Порівняння методів

	Байєсівський тест на одиничний корінь ADF	Байєсівська модель векторної авторегресії (BVAR)
Галузь	Економетрика	Економетрика
Родина	Regression model	Regression model
Рік появи	1991–1992	1984
Автор методу	Sims & Uhlig (1991); Koop, Osiewalski & Steel (1992)	Doan, Litterman & Sims
Тип	Bayesian hypothesis test	Multivariate time-series model
Основоположне джерело	Sims, C. A., & Uhlig, H. (1991). Understanding unit rooters: A helicopter tour. Econometrica, 59(6), 1591–1599.	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.
Інші назви	Bayesian ADF test, Bayesian unit root test, Bayesian Dickey-Fuller, BADF	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Пов'язані	6	5
Підсумок	The Bayesian Augmented Dickey-Fuller (BADF) unit root test re-frames the classical ADF test within a Bayesian framework. Rather than computing a frequentist p-value, it quantifies evidence for or against a unit root by comparing posterior probabilities or Bayes factors under the null (unit root) and alternative (stationarity) hypotheses, incorporating prior beliefs about the autoregressive parameter.	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.