Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Estimatorul DOLS (Dynamic Ordinary Least Squares)× | Estimatorul Augmented Mean Group (AMG)× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1993 | 2010 |
| Autorul original≠ | Stock & Watson (1993); panel extension Kao & Chiang (2001) | Eberhardt & Teal; Bond & Eberhardt |
| Tip≠ | Cointegrating regression estimator | Heterogeneous panel data estimator |
| Sursa seminală≠ | Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820. DOI ↗ | Eberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford. link ↗ |
| Denumiri alternative≠ | DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS) | AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG) |
| Înrudite≠ | 5 | 4 |
| Rezumat≠ | Dynamic OLS is a cointegrating-regression estimator introduced by Stock and Watson (1993) that recovers the long-run relationship between I(1) variables. It augments the static regression with leads and lags of the differenced regressors, correcting endogeneity bias parametrically so that the long-run coefficient can be estimated by ordinary least squares. | 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. |
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