Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| GMM atšķirību metode (Arellano–Bonda novērtētājs)× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads | 1991 | 1991 |
| Autors | Manuel Arellano and Stephen Bond | Manuel Arellano and Stephen Bond |
| Tips≠ | GMM panel estimator | GMM estimator for dynamic panel data |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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 Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous. |
| ScholarGateDatu kopa ↗ |
|
|