling graphical representation of causal mechanisms and linking counterfactual and mechanistic causality theories.

Contribution

It introduces a novel framework that incorporates minimal sufficient causes into DAGs, bridging two major causality conceptualizations.

Findings

Graphical representation of sufficient causes within DAGs

Theoretical link between counterfactual and mechanistic causality

Ability to infer sign of conditional covariances

Abstract

Notions of minimal sufficient causation are incorporated within the directed acyclic graph causal framework. Doing so allows for the graphical representation of sufficient causes and minimal sufficient causes on causal directed acyclic graphs while maintaining all of the properties of causal directed acyclic graphs. This in turn provides a clear theoretical link between two major conceptualizations of causality: one counterfactual-based and the other based on a more mechanistic understanding of causation. The theory developed can be used to draw conclusions about the sign of the conditional covariances among variables.