Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Dynamisch paneeldatamodel× | Difference GMM (Arellano-Bond Estimator)× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1988–1991 | 1991 |
| Grondlegger≠ | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) | Manuel Arellano and Stephen Bond |
| Type≠ | Dynamic regression / GMM estimation | GMM panel estimator |
| Oorspronkelijke bron | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. DOI ↗ |
| Aliassen | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| Verwant | 5 | 5 |
| Samenvatting≠ | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. | Difference GMM, introduced by Arellano and Bond (1991), estimates dynamic panel data models by first-differencing the equation to remove fixed effects, then using lagged levels of the endogenous variables as GMM instruments. It is the standard approach when a lagged dependent variable or other endogenous regressors are present in a panel with many units and few time periods. |
| ScholarGateGegevensset ↗ |
|
|