Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| GMM ya Tofauti ya Parameta Zinazobadilika kwa Wakati× | Kiendesha cha GMM cha Tofauti (Kiendesha cha Arellano-Bond)× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 2000s–2010s | 1991 |
| Mwanzilishi≠ | Extends Arellano & Bond (1991) difference GMM; TVP panel extensions developed in the 2000s–2010s literature | Manuel Arellano and Stephen Bond |
| Aina≠ | Dynamic panel estimator with time-varying parameters | GMM panel estimator |
| Chanzo asilia≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297. 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 | TVP-DGMM, time-varying GMM, TVP difference GMM, dynamic panel TVP estimator | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| Zinazohusiana≠ | 3 | 5 |
| Muhtasari≠ | Time-varying parameter difference GMM combines the Arellano-Bond first-difference GMM estimator for dynamic panels with a state-space or local-smoothing framework that allows regression coefficients to drift over time. It handles endogeneity and lagged dependent variables while relaxing the assumption that structural relationships remain constant across all periods. | 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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