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| Analyse de données de panel× | Moindres carrés ordinaires sur données de panel (Pooled OLS)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1966–1978 | 1986-2003 |
| Auteur d'origine≠ | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) | Classical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010) |
| Type≠ | Panel regression framework | Linear panel regression |
| Source fondatrice≠ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Alias | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | 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. | Panel OLS — also called Pooled OLS — applies the classical ordinary least squares estimator to panel data by stacking all cross-sectional units and time periods into a single sample. It estimates one common set of slope coefficients under the assumption that the intercept and slopes are homogeneous across units and time. |
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