Comparer des méthodes

	Erreurs-types robustes à l'hétéroscédasticité (HC)	Régression quantile
Domaine	Statistique	Économétrie
Famille	Regression model	Regression model
Année d'origine	1980	1978
Auteur d'origine	Eicker; Huber; White (1980); MacKinnon & White (1985)	Koenker & Bassett
Type	Robust covariance estimator for linear regression	Conditional quantile regression
Source fondatrice	White, H. (1980). A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity. Econometrica, 48(4), 817-838.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	robust standard errors, White standard errors, Huber-Eicker-White standard errors, sandwich standard errors	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	5	5
Résumé	Heteroscedasticity-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.	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.