Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Structural Break WLS× | GLS ya Mabadiliko ya Kimuundo× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1998 (break framework); WLS long-established | 1998 (structural break GLS formalization) |
| Mwanzilishi≠ | Bai & Perron (structural break framework); WLS classical | Bai & Perron (1998); GLS framework by Aitken (1936) |
| Aina≠ | Weighted regression with regime shifts | Regression estimator |
| Chanzo asilia≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78. DOI ↗ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ |
| Majina mbadala | WLS with structural change, break-corrected WLS, segmented WLS, structural break weighted regression | GLS with structural breaks, break-adjusted GLS, structural change GLS, regime-switching GLS |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | 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. | Structural Break GLS combines Generalized Least Squares estimation with explicit allowance for regime shifts in the data-generating process. The method estimates separate coefficient vectors for each segment defined by detected break dates while correcting for non-spherical errors — heteroscedasticity or autocorrelation — that frequently accompany structural change, yielding consistent and efficient estimates across all regimes. |
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