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Zeitvariante Parameter Toda-Yamamoto-Kausalität×Vektorautoregressionsmodell (VAR)×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr1995 (base); TVP variant emerged early 2000s–2010s2005
UrheberToda & Yamamoto (1995); TVP extension by subsequent applied econometriciansLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypCausality test (time-varying)Multivariate time-series model
Wegweisende QuelleToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
AliasnamenTVP-TY causality, time-varying Toda-Yamamoto, TVP Granger causality (Toda-Yamamoto), rolling/recursive Toda-Yamamoto causalityvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Verwandt34
ZusammenfassungThe TVP Toda-Yamamoto causality test combines Toda and Yamamoto's (1995) augmented VAR approach — which handles possibly integrated or cointegrated series without pre-testing for unit roots — with time-varying parameters, allowing causal relationships between variables to shift across different periods rather than remaining fixed throughout the sample.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateMethoden vergleichen: Time-varying parameter Toda-Yamamoto causality · VAR Model. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare