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| Nichtlineares VAR-Modell× | Strukturelle Vektorautoregression (SVAR)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1990s–2000s | 1980 |
| Urheber≠ | Tsay (1998); Krolzig (1997); Tong (1990) for threshold framework | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| Typ≠ | Multivariate nonlinear time series model | Multivariate time series model |
| Wegweisende Quelle≠ | Tsay, R. S. (1998). Testing and modeling multivariate threshold models. Journal of the American Statistical Association, 93(443), 1188–1202. DOI ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| Aliasnamen | NLVAR, nonlinear vector autoregression, threshold VAR, TVAR | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| Verwandt≠ | 4 | 5 |
| Zusammenfassung≠ | The Nonlinear VAR (NLVAR) model extends the standard vector autoregression by allowing the dynamic relationships among multiple time series to switch or change smoothly depending on an observed threshold variable, a latent regime state, or a smooth transition function. It is used when economic systems exhibit asymmetric responses, regime shifts, or state-dependent dynamics that a linear VAR cannot capture. | 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. |
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