Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Estimateur Augmenté du Groupe Moyen (AMG)× | Régression par Moindres Carrés Ordinaires (MCO)× | Tests de cointégration de panel (Pedroni, Kao, Westerlund)× | |
|---|---|---|---|
| Domaine | Économétrie | Économétrie | Économétrie |
| Famille | Regression model | Regression model | Regression model |
| Année d'origine≠ | 2010 | 2019 | 2004 |
| Auteur d'origine≠ | Eberhardt & Teal; Bond & Eberhardt | Wooldridge (textbook treatment); classical least squares | Pedroni; Kao; Westerlund |
| Type≠ | Heterogeneous panel data estimator | Linear regression | Panel cointegration test |
| Source fondatrice≠ | Eberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford. link ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | Pedroni, P. (2004). Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis. Econometric Theory, 20(3), 597–625. DOI ↗ |
| Alias≠ | AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | Pedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium tests |
| Apparentées≠ | 4 | 5 | 3 |
| Résumé≠ | The Augmented Mean Group estimator, developed by Eberhardt and Teal (2010), is a panel data method for estimating heterogeneous slope coefficients in the presence of cross-sectional dependence. It approximates the unobserved common dynamic process driving all units and folds it into unit-by-unit regressions, then averages the results. | 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). | Panel cointegration tests check whether a set of integrated variables share a stable long-run equilibrium relationship across a panel of cross-sectional units. Pedroni (1999, 2004) provides heterogeneous-panel tests with seven statistics, Kao (1999) gives an ADF-based homogeneous-panel test, and Westerlund (2007) adds error-correction-based tests robust to structural breaks and cross-sectional dependence. |
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