Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Prueba de especificación de Hausman (EF vs EA)× | Modelo de Efectos Aleatorios para Datos de Panel× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1978 | 2021 |
| Autor original≠ | Jerry A. Hausman | Baltagi (textbook treatment); classical random-effects panel estimator |
| Tipo≠ | Specification test for panel data models | Panel data regression |
| Fuente seminal≠ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. DOI ↗ |
| Alias | Hausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE) | random effects panel model, RE estimator, GLS random effects, Panel Veri — Rassal Etkiler Modeli |
| Relacionados | 5 | 5 |
| Resumen≠ | The Hausman test is a specification test, introduced by Jerry A. Hausman in 1978, that decides between the fixed-effects (FE) and random-effects (RE) estimators in panel data models. The null hypothesis is that the random-effects estimator is consistent and efficient and should be preferred; the alternative is that random effects is inconsistent and fixed effects is required because the unit-specific effects are correlated with the explanatory variables. | 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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