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Ujian Kausaliti Granger×Ujian Kausalitas Toda-Yamamoto×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19691995
PengasasClive W. J. GrangerToda, H. Y. and Yamamoto, T.
JenisCausality test (F-test on VAR)Causality test
Sumber perintisGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. 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 ↗
AliasGranger test, GC test, predictive causality test, Granger non-causality testToda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
Berkaitan55
RingkasanThe Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.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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ScholarGateBandingkan kaedah: Granger Causality Test · Toda-Yamamoto causality test. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare