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Test przyczynowości Granger wg Todę-Yamamotę×Test przyczynowości Grangera×
DziedzinaEkonometriaEkonometria
RodzinaHypothesis testRegression model
Rok powstania19951969
TwórcaHiro Toda & Taku YamamotoClive W. J. Granger
TypModified Wald test on augmented VARTime-series predictive causality test
Źródło pierwotneToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
Inne nazwyTY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik TestiGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Pokrewne35
PodsumowanieThe Toda-Yamamoto (TY) causality test, introduced by Toda and Yamamoto (1995), provides a robust procedure for testing Granger non-causality in vector autoregressive (VAR) models when the variables may be integrated or cointegrated of arbitrary order. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, the method bypasses the need for pre-testing cointegration and preserves the standard asymptotic chi-squared distribution of the Wald statistic.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.
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ScholarGatePorównaj metody: Toda-Yamamoto Causality · Granger Causality. Pobrano 2026-06-18 z https://scholargate.app/pl/compare