Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de Chow pour la rupture structurelle× | Régression par Moindres Carrés Ordinaires (MCO)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1960 | 2019 |
| Auteur d'origine≠ | Gregory C. Chow | Wooldridge (textbook treatment); classical least squares |
| Type≠ | Test for structural break in regression coefficients | Linear regression |
| Source fondatrice≠ | Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Alias≠ | Chow breakpoint test, structural break test, Chow yapısal kırılma testi | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Apparentées≠ | 2 | 5 |
| Résumé≠ | The Chow test, introduced by Gregory Chow in 1960, checks whether the coefficients of a linear regression are the same across two subsamples — that is, whether a structural break occurs at a known point such as a policy change, crisis, or regime shift. It compares the fit of a single pooled regression with the combined fit of two separate regressions; a large improvement from splitting indicates the relationship differs between the two periods or groups. | 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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