Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Nelineārs fiksēto efektu modelis× | Modelis ar fiksētajiem efektiem× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1984 | 1971–1978 |
| Autors≠ | Gary Chamberlain | Mundlak (1978); Nerlove (1971); classical panel econometrics |
| 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 ↗ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002 |
| Citi nosaukumi | nonlinear FE model, NLFE, conditional fixed effects model, incidental parameters model | FE model, within estimator, least squares dummy variable, LSDV regression |
| 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 fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate intercept, FE isolates the causal effect of within-unit variation and eliminates omitted-variable bias from time-constant confounders. |
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