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Fourierov test kauzalnosti Toda-Yamamoto-Granger×Toda-Yamamotovo test uzročnosti×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelHypothesis test
Godina nastanka20191995
TvoracYilanci, Ozgur (building on Toda and Yamamoto 1995; Becker, Enders, and Hurn 2004)Hiro Toda & Taku Yamamoto
VrstaGranger causality testModified Wald test on augmented VAR
Temeljni izvorYilanci, V., & Ozgur, O. (2019). Testing the Fourier Toda-Yamamoto causality test with an application to energy demand. Energy Economics, 84, 104498. link ↗Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. DOI ↗
Drugi naziviFTY causality, Fourier TY causality, Toda-Yamamoto causality with Fourier approximation, FTY Granger causalityTY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik Testi
Srodne33
SažetakThe Fourier Toda-Yamamoto (FTY) causality test extends the classical Toda-Yamamoto procedure by embedding Fourier trigonometric terms in the augmented VAR to capture smooth, gradual structural breaks in the deterministic component. It retains the key advantage of the Toda-Yamamoto approach — Granger causality can be tested without pre-testing for integration or cointegration order — while dramatically improving size and power when breaks occur.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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ScholarGateUsporedite metode: Fourier Toda-Yamamoto Causality · Toda-Yamamoto Causality. Preuzeto 2026-06-20 s https://scholargate.app/hr/compare