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| Ποσοστιαία VAR (Quantile VAR)× | Διανυσματική Αυτοπαλίνδρομη Ανάλυση Δομής (SVAR)× | |
|---|---|---|
| Πεδίο | Οικονομετρία | Οικονομετρία |
| Οικογένεια | Regression model | Regression model |
| Έτος προέλευσης≠ | 2006 | 1980 |
| Δημιουργός≠ | Koenker and Xiao | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| 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 ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| Εναλλακτικές ονομασίες≠ | Quantile-based impulse response | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| Συναφείς≠ | 3 | 5 |
| 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. | Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions. |
| ScholarGateΣύνολο δεδομένων ↗ |
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