Salīdzināt metodes
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| Sistēmas vispārīgie momentu metodes (GMM) ar laikā mainīgiem parametriem× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1998 (System GMM); TVP extensions in applied literature thereafter | 1991 |
| Autors≠ | Blundell & Bond (System GMM base); Cooley & Prescott (TVP framework) | Manuel Arellano and Stephen Bond |
| Tips≠ | Dynamic panel estimator with time-varying coefficients | GMM estimator for dynamic panel data |
| Pirmavots≠ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. 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 | TVP System GMM, time-varying System GMM, TVP-SGMM, dynamic panel TVP estimator | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Time-Varying Parameter System GMM extends the Blundell-Bond System Generalized Method of Moments estimator to allow regression coefficients to change over time. By combining the instrument-based correction for dynamic endogeneity with a time-varying coefficient structure, the method captures both the persistence of the lagged dependent variable and structural shifts in the effect of regressors across periods. | 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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