方法对比
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| 贝叶斯向量误差修正模型 (Bayesian VECM)× | 面板向量误差修正模型 (Panel VECM)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2002–2005 | 1987–1995 |
| 提出者≠ | Kleibergen & Paap; Villani | Engle & Granger (1987) for VECM; Holtz-Eakin, Newey & Rosen (1988) for panel VAR extension |
| 类型≠ | Bayesian multivariate time series model | Multivariate dynamic panel model |
| 开创性文献≠ | Kleibergen, F., & Paap, R. (2002). Priors, posteriors and Bayes factors for a Bayesian analysis of cointegration. Journal of Econometrics, 111(2), 223–249. DOI ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| 别名 | Bayesian VECM, B-VECM, Bayesian cointegrated VAR, Bayesian vector error correction | Panel VECM, panel vector error correction model, PVECM, panel cointegrating VAR |
| 相关 | 5 | 5 |
| 摘要≠ | The Bayesian VECM combines the classical Vector Error Correction Model — which captures both short-run dynamics and long-run cointegrating relationships among non-stationary multivariate time series — with Bayesian prior distributions over the cointegrating rank and coefficient matrices. This allows principled uncertainty quantification, incorporation of economic theory as priors, and coherent inference even in small samples. | Panel VECM combines vector error correction modelling with panel data, simultaneously capturing the long-run cointegrating equilibrium among multiple I(1) variables and their short-run adjustment dynamics across multiple cross-sectional units. It is the standard framework when panel variables share at least one common stochastic trend. |
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