Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle à effets fixes pour données de panel× | Régression par Moindres Carrés Ordinaires (MCO)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2014 | 2019 |
| Auteur d'origine≠ | Hsiao (textbook treatment); within transformation of panel data | Wooldridge (textbook treatment); classical least squares |
| Type≠ | Panel data regression | Linear regression |
| Source fondatrice≠ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Alias | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Apparentées | 5 | 5 |
| Résumé≠ | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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