Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Mínims Quadrats Generalitzats (GLS)× | Mínims Quadrats Generalitzats de Panell (Panel GLS)× | |
|---|---|---|
| Camp≠ | Estadística | Econometria |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1935 | 1935 / developed for panels 1980s–1990s |
| Autor original≠ | Alexander Craig Aitken | Aitken (1935); extended to panel data by Baltagi and others |
| Tipus≠ | Linear estimator | Generalized linear regression |
| Font seminal≠ | Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Àlies≠ | GLS, Aitken estimator, EGLS, feasible GLS | Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel |
| Relacionats | 3 | 3 |
| Resum≠ | Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models. | 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. |
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