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Robuste OLS (OLS mit robusten Standardfehlern)×Quantile Regression×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr19801978
UrheberHalbert WhiteKoenker & Bassett
TypLinear regression with robust inferenceConditional quantile regression
Wegweisende QuelleWhite, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasnamenHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errorsconditional quantile regression, regression quantiles, Kantil Regresyon
Verwandt65
ZusammenfassungRobust 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateMethoden vergleichen: Robust OLS · Quantile Regression. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare