เปรียบเทียบวิธี

	การทดสอบความเป็นเหตุเป็นผลแบบกรานเจอร์ด้วยพารามิเตอร์ที่แปรผันตามเวลา	Structural Vector Autoregression (SVAR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1969 (Granger); TVP extension ~2005	1980
ผู้ริเริ่ม	C.W.J. Granger (causality concept); TVP extension developed by Primiceri (2005) and subsequent literature	Sims (1980); identification schemes by Blanchard & Quah (1989)
ประเภท	Causality test / time-varying model	Multivariate time series model
แหล่งต้นตำรับ	Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438.	Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673.
ชื่อเรียกอื่น	TVP Granger causality, rolling-window Granger causality, time-varying Granger test, dynamic Granger causality	SVAR, structural vector autoregression, identified VAR, structural VAR model
ที่เกี่ยวข้อง	4	5
สรุป	Time-varying parameter Granger causality extends the classical Granger causality framework by allowing the predictive relationships between time series to evolve across time. Instead of assuming fixed causal effects, the model estimates causal coefficients that can shift, capturing structural breaks, regime changes, or gradual evolution in economic or financial relationships.	Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions.