On the Granularity of Causal Effect Identifiability

• URL: http://arxiv.org/abs/2510.16703v1
• Date: Sun, 19 Oct 2025 04:13:09 GMT
• Title: On the Granularity of Causal Effect Identifiability
• Authors: Yizuo Chen, Adnan Darwiche,
• Abstract summary: We consider the identifiability of state-based causal effects.<n>We show that state-based causal effects may be identifiable even when variable-based causal effects may not.
• Score: 10.227026799075215
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The classical notion of causal effect identifiability is defined in terms of treatment and outcome variables. In this note, we consider the identifiability of state-based causal effects: how an intervention on a particular state of treatment variables affects a particular state of outcome variables. We demonstrate that state-based causal effects may be identifiable even when variable-based causal effects may not. Moreover, we show that this separation occurs only when additional knowledge -- such as context-specific independencies and conditional functional dependencies -- is available. We further examine knowledge that constrains the states of variables, and show that such knowledge does not improve identifiability on its own but can improve both variable-based and state-based identifiability when combined with other knowledge such as context-specific independencies. Our findings highlight situations where causal effects of interest may be estimable from observational data and this identifiability may be missed by existing variable-based frameworks.

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