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Zivot-Andrews Test voor Structurele Breuk in eenheidswortel×Toda-Yamamoto Causaliteitstest×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan19921995
GrondleggerEric Zivot and Donald W. K. AndrewsToda, H. Y. and Yamamoto, T.
TypeUnit root test with endogenous structural breakCausality test
Oorspronkelijke bronZivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270. 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 ↗
AliassenZivot-Andrews test, ZA unit root test, endogenous structural break unit root test, ZA breakpoint testToda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
Verwant65
SamenvattingThe Zivot-Andrews test is an endogenous structural break unit root test that determines the break point from the data rather than imposing it externally. It tests for a unit root against the alternative of stationarity around a single structural break — in the mean, the trend, or both — choosing the break date that provides the strongest evidence against the null.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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ScholarGateMethoden vergelijken: Structural break Zivot-Andrews test · Toda-Yamamoto causality test. Geraadpleegd op 2026-06-19 via https://scholargate.app/nl/compare