Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Robustní model náhodných efektů×Robustní analýza panelových dat×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku1980s–2000s1987
TvůrceWooldridge; White (sandwich covariance); ArellanoArellano (1987); White (1980) heteroscedasticity-consistent framework
TypPanel GLS estimator with robust inferenceRobust estimation / inference correction
Původní zdrojWooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗
Další názvyrobust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RErobust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimator
Příbuzné56
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.Robust panel data analysis applies standard panel estimators — fixed effects, random effects, or pooled OLS — while replacing conventional standard errors with cluster-robust or heteroscedasticity-consistent (HC) variants. The point estimates remain unchanged; what changes is the variance-covariance matrix used for inference, making t-tests and F-tests valid even when errors are heteroscedastic or correlated within cross-sectional units over time.
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  3. PUBLISHED

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ScholarGatePorovnat metody: Robust Random Effects Model · Robust Panel Data Analysis. Získáno 2026-06-15 z https://scholargate.app/cs/compare