Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo de efectos fijos en panel× | OLS de Panel (Mínimos Cuadrados Ordinarios Agrupados)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1978 | 1986-2003 |
| Autor original≠ | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) | Classical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010) |
| Tipo≠ | Panel regression estimator | Linear panel regression |
| Fuente seminal | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Alias | within estimator, FE model, within-group estimator, LSDV model | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. | 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. |
| ScholarGateConjunto de datos ↗ |
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