Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Panelu vektorautoregresijas (Panel VAR) modelis× | Strukturālā vektorautoregresija (SVAR)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1988 | 1980 |
| Autors≠ | Holtz-Eakin, Newey & Rosen | Sims (1980); identification schemes by Blanchard & Quah (1989) |
| Tips≠ | Panel vector autoregression | Multivariate time series model |
| Pirmavots≠ | Holtz-Eakin, D., Newey, W. & Rosen, H. S. (1988). Estimating Vector Autoregressions with Panel Data. Econometrica, 56(6), 1371-1395. DOI ↗ | Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗ |
| Citi nosaukumi≠ | PVAR, panel vector autoregression, Panel VAR (PVAR) | SVAR, structural vector autoregression, identified VAR, structural VAR model |
| Saistītās≠ | 3 | 5 |
| Kopsavilkums≠ | Panel VAR extends the vector autoregression model to panel data, modelling the dynamic interactions among several variables while controlling for cross-unit heterogeneity through fixed effects. It was introduced by Holtz-Eakin, Newey and Rosen in 1988 and produces impulse-response functions and variance decompositions at the panel level. | 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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