Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Байесовская модель структурной векторной авторегрессии (B-SVAR)× | Модель коррекции ошибок вектора (VECM)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1998–2005 | 1987 |
| Автор метода≠ | Sims & Zha (1998); Uhlig (2005) for sign-restriction identification | Robert F. Engle and Clive W. J. Granger |
| Тип≠ | Structural multivariate time-series model | Multivariate time-series model |
| Основополагающий источник≠ | Sims, C. A., & Zha, T. (1998). Bayesian methods for dynamic multivariate models. International Economic Review, 39(4), 949–968. DOI ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Другие названия | Bayesian SVAR, B-SVAR, Bayesian structural VAR, Bayesian identified VAR | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Связанные≠ | 6 | 5 |
| Сводка≠ | The Bayesian Structural Vector Autoregression model combines the structural identification of SVAR with Bayesian prior distributions over parameters. It estimates causal impulse responses between multiple time series while incorporating prior economic knowledge and producing full posterior uncertainty bands rather than point estimates alone. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
| ScholarGateНабор данных ↗ |
|
|