Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| GMM ya Mfumo Imara× | Kiendesha cha GMM cha Tofauti (Kiendesha cha Arellano-Bond)× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1998–2005 | 1991 |
| Mwanzilishi≠ | Blundell & Bond (1998); robustness corrections by Windmeijer (2005) | Manuel Arellano and Stephen Bond |
| Aina≠ | Panel data GMM estimator | GMM panel estimator |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala | system GMM with robust standard errors, two-step system GMM, Blundell-Bond robust estimator, robust S-GMM | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Robust System GMM is a two-step panel data estimator that combines the difference and levels moment conditions of Blundell and Bond (1998) with Windmeijer's (2005) finite-sample correction to the two-step variance, producing valid inference even in short panels with a persistent dependent variable, individual fixed effects, and potentially endogenous regressors. | 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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