Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Random Effects Panel Model× | Hausmana specifikācijas tests (FE vs RE)× | Fiksēto efektu paneļa datu modelis× | |
|---|---|---|---|
| Nozare | Ekonometrija | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model | Regression model |
| Izcelsmes gads≠ | 1978 | 1978 | 2014 |
| Autors≠ | Baltagi (textbook treatment); Hausman specification test | Jerry A. Hausman | Hsiao (textbook treatment); within transformation of panel data |
| Tips≠ | Panel data regression | Specification test for panel data models | Panel data regression |
| Pirmavots≠ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Citi nosaukumi | random effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler Modeli | Hausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE) | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Saistītās | 5 | 5 | 5 |
| Kopsavilkums≠ | The random effects model is a panel data estimator that explains an outcome using both within-unit and between-unit variation, treating the unobserved unit-specific heterogeneity as a random, normally distributed term rather than a fixed parameter. Its validity is judged with the Hausman (1978) specification test, and it is developed in standard treatments such as Baltagi's Econometric Analysis of Panel Data. | 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 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). |
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