Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Nelineārs fiksēto efektu modelis× | Fiksēto efektu paneļa modelis (FE)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1984 | 1978 |
| Autors≠ | Gary Chamberlain | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Tips≠ | Panel data estimator | Panel regression estimator |
| Pirmavots≠ | Chamberlain, G. (1984). Panel data. In Z. Griliches & M. D. Intriligator (Eds.), Handbook of Econometrics (Vol. 2, pp. 1247–1318). Elsevier. link ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Citi nosaukumi | nonlinear FE model, NLFE, conditional fixed effects model, incidental parameters model | within estimator, FE model, within-group estimator, LSDV model |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | The nonlinear fixed effects model extends fixed effects panel estimation to outcomes governed by nonlinear response functions — such as binary, count, or censored outcomes — while absorbing unobserved individual heterogeneity through unit-specific intercepts. Key special cases include conditional logit for binary outcomes and Poisson fixed effects for count data. | 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. |
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