方法对比
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| 贝叶斯系统GMM× | 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≠ | 1998–2010 | 1988–1991 |
| 提出者≠ | Blundell & Bond (System GMM, 1998); Bayesian integration via Chib and related MCMC literature | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) |
| 类型≠ | Bayesian dynamic panel estimator | Dynamic regression / GMM estimation |
| 开创性文献≠ | 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 ↗ |
| 别名 | Bayesian Sys-GMM, Bayesian BB estimator, Bayesian Blundell-Bond GMM, B-SGMM | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model |
| 相关 | 5 | 5 |
| 摘要≠ | Bayesian System GMM combines the Blundell-Bond System Generalized Method of Moments estimator for dynamic panel data with Bayesian prior distributions and posterior inference via MCMC. It handles endogeneity, individual fixed effects, and weak-instrument problems while incorporating prior knowledge and delivering full posterior uncertainty quantification — not just point estimates and asymptotic standard errors. | 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. |
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