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Bayesijanski test uzročnosti Toda-Yamamoto×Grangerov test uzročnosti×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1995 (base); Bayesian variant developed post-20001969
TvoracToda & Yamamoto (1995) for the frequentist base; Bayesian extension by subsequent applied econometriciansClive W. J. Granger
VrstaCausality test / VAR-based inferenceTime-series predictive causality test
Temeljni izvorToda, 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 ↗
Drugi naziviBayesian TY causality, Bayesian modified Wald causality, Bayesian Granger non-causality in VAR, BTY causalityGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Srodne35
SažetakThe Bayesian Toda-Yamamoto causality procedure combines the Toda-Yamamoto VAR augmentation strategy — which sidesteps the need for pre-testing integration and cointegration — with Bayesian prior-posterior updating. It tests Granger non-causality between time series that may be integrated or cointegrated without requiring differencing or error-correction modeling, while incorporating prior information and producing full posterior distributions over the causal parameters.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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ScholarGateUsporedite metode: Bayesian Toda-Yamamoto Causality · Granger Causality. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare