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시변 모수 VAR 모형 (TVP-VAR)×베이즈 VAR 모형 (BVAR)×
분야계량경제학계량경제학
계열Regression modelRegression model
기원 연도20051984
창시자Primiceri (2005); Cogley & Sargent (2001, 2005)Doan, Litterman & Sims
유형Multivariate time-series model with drifting coefficientsMultivariate time-series model
원전Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821-852. DOI ↗Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100. DOI ↗
별칭TVP-VAR, time-varying VAR, TV-VAR, drifting-coefficient VARBVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
관련65
요약The Time-Varying Parameter VAR (TVP-VAR) model extends the standard vector autoregression by allowing the coefficients and error covariances to evolve gradually over time. Estimated via Bayesian methods and MCMC simulation, it captures how dynamic relationships between macroeconomic or financial variables shift across different economic regimes without requiring pre-specified break points.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.
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