Comparer des méthodes

	Structural Break WLS	Moindres Carrés Pondérés Robustes (Robust WLS)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1998 (break framework); WLS long-established	1964/1981
Auteur d'origine	Bai & Perron (structural break framework); WLS classical	Huber, P. J.
Type	Weighted regression with regime shifts	Robust weighted regression
Source fondatrice	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78.	Huber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054
Alias	WLS with structural change, break-corrected WLS, segmented WLS, structural break weighted regression	robust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regression
Apparentées	5	5
Résumé	Structural Break WLS combines Weighted Least Squares estimation with explicit detection and correction for structural breaks — abrupt regime shifts — in the data. By identifying break points and assigning observation-level weights that account for heteroscedasticity within and across regimes, the estimator delivers consistent, efficient coefficient estimates even when the error variance changes dramatically at a break.	Robust WLS combines weighted least squares — which corrects for known or estimated heteroscedasticity — with robust M-estimation that down-weights influential outliers. The result is a regression estimator that is simultaneously efficient under non-constant error variance and resistant to observations that would otherwise distort coefficient estimates.