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| Modello a Effetti Casuali Panel× | Analisi dei dati panel× | |
|---|---|---|
| Campo | Econometria | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1966 | 1966–1978 |
| Ideatore≠ | Balestra & Nerlove | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) |
| Tipo≠ | Panel data estimator | Panel regression framework |
| Fonte seminale≠ | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 |
| Alias | random effects estimator, RE model, GLS random effects, error components model | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis |
| Correlati | 5 | 5 |
| Sintesi≠ | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. | 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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