Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Modeli ya Athari Nasibu ya Mapumziko ya Muundo× | Mfumo wa Athari Nasibu za Paneli× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1998–2000s | 1966 |
| Mwanzilishi≠ | Bai & Perron (break detection); Baltagi (panel RE framework) | Balestra & Nerlove |
| Aina≠ | Panel regression with regime shifts | Panel data estimator |
| Chanzo asilia≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ |
| Majina mbadala | RE model with structural breaks, break-adjusted random effects, random effects break model, panel RE with regime shifts | random effects estimator, RE model, GLS random effects, error components model |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | The structural break random effects model extends standard panel RE estimation by allowing one or more breakpoints at which slope coefficients or error variances shift across time. It combines structural change detection (e.g., Bai-Perron) with the GLS-based random effects estimator, producing regime-specific parameter estimates while retaining the efficiency gains of pooling individual-level variation as random draws from a common distribution. | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. |
| ScholarGateSeti ya data ↗ |
|
|