Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Робастни обобщени най-малки квадрати (Robust GLS)× | Обобщен метод на най-малките квадрати за панелни данни (Panel GLS)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1936 / 1980 | 1935 / developed for panels 1980s–1990s |
| Създател≠ | Aitken (GLS theory, 1936); White (robust covariance, 1980) | Aitken (1935); extended to panel data by Baltagi and others |
| Тип≠ | Robust linear regression | Generalized linear regression |
| Основополагащ източник≠ | Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Други названия | robust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS | Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel |
| Свързани≠ | 5 | 3 |
| Резюме≠ | 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. | 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. |
| ScholarGateНабор от данни ↗ |
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