Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Sistēmas GMM panelim (Blundell-Bonda novērtētājs)× | Fiksēto efektu paneļa modelis (FE)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1998 | 1978 |
| Autors≠ | Blundell & Bond (1998); Arellano & Bover (1995) | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Tips≠ | GMM estimator for dynamic panel data | Panel regression 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 ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Citi nosaukumi | System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM | within estimator, FE model, within-group estimator, LSDV model |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Panel System GMM is a two-equation GMM estimator for dynamic panel data that stacks the differenced equation (using lagged levels as instruments) with the levels equation (using lagged differences as instruments). Developed by Blundell and Bond (1998) on the foundation of Arellano and Bover (1995), it is the preferred tool when the lagged dependent variable is highly persistent or individual effects are large. | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. |
| ScholarGateDatu kopa ↗ |
|
|