Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālas pārtraukumas atšķirības GMM× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991 / 1998 | 1991 |
| Autors≠ | Arellano & Bond (Difference GMM); Bai & Perron (structural break testing) | Manuel Arellano and Stephen Bond |
| Tips≠ | Dynamic panel estimator with structural breaks | 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 ↗ | 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 | Difference GMM with structural breaks, break-augmented Arellano-Bond GMM, dynamic panel GMM with regime shifts, structural change Difference GMM | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Structural Break Difference GMM extends the Arellano-Bond first-difference GMM estimator to dynamic panel settings where the data-generating process shifts at one or more unknown breakpoints. By explicitly incorporating break indicators or allowing regime-specific parameters, the estimator avoids the biased coefficient and invalid moment conditions that arise when a structural change is ignored in a standard Difference GMM fit. | 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. |
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