Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de Vector Autorregresivo Estructural Bayesiano (B-SVAR)× | Prueba Bayesiana de Límites ARDL× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1998–2005 | 2001 (ARDL); Bayesian extension 2010s |
| Autor original≠ | Sims & Zha (1998); Uhlig (2005) for sign-restriction identification | Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature |
| Tipo≠ | Structural multivariate time-series model | Cointegration / bounds testing |
| Fuente seminal≠ | Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968. DOI ↗ | 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 ↗ |
| Alias | Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR | Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test |
| Relacionados≠ | 6 | 5 |
| Resumen≠ | The Bayesian Structural Vector Autoregression model combines the structural identification of SVAR with Bayesian prior distributions over parameters. It estimates causal impulse responses between multiple time series while incorporating prior economic knowledge and producing full posterior uncertainty bands rather than point estimates alone. | 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. |
| ScholarGateConjunto de datos ↗ |
|
|