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| Байесов векторна авторегресия (BVAR)× | Модел на Марковски превключващи се режими (MS-AR / MS-VAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1986 | 1989 |
| Създател≠ | Litterman (1986); Bańbura, Giannone & Reichlin (2010) | Hamilton (1989); Kim & Nelson (1999) |
| Тип≠ | Bayesian multivariate time-series model | Regime-switching time series model |
| Основополагащ източник≠ | Litterman, R. B. (1986). Forecasting with Bayesian Vector Autoregressions—Five Years of Experience. Journal of Business & Economic Statistics, 4(1), 25-38. 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≠ | BVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR) | regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR |
| Свързани | 5 | 5 |
| Резюме≠ | Bayesian VAR adds Minnesota or other prior distributions to a vector autoregressive model to control over-parameterisation. Introduced by Litterman (1986) and extended to high dimensions by Bańbura, Giannone and Reichlin (2010), it outperforms classical VAR on short series and high-dimensional macroeconomic forecasts. | 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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