方法对比
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| 面板结构向量自回归 (Panel SVAR) 模型× | 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≠ | 2004 (panel extension); 1986 (SVAR origins) | 1987–1995 |
| 提出者≠ | Canova & Ciccarelli; Bernanke (SVAR identification) | Engle & Granger (1987) for VECM; Holtz-Eakin, Newey & Rosen (1988) for panel VAR extension |
| 类型≠ | Multivariate time-series model with structural identification | Multivariate dynamic panel model |
| 开创性文献≠ | Canova, F., & Ciccarelli, M. (2004). Forecasting and turning point predictions in a Bayesian panel VAR model. Journal of Econometrics, 120(2), 327-359. 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 | Panel SVAR, PSVAR, Structural Panel VAR, Panel Structural VAR | Panel VECM, panel vector error correction model, PVECM, panel cointegrating VAR |
| 相关 | 5 | 5 |
| 摘要≠ | The Panel SVAR model extends the Structural VAR framework to panel data, jointly modelling multiple endogenous time-series variables across several cross-sectional units (e.g., countries or firms). Structural restrictions — short-run, long-run, or sign restrictions — are imposed on the contemporaneous relationships among variables to identify economically meaningful causal shocks and trace their propagation across units and time. | 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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