So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Mô hình Hiệu chỉnh Sai số Vector Fourier (Fourier VECM)× | Mô hình VAR Fourier× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 2004–2012 | 2010s |
| Người khởi xướng≠ | Enders & Lee (2004/2012); extended to VECM by subsequent authors | Enders & Lee; extended by Nazlioglu and others to VAR systems |
| Loại≠ | Error-correction model with Fourier terms | Multivariate time-series model |
| Công trình gốc≠ | 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 ↗ | 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 ↗ |
| Tên gọi khác | Fourier VECM, Fourier-approximation VECM, smooth-break VECM, trigonometric VECM | Fourier VAR, smooth structural break VAR, trigonometric VAR, Fourier-augmented VAR |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | The Fourier VECM augments the classical vector error correction model with low-frequency trigonometric terms — sine and cosine components — to capture smooth, gradual structural change in cointegrating relationships without specifying the number or timing of breaks in advance. It is used for multivariate cointegrated systems where long-run equilibria may shift gradually over time. | 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. |
| ScholarGateBộ dữ liệu ↗ |
|
|