Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| GLS con Rupturas Estructurales× | Mínimos Cuadrados Generalizados Robustos (Robust GLS)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1998 (structural break GLS formalization) | 1936 / 1980 |
| Autor original≠ | Bai & Perron (1998); GLS framework by Aitken (1936) | Aitken (GLS theory, 1936); White (robust covariance, 1980) |
| Tipo≠ | Regression estimator | Robust linear regression |
| Fuente seminal≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381 |
| Alias | GLS with structural breaks, break-adjusted GLS, structural change GLS, regime-switching GLS | robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS |
| Relacionados≠ | 6 | 5 |
| Resumen≠ | Structural Break GLS combines Generalized Least Squares estimation with explicit allowance for regime shifts in the data-generating process. The method estimates separate coefficient vectors for each segment defined by detected break dates while correcting for non-spherical errors — heteroscedasticity or autocorrelation — that frequently accompany structural change, yielding consistent and efficient estimates across all regimes. | Robust GLS extends classical Generalized Least Squares by pairing GLS coefficient estimation with heteroscedasticity- and autocorrelation-consistent (HAC) standard errors, or by using M-estimation within the GLS framework. It corrects for non-spherical errors — heteroscedasticity, autocorrelation, or both — while also guarding inference against misspecification of the error covariance structure. |
| ScholarGateConjunto de datos ↗ |
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