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| Модел на Фуриеров структурен векторна авторегресия (Fourier SVAR)× | Модел на векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2010s | 2005 |
| Създател≠ | Extension of Sims (1980) SVAR framework with Fourier-series smoothing, developed across multiple authors in 2010s | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Тип≠ | Structural 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 ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Други названия | Fourier SVAR, Fourier structural VAR, Fourier-approximation SVAR, frequency-domain SVAR | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Свързани≠ | 3 | 4 |
| Резюме≠ | The Fourier SVAR model integrates Fourier series approximations into the structural VAR framework, allowing the model to capture smooth, gradual structural breaks and time-varying dynamics in multivariate time series without requiring a priori knowledge of break dates. It recovers structural shocks and their propagation effects while remaining robust to low-frequency parameter drift. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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