Порівняння методів

	Байєсівський тест на одиничний корінь Філіппса-Перрона	Байєсівська модель векторної авторегресії (BVAR)
Галузь	Економетрика	Економетрика
Родина	Regression model	Regression model
Рік появи	1988 / early 1990s	1984
Автор методу	Phillips & Perron (classical test, 1988); Bayesian framework: Sims & Uhlig (1991)	Doan, Litterman & Sims
Тип	Unit root test (Bayesian)	Multivariate time-series model
Основоположне джерело	Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346.	Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100.
Інші назви	Bayesian PP test, Bayesian Phillips-Perron test, Bayesian nonparametric unit root test, Bayes PP unit root	BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model
Пов'язані	5	5
Підсумок	The Bayesian Phillips-Perron unit root test combines the nonparametric long-run variance correction of the classical Phillips-Perron test with a Bayesian inferential framework. Instead of a p-value, it yields a posterior probability or Bayes factor quantifying evidence for or against a unit root, allowing researchers to incorporate prior economic knowledge and obtain probability statements directly about the persistence of a time series.	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.