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| Mô hình Tự hồi quy Vector Tăng cường Nhân tố (FAVAR)× | Mô hình Chuyển đổi Chế độ Markov (MS-AR / MS-VAR)× | Mô hình Tự hồi quy Vector (VAR)× | |
|---|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model | Regression model |
| Năm ra đời≠ | 2005 | 1989 | 2005 |
| Người khởi xướng≠ | Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexes | Hamilton (1989); Kim & Nelson (1999) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Loại≠ | Multivariate time-series model | Regime-switching time series model | Multivariate time-series model |
| Công trình gốc≠ | Bernanke, B. S., Boivin, J. & Eliasz, P. (2005). Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. The Quarterly Journal of Economics, 120(1), 387-422. DOI ↗ | Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Tên gọi khác≠ | factor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR) | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Liên quan≠ | 4 | 5 | 4 |
| Tóm tắt≠ | FAVAR is a multivariate time-series model that first compresses information from a very large set of variables into a few common factors, then includes those factors alongside the observed variables in a vector autoregression. It was introduced by Bernanke, Boivin and Eliasz in 2005 to study monetary policy using hundreds of macroeconomic indicators at once. | The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions. | 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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