Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Globālais VAR× | TVP-FAVAR× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2004 | 2005 |
| Autors≠ | Pesaran, Schuermann, and Weiner | Bernanke, Boivin, and Eliasz |
| Tips≠ | International system model | Time-varying system |
| Pirmavots≠ | Pesaran, M. H., Schuermann, T., & Weiner, S. M. (2004). Modeling regional interdependencies using a global error-correcting macroeconometric model. Journal of Business and Economic Statistics, 22(2), 129-162. DOI ↗ | Bernanke, B. S., Boivin, J., & Eliasz, P. S. (2005). Measuring monetary policy. Journal of Political Economy, 113(1), 161-208. link ↗ |
| Citi nosaukumi≠ | GVAR, Multi-country VAR | Dynamic factor model with time-varying parameters |
| Saistītās | 3 | 3 |
| Kopsavilkums≠ | Global VAR (GVAR) is a large-scale macroeconomic modeling framework linking multiple countries (or regions) via trade and financial channels, allowing shocks in one country to propagate through the global system. Introduced by Pesaran et al. (2004), it solves the curse of dimensionality in international VAR models by estimating country-specific VARs conditional on foreign variables, then solving a system linking all countries. This approach is invaluable for analyzing global spillovers and international policy coordination. | TVP-FAVAR is a hybrid framework combining factor-augmented VARs with time-varying parameter estimation via Kalman filtering. Introduced by Bernanke et al. (2005) and refined by Primiceri (2005), it extracts latent economic factors (e.g., a 'common monetary policy shock') from high-dimensional data while allowing VAR coefficients to evolve stochastically over time. This framework captures both reduced-dimensionality patterns and structural instability, making it ideal for studying evolving policy regimes and shock dynamics. |
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