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Parametru laika dinamika Toda-Jamamoto cēloņsakarība×Toda-Yamamoto (TY) Granger cēloņsakarības pārbaude×
NozareEkonometrijaEkonometrija
SaimeRegression modelHypothesis test
Izcelsmes gads1995 (base); TVP variant emerged early 2000s–2010s1995
AutorsToda & Yamamoto (1995); TVP extension by subsequent applied econometriciansHiro Toda & Taku Yamamoto
TipsCausality test (time-varying)Modified Wald test on augmented VAR
PirmavotsToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. DOI ↗
Citi nosaukumiTVP-TY causality, time-varying Toda-Yamamoto, TVP Granger causality (Toda-Yamamoto), rolling/recursive Toda-Yamamoto causalityTY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik Testi
Saistītās33
KopsavilkumsThe 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.The 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.
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ScholarGateSalīdzināt metodes: Time-varying parameter Toda-Yamamoto causality · Toda-Yamamoto Causality. Izgūts 2026-06-20 no https://scholargate.app/lv/compare