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| Bayesian Toda-Yamamoto-Kausalitätstest× | Vektorautoregression (VAR)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1995 (base); Bayesian variant developed post-2000 | 1980 |
| Urheber≠ | Toda & Yamamoto (1995) for the frequentist base; Bayesian extension by subsequent applied econometricians | Christopher A. Sims |
| Typ≠ | Causality test / VAR-based inference | Multivariate time-series model |
| Wegweisende Quelle≠ | Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Aliasnamen | Bayesian TY causality, Bayesian modified Wald causality, Bayesian Granger non-causality in VAR, BTY causality | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Verwandt≠ | 3 | 5 |
| Zusammenfassung≠ | The 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. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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