Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sistemiskā GMM metodes strukturālās pārtraukuma sistēma× | GMM atšķirību metode (Arellano–Bonda novērtētājs)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1998–2003 | 1991 |
| Autors≠ | Blundell & Bond (System GMM); Bai & Perron (structural break framework) | Manuel Arellano and Stephen Bond |
| Tips≠ | Dynamic panel estimator with regime change | GMM panel estimator |
| 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 | System GMM with structural breaks, SB-SGMM, break-augmented System GMM, System GMM structural change estimator | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Structural Break System GMM extends the Blundell-Bond System GMM estimator for dynamic panel data by explicitly accounting for structural breaks — abrupt regime changes in slopes, intercepts, or dynamics — that, if ignored, bias the coefficient estimates and invalidate the moment conditions that underpin standard GMM inference. | Difference GMM, introduced by Arellano and Bond (1991), estimates dynamic panel data models by first-differencing the equation to remove fixed effects, then using lagged levels of the endogenous variables as GMM instruments. It is the standard approach when a lagged dependent variable or other endogenous regressors are present in a panel with many units and few time periods. |
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