Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель векторной авторегрессии (VAR)× | Модель коррекции ошибок вектора (VECM)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2005 | 1987 |
| Автор метода≠ | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition | Engle & Granger |
| Тип | Multivariate time-series model | Multivariate time-series model |
| Основополагающий источник≠ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. 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 | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon | vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli) |
| Связанные | 4 | 4 |
| Сводка≠ | 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). | The Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework. |
| ScholarGateНабор данных ↗ |
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