Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Nelineārais GMM atšķirībās× | GMM atšķirību metode (Arellano–Bonda novērtētājs)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1991–2010 | 1991 |
| Autors≠ | Wooldridge; building on Arellano and Bond (1991) | Manuel Arellano and Stephen Bond |
| Tips≠ | Nonlinear panel estimator | GMM panel estimator |
| Pirmavots≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 9780262232586 | 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 | nonlinear diff-GMM, nonlinear Arellano-Bond GMM, first-difference nonlinear GMM, NL-GMM | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Nonlinear Difference GMM extends the Arellano-Bond difference GMM estimator to models where the structural relationship between the outcome and its predictors is inherently nonlinear. By first-differencing to eliminate individual fixed effects and then applying GMM moment conditions with lagged levels as instruments, it consistently estimates parameters in dynamic panel settings without requiring a linear functional form. | 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. |
| ScholarGateDatu kopa ↗ |
|
|