Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Model d'efectes aleatoris de panell× | Panell OLS (Mínims Quadrats Ordinaris Agrupats)× | |
|---|---|---|
| Camp | Econometria | Econometria |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1966 | 1986-2003 |
| Autor original≠ | Balestra & Nerlove | Classical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010) |
| Tipus≠ | Panel data estimator | Linear panel regression |
| Font seminal≠ | 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 ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Àlies | random effects estimator, RE model, GLS random effects, error components model | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| Relacionats≠ | 5 | 4 |
| Resum≠ | 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. | Panel OLS — also called Pooled OLS — applies the classical ordinary least squares estimator to panel data by stacking all cross-sectional units and time periods into a single sample. It estimates one common set of slope coefficients under the assumption that the intercept and slopes are homogeneous across units and time. |
| ScholarGateConjunt de dades ↗ |
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