Сравнение методов

	Байесовская модель структурной векторной авторегрессии (B-SVAR)	Байесовский ARDL-тест на коинтеграцию
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1998–2005	2001 (ARDL); Bayesian extension 2010s
Автор метода	Sims & Zha (1998); Uhlig (2005) for sign-restriction identification	Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature
Тип	Structural multivariate time-series model	Cointegration / bounds testing
Основополагающий источник	Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968.	Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
Другие названия	Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR	Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test
Связанные	6	5
Сводка	The Bayesian Structural Vector Autoregression model combines the structural identification of SVAR with Bayesian prior distributions over parameters. It estimates causal impulse responses between multiple time series while incorporating prior economic knowledge and producing full posterior uncertainty bands rather than point estimates alone.	The Bayesian ARDL Bounds Test extends the classical Pesaran-Shin-Smith (2001) bounds testing approach to cointegration by embedding it within a Bayesian inferential framework. Instead of relying on frequentist F- and t-statistics with tabulated critical values, the researcher specifies prior distributions on the model parameters and derives posterior evidence of a long-run level relationship between variables that may be integrated of order zero or one.