เปรียบเทียบวิธี

	การทดสอบ Robust Granger Causality	การทดสอบความเป็นเหตุเป็นผลแบบแกรนเจอร์ (Granger Causality Test)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2006 (robust variant); 1969 (original Granger)	1969
ผู้ริเริ่ม	Hacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept)	Clive W. J. Granger
ประเภท	Hypothesis test	Time-series predictive causality test
แหล่งต้นตำรับ	Hacker, R. S., & Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distributions: Theory and application. Applied Economics, 38(13), 1489–1500.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
ชื่อเรียกอื่น	bootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGC	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
ที่เกี่ยวข้อง	4	5
สรุป	Robust Granger causality extends the classic Granger causality framework by using bootstrap-based or heteroscedasticity-robust critical values rather than asymptotic chi-squared tables. This makes the test reliable in finite samples and when the data exhibit non-normality, heteroscedasticity, or near-integration, settings where the standard F- or Wald-based test is known to over-reject.	The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.