Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Furjē dinamiskais paneļdatu modelis× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2004-2012 | 1991 |
| Autors≠ | Enders & Lee (2012); Becker, Enders & Hurn (2004) | Manuel Arellano and Stephen Bond |
| Tips≠ | Dynamic panel model with Fourier approximation | GMM estimator for dynamic panel data |
| Pirmavots≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. 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 | Fourier dynamic panel, Fourier DPDM, smooth break dynamic panel, trigonometric dynamic panel | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | The Fourier dynamic panel data model extends standard dynamic panel specifications by incorporating low-frequency trigonometric (Fourier) terms to flexibly capture smooth, gradual structural breaks or time-varying patterns in the data, without requiring knowledge of the exact number or timing of breaks. | 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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