Methoden vergleichen

	Strukturelle Bruch-Granger-Kausalität	Granger-Kausalitätstest	Vektorautoregression (VAR)
Fachgebiet	Ökonometrie	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model	Regression model
Entstehungsjahr	1995-2010	1969	1980
Urheber	Granger (1969) causality framework extended by Toda & Yamamoto (1995) and Balcilar et al. (2010)	Clive W. J. Granger	Christopher A. Sims
Typ	Hypothesis test / time-series model	Time-series predictive causality test	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.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Aliasnamen	break-robust Granger causality, Granger causality under regime change, time-varying Granger causality, structural change Granger test	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi	VAR, VAR model, vector autoregressive model, multivariate autoregression
Verwandt	3	5	5
Zusammenfassung	Structural break Granger causality extends the classic Granger causality framework to accommodate regime shifts and parameter instability in time series. By detecting break points and testing causality within sub-samples or via rolling/recursive windows, it reveals whether a predictive relationship between variables switches on, switches off, or changes direction over time.	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.	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.