Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Fiksēto efektu paneļa modelis (FE)× | Panel OLS (apvienotie parastie mazākie kvadrāti)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1978 | 1986-2003 |
| Autors≠ | 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) |
| Tips≠ | Panel regression estimator | Linear panel regression |
| Pirmavots | 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 |
| Citi nosaukumi | within estimator, FE model, within-group estimator, LSDV model | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | 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. |
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