Сравнение методов

	Байесовский тест на единичный корень ADF	Модель Байесовского векторного авторегрессионного анализа (BVAR)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1991–1992	1984
Автор метода	Sims & Uhlig (1991); Koop, Osiewalski & Steel (1992)	Doan, Litterman & Sims
Тип	Bayesian hypothesis test	Multivariate time-series model
Основополагающий источник	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.
Другие названия	Bayesian ADF test, Bayesian unit root test, Bayesian Dickey-Fuller, BADF	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Связанные	6	5
Сводка	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.