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| Ποσοστιαία VAR (Quantile VAR)× | Μοντέλο Αυτοπαλινδρόμησης Διανυσμάτων (VAR)× | |
|---|---|---|
| Πεδίο | Οικονομετρία | Οικονομετρία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 2006 | 2005 |
| Δημιουργός≠ | Koenker and Xiao | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Τύπος≠ | Distribution impulse response | Multivariate time-series model |
| Θεμελιώδης πηγή≠ | Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Εναλλακτικές ονομασίες≠ | Quantile-based impulse response | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Συναφείς≠ | 3 | 4 |
| Σύνοψη≠ | Quantile VAR estimates impulse responses of multivariate systems conditional on different quantiles of the distribution, revealing how shocks propagate heterogeneously across the conditional distribution. Introduced by Koenker and Xiao (2006) and applied to risk measurement by White et al. (2015), it reveals tail behavior and contagion effects invisible to mean-based VAR analysis. This is essential for risk management and understanding how crises propagate differently than normal times. | 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). |
| ScholarGateΣύνολο δεδομένων ↗ |
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