方法对比
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| 非线性结构向量自回归（NL-SVAR）模型× | 非线性向量误差修正模型（非线性VECM）× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s–2010s | 1989–1998 |
| 提出者≠ | Extensions by Koop, Potter, Auerbach, Gorodnichenko and others | Granger & Lee (1989); Enders & Granger (1998) |
| 类型≠ | Multivariate nonlinear structural time series model | Nonlinear time-series model |
| 开创性文献≠ | Koop, G., & Korobilis, D. (2010). Bayesian multivariate time series methods for empirical macroeconomics. Foundations and Trends in Econometrics, 3(4), 267–358. DOI ↗ | Enders, W., & Granger, C. W. J. (1998). Unit-root tests and asymmetric adjustment with an example using the term structure of interest rates. Journal of Business & Economic Statistics, 16(3), 304–311. DOI ↗ |
| 别名 | nonlinear structural VAR, NL-SVAR, threshold SVAR, regime-switching SVAR | nonlinear VECM, NVECM, threshold VECM, asymmetric VECM |
| 相关≠ | 6 | 2 |
| 摘要≠ | The Nonlinear Structural VAR model extends the standard SVAR framework to allow structural relationships and dynamic responses to vary across economic regimes or states of the world. By imposing nonlinear transition mechanisms — such as threshold switching or smooth regime change — it captures asymmetric responses to shocks that a linear SVAR cannot detect. | The Nonlinear VECM extends the standard linear VECM by allowing the speed of adjustment toward long-run equilibrium to differ depending on the sign, magnitude, or regime of deviations from that equilibrium. It captures asymmetric or threshold-driven dynamics in cointegrated time-series systems that a standard VECM would miss. |
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