Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Testet kufizues ARDL Bayesian× | Modeli Bayesian i Korrigjimit të Gabimeve Vektoriale (Bayesian VECM)× | |
|---|---|---|
| Fusha | Ekonometri | Ekonometri |
| Familja | Regression model | Regression model |
| Viti i origjinës≠ | 2001 (ARDL); Bayesian extension 2010s | 2002–2005 |
| Krijuesi≠ | Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature | Kleibergen & Paap; Villani |
| Lloji≠ | Cointegration / bounds testing | Bayesian multivariate time series model |
| Burimi themelues≠ | 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. DOI ↗ | Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249. DOI ↗ |
| Emërtime të tjera | Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test | Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction |
| Të lidhura | 5 | 5 |
| Përmbledhja≠ | 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. |
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