Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à effets fixes× | Analyse de données de panel× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1971–1978 | 1966–1978 |
| Auteur d'origine≠ | Mundlak (1978); Nerlove (1971); classical panel econometrics | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) |
| Type≠ | Panel regression estimator | Panel regression framework |
| Source fondatrice | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002 | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 |
| Alias | FE model, within estimator, least squares dummy variable, LSDV regression | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis |
| Apparentées | 5 | 5 |
| Résumé≠ | 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. | Panel data analysis models data that track multiple units — countries, firms, individuals — over time, enabling researchers to control for unobserved unit-level heterogeneity that would otherwise bias cross-sectional or time-series estimates. The two core specifications are fixed effects and random effects, selected via the Hausman test. |
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