方法对比
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| 非线性结构向量自回归（NL-SVAR）模型× | 非线性向量自回归模型× | |
|---|---|---|
| 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 | 1990s–2000s |
| 提出者≠ | Extensions by Koop, Potter, Auerbach, Gorodnichenko and others | Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework |
| 类型≠ | Multivariate nonlinear structural time series model | Multivariate 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 ↗ | Tsay, R. S. (1998). Testing and modeling multivariate threshold models. Journal of the American Statistical Association, 93(443), 1188–1202. DOI ↗ |
| 别名 | nonlinear structural VAR, NL-SVAR, threshold SVAR, regime-switching SVAR | NLVAR, nonlinear vector autoregression, threshold VAR, TVAR |
| 相关≠ | 6 | 4 |
| 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 VAR (NLVAR) model extends the standard vector autoregression by allowing the dynamic relationships among multiple time series to switch or change smoothly depending on an observed threshold variable, a latent regime state, or a smooth transition function. It is used when economic systems exhibit asymmetric responses, regime shifts, or state-dependent dynamics that a linear VAR cannot capture. |
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