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| Test dei Limiti Bayesiano ARDL× | Test di Cointegrazione di Engle-Granger× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 2001 (ARDL); Bayesian extension 2010s | 1987 |
| Ideatore≠ | Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature | Robert F. Engle and Clive W. J. Granger |
| Tipo≠ | Cointegration / bounds testing | Cointegration test |
| Fonte seminale≠ | 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 ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Alias | Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test | EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test |
| Correlati | 5 | 5 |
| Sintesi≠ | 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 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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