Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālā vektorautoregresija (SVAR)× | Vektora autoregresijas (VAR) modelis× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980 | 2005 |
| Autors≠ | Christopher Sims | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Tips≠ | Structural multivariate time-series model | Multivariate time-series model |
| Pirmavots≠ | Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1–48. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Citi nosaukumi | Structural VAR, Identified VAR, SVAR Model, Yapısal Vektör Otoregresyon | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Saistītās≠ | 2 | 4 |
| Kopsavilkums≠ | Structural Vector Autoregression (SVAR) is a multivariate time-series model, developed by Christopher Sims (1980), that extends the reduced-form VAR by imposing economically motivated identifying restrictions on contemporaneous relationships among variables. SVAR enables researchers to isolate orthogonal structural shocks and trace their causal dynamic effects through impulse response functions and forecast error variance decompositions, making it a cornerstone of modern empirical macroeconomics. | 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). |
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