Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Robust Difference GMM× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 / 2005 | 1991 |
| Autors≠ | Arellano & Bond (1991); robust inference extension via Windmeijer (2005) | Manuel Arellano and Stephen Bond |
| Tips≠ | GMM estimator with robust standard errors | Dynamic panel GMM estimator |
| Pirmavots≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The 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 | robust Arellano-Bond estimator, difference GMM with robust SE, HAC difference GMM, AB-GMM robust | Arellano-Bond GMM, AB-GMM, difference GMM estimator, dynamic panel GMM |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Robust Difference GMM applies the Arellano-Bond first-difference GMM estimator with heteroscedasticity- and autocorrelation-consistent (HAC) or Windmeijer-corrected standard errors, delivering valid inference for dynamic panel models even when error variances are non-constant or residuals are cross-sectionally correlated. | The Arellano-Bond GMM estimator addresses the two core problems of dynamic panel models — individual fixed effects correlated with the regressors, and the endogeneity introduced by a lagged dependent variable — by first-differencing to remove fixed effects and then using lagged levels of the dependent variable as internal instruments. |
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