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| Модел на Фуриеров векторна авторегресия (VAR)× | Векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2010s | 1980 |
| Създател≠ | Enders & Lee; extended by Nazlioglu and others to VAR systems | Christopher A. Sims |
| Тип | Multivariate time-series model | Multivariate time-series model |
| Основополагащ източник≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Други названия | Fourier VAR, smooth structural break VAR, trigonometric VAR, Fourier-augmented VAR | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Свързани≠ | 6 | 5 |
| Резюме≠ | The Fourier VAR model extends the standard Vector Autoregression by replacing fixed deterministic terms with Fourier trigonometric components, allowing the intercept (and optionally the trend) to shift gradually and smoothly over time. This eliminates the need to pre-specify the number, timing, or shape of structural breaks in a multivariate time-series system. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
| ScholarGateНабор от данни ↗ |
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