方法对比
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| 面板结构向量自回归 (Panel SVAR) 模型× | 向量误差修正模型 (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 |
| 提出者≠ | Canova & Ciccarelli; Bernanke (SVAR identification) | Robert F. Engle and Clive W. J. Granger |
| 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 ↗ | 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 | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction 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. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
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