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Model Bayesowski VAR (BVAR)×Autoregresja Wektorowa (VAR)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19841980
TwórcaDoan, Litterman & SimsChristopher A. Sims
TypMultivariate time-series modelMultivariate time-series model
Źródło pierwotneDoan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100. DOI ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Inne nazwyBVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR modelVAR, VAR model, vector autoregressive model, multivariate autoregression
Pokrewne55
PodsumowanieThe 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.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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