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Έλεγχος Αιτιότητας Fourier-Granger×Δοκιμή Αιτιότητας Toda-Yamamoto×
ΠεδίοΟικονομετρίαΟικονομετρία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης20161995
ΔημιουργόςEnders and JonesToda, H. Y. and Yamamoto, T.
ΤύποςCausality testCausality test
Θεμελιώδης πηγήEnders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. 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 ↗
Εναλλακτικές ονομασίεςFourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causalityToda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
Συναφείς65
ΣύνοψηThe Fourier Granger causality test extends the classic Granger causality framework by embedding low-frequency Fourier terms in the VAR equation, allowing the causal relationship to shift gradually over time without requiring the researcher to pre-specify the number or location of structural breaks.The Toda-Yamamoto (TY) causality test is a modified Wald procedure for testing Granger causality in vector autoregressions (VARs) estimated in levels, even when variables are nonstationary or cointegrated. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, it restores the standard chi-squared asymptotic distribution of the Wald statistic without requiring prior unit-root or cointegration pretesting.
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ScholarGateΣύγκριση μεθόδων: Fourier Granger Causality · Toda-Yamamoto causality test. Ανακτήθηκε στις 2026-06-19 από https://scholargate.app/el/compare