Regression model
Granger Causality Test
The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.
EconMind ile uygulaSoonVideoSoon
Tam yöntemi oku
Members only
Sign inSign in with a free account to read this section.
Sources
- Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI: 10.2307/1912791 ↗
Related methods
Referenced by
Bayesian Toda-Yamamoto CausalityCointegration TestConvergent Cross MappingDifference-in-DifferencesDolado-Lütkepohl CausalityDumitrescu-Hurlin CausalityFourier Hausman testFourier Toda-Yamamoto CausalityHatemi-J Asymmetric CausalityHiemstra-Jones CausalityKónya Bootstrap CausalityNonlinear NARDLNonlinear Toda-Yamamoto CausalityRobust Granger CausalityStructural Break Granger CausalityTime-varying parameter Granger causalityTime-varying parameter Toda-Yamamoto causalityToda-Yamamoto CausalityTransfer Entropy