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Байесовский ARDL-тест на коинтеграцию×Тест на коинтеграцию Энгла-Грэнджера×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления2001 (ARDL); Bayesian extension 2010s1987
Автор методаPesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literatureRobert F. Engle and Clive W. J. Granger
ТипCointegration / bounds testingCointegration test
Основополагающий источникPesaran, 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. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Другие названияBayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds testEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test
Связанные55
СводкаThe 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 Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment.
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  2. 2 Источники
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  1. v1
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ScholarGateСравнение методов: Bayesian ARDL Bounds Test · Engle-Granger Cointegration Test. Получено 2026-06-18 из https://scholargate.app/ru/compare