Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| GLS con Rupturas Estructurales× | Mínimos Cuadrados Generalizados para Datos de Panel (Panel GLS)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1998 (structural break GLS formalization) | 1935 / developed for panels 1980s–1990s |
| Autor original≠ | Bai & Perron (1998); GLS framework by Aitken (1936) | Aitken (1935); extended to panel data by Baltagi and others |
| Tipo≠ | Regression estimator | Generalized linear regression |
| Fuente seminal≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Alias | GLS with structural breaks, break-adjusted GLS, structural change GLS, regime-switching GLS | Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel |
| Relacionados≠ | 6 | 3 |
| 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. | Panel GLS is a regression method for longitudinal data that explicitly models the non-spherical error structure — heteroscedasticity across units and serial correlation within units — to recover efficient coefficient estimates. Unlike OLS, it weights observations by the inverse of the error covariance matrix, yielding the Best Linear Unbiased Estimator when the error structure is correctly specified. |
| ScholarGateConjunto de datos ↗ |
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