Vertaile menetelmiä
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| Bayesiläinen ARDL-raja-arvotesti× | Bayesiläinen VECM (Bayesian VECM)× | |
|---|---|---|
| Tieteenala | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 2001 (ARDL); Bayesian extension 2010s | 2002–2005 |
| Kehittäjä≠ | Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature | Kleibergen & Paap; Villani |
| Tyyppi≠ | Cointegration / bounds testing | Bayesian multivariate time series model |
| Alkuperäislähde≠ | 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 ↗ |
| Rinnakkaisnimet | Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test | Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction |
| Liittyvät | 5 | 5 |
| Tiivistelmä≠ | 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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