Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Estimation par la méthode généralisée des moments (GMM)× | Régression par Moindres Carrés Ordinaires (MCO)× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1982 | 2019 |
| Auteur d'origine≠ | Lars Peter Hansen; Arellano & Bond (dynamic panel) | Wooldridge (textbook treatment); classical least squares |
| Type≠ | Moment-condition estimator | Linear regression |
| Source fondatrice≠ | Hansen, L. P. (1982). Large Sample Properties of Generalized Method of Moments Estimators. Econometrica, 50(4), 1029-1054. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Alias | generalized method of moments, GMM, Arellano-Bond estimator, Genelleştirilmiş Momentler Yöntemi (GMM) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Apparentées | 5 | 5 |
| Résumé≠ | The Generalized Method of Moments is a general-purpose econometric estimator that recovers parameters from population moment conditions, introduced by Lars Peter Hansen in 1982. It is widely used for instrumental-variable estimation, dynamic panel-data models (the Arellano-Bond estimator), and time-series applications. | 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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