38.4 Causal Discovery
Causal discovery involves algorithmically identifying causal relationships from data under a set of assumptions (like faithfulness and causal sufficiency). Key algorithms include:
- PC algorithm: Constraint-based, uses conditional independence testing
- GES (Greedy Equivalence Search): Score-based method
- FCI (Fast Causal Inference): Extends PC to handle latent confounders
See (Eberhardt, Kaynar, and Siddiq 2024) for a comprehensive discussion on the assumptions and limitations of discovery algorithms in practice.
References
Eberhardt, Frederick, Nur Kaynar, and Auyon Siddiq. 2024. “Discovering Causal Models with Optimization: Confounders, Cycles, and Instrument Validity.” Management Science.