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| Fourier Nonlinear ARDL (Fourier NARDL)× | Estimateur GMM d'Arellano-Bond× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2014–2020s | 1991 |
| Auteur d'origine≠ | Extension of Shin, Yu & Greenwood-Nimmo (2014) NARDL, incorporating Fourier terms from Becker, Enders & Lee (2006) | Manuel Arellano and Stephen Bond |
| Type≠ | Nonlinear cointegrating model with smooth break approximation | GMM estimator for dynamic panel data |
| Source fondatrice≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. link ↗ | 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 ↗ |
| Alias | Fourier NARDL, Fourier nonlinear ARDL, F-NARDL, Fourier asymmetric ARDL | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Fourier NARDL extends the Nonlinear ARDL (NARDL) bounds-testing framework by adding Fourier trigonometric terms to the error-correction equation, allowing the model to capture smooth, gradual structural breaks in the long-run relationship without requiring the researcher to know or specify the break date in advance. | 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. |
| ScholarGateJeu de données ↗ |
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