方法对比
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| 非线性自回归 (NAR) 模型× | 结构突变自回归模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1978-1990 | 1989-2003 |
| 提出者≠ | Tong, H. (threshold AR); Terasvirta, T. (STAR variant) | Perron (1989); Bai & Perron (1998, 2003) |
| 类型≠ | Nonlinear time series model | Time-series model with structural change |
| 开创性文献≠ | Tong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 9780198522201 | Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22. DOI ↗ |
| 别名 | NAR model, nonlinear autoregression, NLAR, threshold autoregressive model | AR model with structural change, breakpoint AR model, piecewise autoregressive model, AR model with regime shifts |
| 相关 | 6 | 6 |
| 摘要≠ | The Nonlinear AR model extends the classical autoregressive framework by allowing the mapping from past values to the current value to follow an arbitrary or regime-switching nonlinear function. Major families include the Self-Exciting Threshold AR (SETAR), Smooth Transition AR (STAR), and neural network AR, each capturing different forms of asymmetry, regime shifts, or smooth nonlinear dynamics in univariate time series. | The structural break AR model extends the standard autoregressive framework by allowing the intercept and autoregressive coefficients to shift at one or more unknown break dates. Each regime between consecutive break points is governed by its own AR parameters, capturing abrupt changes in the dynamics of a time series caused by crises, policy shifts, or other shocks. |
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