方法对比
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| 面板结构向量自回归 (Panel SVAR) 模型× | 结构向量自回归 (SVAR)× | |
|---|---|---|
| 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) | 1980 |
| 提出者≠ | Canova & Ciccarelli; Bernanke (SVAR identification) | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| 类型≠ | Multivariate time-series model with structural identification | Multivariate time series 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 ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| 别名 | Panel SVAR, PSVAR, Structural Panel VAR, Panel Structural VAR | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| 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. | Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions. |
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