방법 비교

	베이지안 벡터 자기회귀 (BVAR)	Vector Autoregression (VAR) Model
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	1986	2005
창시자	Litterman (1986); Bańbura, Giannone & Reichlin (2010)	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
유형	Bayesian multivariate time-series model	Multivariate time-series model
원전	Litterman, R. B. (1986). Forecasting with Bayesian Vector Autoregressions—Five Years of Experience. Journal of Business & Economic Statistics, 4(1), 25-38.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
별칭	BVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR)	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
관련	5	4
요약	Bayesian VAR adds Minnesota or other prior distributions to a vector autoregressive model to control over-parameterisation. Introduced by Litterman (1986) and extended to high dimensions by Bańbura, Giannone and Reichlin (2010), it outperforms classical VAR on short series and high-dimensional macroeconomic forecasts.	Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).