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| Modelo ARDL no lineal (NARDL)× | Modelo de Corrección de Errores Vectorial (VECM)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 2014 | 1987 |
| Autor original≠ | Shin, Yu & Greenwood-Nimmo | Robert F. Engle and Clive W. J. Granger |
| Tipo≠ | Nonlinear cointegration model | Multivariate time-series model |
| Fuente seminal≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. link ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Alias | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Relacionados | 5 | 5 |
| Resumen≠ | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
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