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	समय-परिवर्तनीय पैरामीटर एसवीएआर मॉडल (टीवीपी-एसवीएआर)	बायेसियन VAR मॉडल (BVAR)
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	2005	1984
प्रवर्तक	Giorgio E. Primiceri	Doan, Litterman & Sims
प्रकार	Bayesian state-space SVAR	Multivariate time-series model
मौलिक स्रोत	Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821–852.	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.
उपनाम	TVP-SVAR, time-varying SVAR, drifting-parameter SVAR, TVP structural VAR	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
संबंधित	2	5
सारांश	The Time-Varying Parameter Structural VAR (TVP-SVAR) model extends classical structural VARs by allowing both the reduced-form coefficients and the structural impact matrix to evolve continuously over time. Estimated via Bayesian MCMC, it captures shifting transmission mechanisms and heteroscedastic volatility — making it the workhorse for empirical macroeconomics when policy regimes and economic relationships change.	The Bayesian Vector Autoregression (BVAR) model extends the classical VAR framework by incorporating prior beliefs about the model coefficients. Priors — most commonly the Minnesota prior — shrink VAR coefficients toward economically sensible values, dramatically reducing overfitting and improving out-of-sample forecast accuracy even when the number of variables is large.