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Heteroskedastizitätsrobuste (HC) Standardfehler×Clusterrobuste Standardfehler×
FachgebietStatistikStatistik
FamilieRegression modelRegression model
Entstehungsjahr19801986
UrheberEicker; Huber; White (1980); MacKinnon & White (1985)Liang & Zeger (GEE sandwich); Cameron & Miller (practitioner synthesis)
TypRobust covariance estimator for linear regressionRobust variance estimation for regression
Wegweisende QuelleWhite, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817-838. DOI ↗Liang, K. Y. & Zeger, S. L. (1986). Longitudinal Data Analysis Using Generalized Linear Models. Biometrika, 73(1), 13-22. DOI ↗
Aliasnamenrobust standard errors, White standard errors, Huber-Eicker-White standard errors, sandwich standard errorsclustered standard errors, cluster-robust inference, clustered variance estimator, Küme Robust Standart Hatalar
Verwandt54
ZusammenfassungHeteroscedasticity-robust standard errors are a correction to the covariance matrix of an OLS regression that yields valid inference when the error variance is not constant. Introduced by Halbert White in 1980 and refined into the finite-sample variants HC1-HC4 by MacKinnon and White in 1985, they leave the coefficient estimates unchanged but rebuild the standard errors so that t and F tests remain trustworthy under heteroscedasticity.Cluster-robust standard errors correct the variance of regression coefficients when observations are correlated within clusters such as schools, hospitals, or regions. The clustered sandwich estimator grew out of Liang & Zeger's (1986) generalized estimating equations and was synthesized for applied work by Cameron & Miller (2015), delivering valid inference when ordinary standard errors would be too small.
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ScholarGateMethoden vergleichen: Heteroscedasticity-Robust Standard Errors · Cluster-Robust Standard Errors. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare