Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Векторна авторегресія з доповненням факторами (FAVAR)× | Модель Марковського перемикання режимів (MS-AR / MS-VAR)× | Модель векторної авторегресії (VAR)× | |
|---|---|---|---|
| Галузь | Економетрика | Економетрика | Економетрика |
| Родина | Regression model | Regression model | Regression model |
| Рік появи≠ | 2005 | 1989 | 2005 |
| Автор методу≠ | Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexes | Hamilton (1989); Kim & Nelson (1999) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Тип≠ | Multivariate time-series model | Regime-switching time series model | Multivariate time-series model |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | 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 |
| Пов'язані≠ | 4 | 5 | 4 |
| Підсумок≠ | 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). |
| ScholarGateНабір даних ↗ |
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