Porównaj metody
Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.
| Robustowy test Hausmana× | Regresja metodą najmniejszych kwadratów (OLS)× | |
|---|---|---|
| Dziedzina≠ | Statystyka | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1978 | 2019 |
| Twórca≠ | Hausman (1978); robust variant after Arellano (1993) | Wooldridge (textbook treatment); classical least squares |
| Typ≠ | Panel model specification test | Linear regression |
| Źródło pierwotne≠ | 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 |
| Inne nazwy≠ | robust hausman specification test, cluster-robust hausman test, Robust Hausman Testi | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | The Robust Hausman Test is a heteroscedasticity- and autocorrelation-robust version of the Hausman specification test, used to choose between fixed-effects and random-effects estimators in panel-data models. It builds on Hausman's 1978 test and the robust treatment of correlated effects developed by Arellano (1993). | 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). |
| ScholarGateZbiór danych ↗ |
|
|