A review of the Granger-causality fallacy
Mariusz Maziarz
Abstract
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Mariusz Maziarz
Abstract
Open-access reader
Methods used to infer causal relations from data rather than knowledge of mechanisms are most helpful and exploited only if the theoretical background is insufficient or experimentation impossible. The review of literature shows that when an investigator has no prior knowledge of the researched phenomenon, no result of the Grangercausality test has any epistemic utility due to different possible interpretations. (1) Rejecting the null in one of the tests can be interpreted as either a true causal relation, opposite direction of the true causation, instant causality, time series cointegration, not frequent enough sampling, etc. (2) Bi-directional Granger causality can be read either as instant causality or common cause fallacy. (3) Non-rejection of both nulls possibly means either indirect or nonlinear causality, or no causal relation.
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Methods used to infer causal relations from data rather than knowledge of mechanisms are most helpful and exploited only if the theoretical background is insufficient or experimentation impossible. The review of literature shows that when an investigator has no prior knowledge of the researched phenomenon, no result of the Grangercausality test has any epistemic utility due to different possible interpretations. (1) Rejecting the null in one of the tests can be interpreted as either a true causal relation, opposite direction of the true causation, instant causality, time series cointegration, not frequent enough sampling, etc. (2) Bi-directional Granger causality can be read either as instant causality or common cause fallacy. (3) Non-rejection of both nulls possibly means either indirect or nonlinear causality, or no causal relation.
Key concepts: Causality (physics), Granger causality, Causation, Fallacy, Null hypothesis, Econometrics, Relation (database), Epistemology