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Structural Break WLS×Mínimos Quadrados Ponderados (WLS)×
ÁreaEconometriaEstatística
FamíliaRegression modelRegression model
Ano de origem1998 (break framework); WLS long-established1935
Autor originalBai & Perron (structural break framework); WLS classicalAlexander Craig Aitken
TipoWeighted regression with regime shiftsWeighted linear estimator
Fonte seminalBai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Outros nomesWLS with structural change, break-corrected WLS, segmented WLS, structural break weighted regressionWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squares
Relacionados53
ResumoStructural 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.Weighted Least Squares is a generalization of Ordinary Least Squares (OLS) regression that assigns each observation a weight inversely proportional to its error variance, thereby down-weighting high-variance data points and up-weighting precise ones. Introduced in its general matrix form by Alexander Craig Aitken in 1935, WLS is the canonical remedy when heteroscedasticity is present and the error variance structure is known or can be reliably estimated.
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ScholarGateComparar métodos: Structural Break WLS · Weighted Least Squares. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare