方法对比
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| 非线性OLS（非线性最小二乘法）× | 非线性自回归分布式滞后 (NARDL) 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≠ | 1974–1987 | 2014 |
| 提出者≠ | Gallant (1987); Wooldridge (2010) for econometric treatment | Shin, Yu & Greenwood-Nimmo |
| 类型≠ | Nonlinear regression estimator | Nonlinear cointegration model |
| 开创性文献≠ | Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600 | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. link ↗ |
| 别名 | nonlinear least squares, NLS, NLLS, nonlinear regression | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model |
| 相关 | 5 | 5 |
| 摘要≠ | Nonlinear Ordinary Least Squares (NLS) estimates regression models in which the conditional mean function is nonlinear in the parameters. Like standard OLS it minimises the sum of squared residuals, but because no closed-form solution exists the estimator is found by iterative numerical optimisation. Under standard regularity conditions NLS is consistent and asymptotically normal. | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. |
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