Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Modelul cu efecte aleatorii și puncte de ruptură structurale× | Model cu Efecte Aleatorii pe Panou× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1998–2000s | 1966 |
| Autorul original≠ | Bai & Perron (break detection); Baltagi (panel RE framework) | Balestra & Nerlove |
| Tip≠ | Panel regression with regime shifts | Panel data estimator |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative | 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 |
| Înrudite | 5 | 5 |
| Rezumat≠ | 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. |
| ScholarGateSet de date ↗ |
|
|