Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Vektora autoregresijas (VAR) modelis× | Vektora kļūdu labojuma modelis (VECM)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2005 | 1987 |
| Autors≠ | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition | Engle & Granger |
| Tips | Multivariate time-series model | Multivariate time-series model |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon | vector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli) |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | 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. |
| ScholarGateDatu kopa ↗ |
|
|