Linganisha mbinu

	VAR ya Kimataifa	Utafiti wa Mpito Lainifu wa Paneli	Kigezo Kinachobadilika kwa Wakati cha VAR Iliyoimarishwa na Vipengele
Nyanja	Ekonometriki	Ekonometriki	Ekonometriki
Familia	Regression model	Regression model	Regression model
Mwaka wa asili	2004	2005	2005
Mwanzilishi	Pesaran, Schuermann, and Weiner	Gonzalez, Terasvirta, and van Dijk	Bernanke, Boivin, and Eliasz
Aina	International system model	Smooth-regime panel model	Time-varying system
Chanzo asilia	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.	Gonzalez, A., Terasvirta, T., & van Dijk, D. (2005). Panel smooth transition regression models. Research Paper, Melbourne Institute of Applied Economic and Social Research.	Bernanke, B. S., Boivin, J., & Eliasz, P. S. (2005). Measuring monetary policy. Journal of Political Economy, 113(1), 161-208.
Majina mbadala	GVAR, Multi-country VAR	Smooth-transition panel model	Dynamic factor model with time-varying parameters
Zinazohusiana	3	3	3
Muhtasari	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.	Panel Smooth Transition Regression (PSTR) models nonlinear panel relationships where coefficients transition smoothly (rather than abruptly) between regimes as a transition variable crosses thresholds. Introduced by Gonzalez et al. (2005), it extends univariate smooth-transition autoregression (STAR) models to panels, capturing gradual shifts in economic behavior. This approach is realistic when adjustment costs cause smooth (not sudden) regime changes.	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.