方法对比
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| 结构断裂动态面板数据模型× | 动态面板数据模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1991–1998 | 1988–1991 |
| 提出者≠ | Bai & Perron (break detection); Arellano & Bond (dynamic panel GMM) | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| 类型≠ | Dynamic panel model with regime change | Dynamic regression / GMM estimation |
| 开创性文献≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. 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 with breaks, panel dynamic model structural change, DPDSB, panel dynamic structural break estimator | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| 相关≠ | 6 | 5 |
| 摘要≠ | The structural break dynamic panel data model extends the standard dynamic panel framework by allowing regression coefficients or the autoregressive parameter to shift at one or more unknown break dates. It combines GMM-based dynamic panel estimation with formal structural change tests, enabling researchers to study how economic relationships evolve across distinct regimes while controlling for unobserved individual heterogeneity and endogeneity of the lagged dependent variable. | 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. |
| ScholarGate数据集 ↗ |
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