Σύγκριση μεθόδων

	Δοκιμή Αιτιότητας Toda-Yamamoto	Έλεγχος Μοναδιαίας Ρίζας Augmented Dickey-Fuller (ADF)
Πεδίο	Οικονομετρία	Οικονομετρία
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1995	1979–1984
Δημιουργός	Toda, H. Y. and Yamamoto, T.	Said & Dickey (1984); building on Dickey & Fuller (1979)
Τύπος	Causality test	Hypothesis test (unit root)
Θεμελιώδης πηγή	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.	Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.
Εναλλακτικές ονομασίες	Toda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD	ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test
Συναφείς	5	5
Σύνοψη	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.	The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance.