Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Régression linéaire simple sur données de panel× | Modèle à effets aléatoires pour données de panel× | |
|---|---|---|
| Domaine≠ | Statistique | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1986 | 2021 |
| Auteur d'origine≠ | Hsiao (1986); Baltagi (seminal textbook treatments) | Baltagi (textbook treatment); classical random-effects panel estimator |
| Type≠ | Linear regression (panel data) | Panel data regression |
| Source fondatrice≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. DOI ↗ |
| Alias | panel SLR, longitudinal simple regression, two-way panel simple regression, fixed-effects simple linear regression | random effects panel model, RE estimator, GLS random effects, Panel Veri — Rassal Etkiler Modeli |
| Apparentées | 5 | 5 |
| Résumé≠ | Panel simple linear regression models a continuous outcome as a linear function of a single predictor using data that track the same entities (individuals, firms, countries) across multiple time periods. It separates within-entity variation from between-entity variation, enabling control for unobserved time-invariant characteristics that would confound a plain cross-sectional regression. | The Random Effects model is a panel-data regression that treats unobserved individual heterogeneity as a random component drawn from a common distribution, rather than a separate parameter for each unit. It is a standard estimator in panel econometrics, developed in textbook treatments such as Baltagi's Econometric Analysis of Panel Data (2021). |
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