Linking Granger Causality and the Pearl Causal Model with Settable Systems
Proceedings of the Neural Information Processing Systems Mini-Symposium on Causality in Time Series, PMLR 12:1-29, 2011.
The causal notions embodied in the concept of Granger causality have been argued to belong to a different category than those of Judea Pearl’s Causal Model, and so far their relation has remained obscure. Here, we demonstrate that these concepts are in fact closely linked by showing how each relates to straightforward notions of direct causality embodied in settable systems, an extension and refinement of the Pearl Causal Model designed to accommodate optimization, equilibrium, and learning. We then provide straightforward practical methods to test for direct causality using tests for Granger causality.