Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Факторно-допълнена векторна авторегресия (FAVAR)× | Модел на Марковски превключващи се режими (MS-AR / MS-VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2005 | 1989 |
| Създател≠ | Bernanke, Boivin & Eliasz (2005); building on Stock & Watson diffusion indexes | Hamilton (1989); Kim & Nelson (1999) |
| Тип≠ | Multivariate time-series model | Regime-switching time series model |
| Основополагащ източник≠ | 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 ↗ |
| Други названия≠ | factor-augmented VAR, FAVAR model, Faktör Artırımlı VAR (FAVAR) | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR |
| Свързани≠ | 4 | 5 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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