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Robustní model náhodných efektů×Panelová metoda zobecněných nejmenších čtverců (Panel GLS)×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku1980s–2000s1935 / developed for panels 1980s–1990s
TvůrceWooldridge; White (sandwich covariance); ArellanoAitken (1935); extended to panel data by Baltagi and others
TypPanel GLS estimator with robust inferenceGeneralized linear regression
Původní zdrojWooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
Další názvyrobust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust REPanel GLS, Generalized Least Squares for panel data, FGLS panel, feasible GLS panel
Příbuzné53
ShrnutíThe Robust Random Effects model estimates panel data relationships using the GLS random effects estimator while replacing the conventional standard errors with sandwich (heteroscedasticity- and cluster-robust) variance estimates. This protects inference against arbitrary within-group correlation and heteroscedasticity without discarding the efficiency gains of random effects when unit-specific effects are genuinely uncorrelated with the regressors.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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ScholarGatePorovnat metody: Robust Random Effects Model · Panel GLS. Získáno 2026-06-15 z https://scholargate.app/cs/compare