The Case for Time in Causal DAGs

TL;DR

This paper argues for integrating explicit time considerations into causal DAGs to clarify causal relationships and justify acyclicity assumptions, proposing a formalization with temporal variables.

Contribution

It introduces a formalization of causal variables at multiple time points and highlights the importance of time in interpreting and justifying causal DAGs.

Findings

Nontemporal causal DAGs are ambiguous without explicit time.

Causal relationships depend on temporal ordering.

Acyclicity assumptions require different justifications with cycles.

Abstract

We make the case for incorporating a notion of time into causal directed acyclic graphs (DAGs). We demonstrate that nontemporal causal DAGs are ambiguous and obstruct justification of the acyclicity assumption. Assuming that causes precede effects, causal relationships are relative to the time order, and causal DAGs require temporal qualification. We propose a formalization via composite causal variables that refer to quantities at one or multiple time points. We emphasize that the acyclicity assumption requires different justifications depending on whether the time order allows cycles. We conclude by discussing implications for the interpretation and applicability of DAGs as causal models.