Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Модел на Марковски превключващи се режими (MS-AR / MS-VAR)× | Модел на векторна авторегресия (VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1989 | 2005 |
| Създател≠ | Hamilton (1989); Kim & Nelson (1999) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Тип≠ | Regime-switching time series model | Multivariate time-series model |
| Основополагащ източник≠ | 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 ↗ |
| Други названия≠ | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Свързани≠ | 5 | 4 |
| Резюме≠ | 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). |
| ScholarGateНабор от данни ↗ |
|
|