Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Arellano-Bond GMM novērtētājs× | Fiksēto efektu paneļa modelis (FE)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 | 1978 |
| Autors≠ | Manuel Arellano and Stephen Bond | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Tips≠ | Dynamic panel GMM estimator | Panel regression estimator |
| 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 ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Citi nosaukumi | Arellano-Bond GMM, AB-GMM, difference GMM estimator, dynamic panel GMM | within estimator, FE model, within-group estimator, LSDV model |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. |
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