เปรียบเทียบวิธี

	การทดสอบสาเหตุแบบแกรนเจอร์ (Granger Causality Test)	การทดสอบความเป็นเหตุเป็นผลแบบ Toda-Yamamoto
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1969	1995
ผู้ริเริ่ม	Clive W. J. Granger	Toda, H. Y. and Yamamoto, T.
ประเภท	Causality test (F-test on VAR)	Causality test
แหล่งต้นตำรับ	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438.	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.
ชื่อเรียกอื่น	Granger test, GC test, predictive causality test, Granger non-causality test	Toda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
ที่เกี่ยวข้อง	5	5
สรุป	The 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.