Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Panelu VECM (Panel Vector Error Correction Model)× | Arellano-Bond GMM novērtētājs× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1987–1995 | 1991 |
| Autors≠ | Engle & Granger (1987) for VECM; Holtz-Eakin, Newey & Rosen (1988) for panel VAR extension | Manuel Arellano and Stephen Bond |
| Tips≠ | Multivariate dynamic panel model | Dynamic panel GMM estimator |
| Pirmavots≠ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. 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 | Panel VECM, panel vector error correction model, PVECM, panel cointegrating VAR | Arellano-Bond GMM, AB-GMM, difference GMM estimator, dynamic panel GMM |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Panel VECM combines vector error correction modelling with panel data, simultaneously capturing the long-run cointegrating equilibrium among multiple I(1) variables and their short-run adjustment dynamics across multiple cross-sectional units. It is the standard framework when panel variables share at least one common stochastic trend. | The Arellano-Bond GMM estimator addresses the two core problems of dynamic panel models — individual fixed effects correlated with the regressors, and the endogeneity introduced by a lagged dependent variable — by first-differencing to remove fixed effects and then using lagged levels of the dependent variable as internal instruments. |
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