方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 动态面板数据模型× | 差分GMM（Arellano-Bond估计量）× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1988–1991 | 1991 |
| 提出者≠ | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) | Manuel Arellano and Stephen Bond |
| 类型≠ | Dynamic regression / GMM estimation | GMM panel estimator |
| 开创性文献 | 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 ↗ | 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 ↗ |
| 别名 | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model | Arellano-Bond estimator, AB-GMM, first-difference GMM, difference GMM estimator |
| 相关 | 5 | 5 |
| 摘要≠ | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. | 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. |
| ScholarGate数据集 ↗ |
|
|