Сравнение методов

	Байесовский ARDL-тест на коинтеграцию	Байесовская модель векторной коррекции ошибок (Bayesian VECM)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	2001 (ARDL); Bayesian extension 2010s	2002–2005
Автор метода	Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature	Kleibergen & Paap; Villani
Тип	Cointegration / bounds testing	Bayesian multivariate time series model
Основополагающий источник	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.	Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249.
Другие названия	Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test	Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction
Связанные	5	5
Сводка	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.	The Bayesian VECM combines the classical Vector Error Correction Model — which captures both short-run dynamics and long-run cointegrating relationships among non-stationary multivariate time series — with Bayesian prior distributions over the cointegrating rank and coefficient matrices. This allows principled uncertainty quantification, incorporation of economic theory as priors, and coherent inference even in small samples.