Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Paneeli yleistetty pienimmän neliösumman menetelmä (Paneeli GLS)× | Robust OLS (OLS, jossa robustit keskivirheet)× | |
|---|---|---|
| Tieteenala | Ekonometria | Ekonometria |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1935 / developed for panels 1980s–1990s | 1980 |
| Kehittäjä≠ | Aitken (1935); extended to panel data by Baltagi and others | Halbert White |
| Tyyppi≠ | Generalized linear regression | Linear regression with robust inference |
| Alkuperäislähde≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗ |
| Rinnakkaisnimet | Panel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel | HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors |
| Liittyvät≠ | 3 | 6 |
| Tiivistelmä≠ | 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. | Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations. |
| ScholarGateAineisto ↗ |
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