Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель векторной авторегрессии с изменяющимися во времени параметрами (TVP-VAR)× | Векторная авторегрессия (VAR)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2005 | 1980 |
| Автор метода≠ | Primiceri (2005); Cogley & Sargent (2001, 2005) | Christopher A. Sims |
| Тип≠ | Multivariate time-series model with drifting coefficients | Multivariate time-series model |
| Основополагающий источник≠ | Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. Review of Economic Studies, 72(3), 821-852. DOI ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Другие названия | TVP-VAR, time-varying VAR, TV-VAR, drifting-coefficient VAR | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Связанные≠ | 6 | 5 |
| Сводка≠ | The Time-Varying Parameter VAR (TVP-VAR) model extends the standard vector autoregression by allowing the coefficients and error covariances to evolve gradually over time. Estimated via Bayesian methods and MCMC simulation, it captures how dynamic relationships between macroeconomic or financial variables shift across different economic regimes without requiring pre-specified break points. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
| ScholarGateНабор данных ↗ |
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