Porovnať metódy
Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Model s náhodnými efektmi (Random Effects Panel Model)× | Regresia metódou najmenších štvorcov (OLS)× | |
|---|---|---|
| Odbor | Ekonometria | Ekonometria |
| Rodina | Regression model | Regression model |
| Rok vzniku≠ | 1978 | 2019 |
| Tvorca≠ | Baltagi (textbook treatment); Hausman specification test | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Panel data regression | Linear regression |
| Pôvodný zdroj≠ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Ďalšie názvy | random effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler Modeli | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Príbuzné | 5 | 5 |
| Zhrnutie≠ | 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. | 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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