Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Robustais Arellano-Bonda GMM novērtētājs× | Sistēmas GMM panelim (Blundell-Bonda novērtētājs)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 | 1998 |
| Autors≠ | Arellano & Bond (1991); robust inference extensions by Windmeijer (2005) | Blundell & Bond (1998); Arellano & Bover (1995) |
| Tips≠ | Dynamic panel GMM estimator with robust inference | 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. The Review of Economic Studies, 58(2), 277-297. DOI ↗ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. DOI ↗ |
| Citi nosaukumi | Robust Difference GMM, AB-GMM with robust standard errors, Robust first-difference GMM, Arellano-Bond robust estimator | System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | The Robust Arellano-Bond GMM estimator applies the Arellano-Bond first-difference GMM approach to dynamic panel data while computing heteroscedasticity- and autocorrelation-consistent (robust) standard errors. This combination handles the Nickell bias from lagged dependent variables and simultaneously yields reliable inference when error variances differ across units or periods. | Panel System GMM is a two-equation GMM estimator for dynamic panel data that stacks the differenced equation (using lagged levels as instruments) with the levels equation (using lagged differences as instruments). Developed by Blundell and Bond (1998) on the foundation of Arellano and Bover (1995), it is the preferred tool when the lagged dependent variable is highly persistent or individual effects are large. |
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