เปรียบเทียบวิธี

	แบบจำลอง VAR พารามิเตอร์แปรผันตามเวลา (TVP-VAR)	แบบจำลองเวกเตอร์อัตถารวมเชิงโครงสร้าง (Structural Vector Autoregression: SVAR)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2005	1980
ผู้ริเริ่ม	Giorgio Primiceri	Christopher Sims
ประเภท	Bayesian state-space model	Structural multivariate time-series model
แหล่งต้นตำรับ	Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821–852.	Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48.
ชื่อเรียกอื่น	Time-Varying Parameter Vector Autoregression, TVP-SVAR, Stochastic Coefficient VAR, Zamana Göre Değişen Parametreli VAR	Structural VAR, Identified VAR, SVAR Model, Yapısal Vektör Otoregresyon
ที่เกี่ยวข้อง	2	2
สรุป	TVP-VAR is a Bayesian multivariate time-series model in which both the VAR coefficients and the shock covariance matrix are allowed to evolve continuously over time as random walks. Introduced by Primiceri (2005) to study U.S. monetary policy transmission, the model captures structural changes and regime shifts without requiring ex-ante knowledge of when breaks occurred, making it indispensable for macroeconomics, finance, and any setting where economic relationships are suspected to be unstable across time.	Structural Vector Autoregression (SVAR) is a multivariate time-series model, developed by Christopher Sims (1980), that extends the reduced-form VAR by imposing economically motivated identifying restrictions on contemporaneous relationships among variables. SVAR enables researchers to isolate orthogonal structural shocks and trace their causal dynamic effects through impulse response functions and forecast error variance decompositions, making it a cornerstone of modern empirical macroeconomics.