Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Diferența GMM (Estimator Arellano-Bond)× | Modelul de date de panel dinamic× | |
|---|---|---|
| Domeniu | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1991 | 1988–1991 |
| Autorul original≠ | Manuel Arellano and Stephen Bond | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| Tip≠ | GMM panel estimator | Dynamic regression / GMM estimation |
| Sursa seminală | 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 ↗ |
| Denumiri alternative | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| Înrudite | 5 | 5 |
| Rezumat≠ | 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. | 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. |
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