Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo Autorregresivo de Transición Suave (STAR)× | Regresión de Umbral× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1994 | 2000 |
| Autor original≠ | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) | Bruce E. Hansen |
| Tipo≠ | Nonlinear time-series regime-switching model | Nonlinear regime-switching regression |
| Fuente seminal≠ | Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗ | Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗ |
| Alias≠ | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR | threshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression) |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations. | Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships. |
| ScholarGateConjunto de datos ↗ |
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