Compara mètodes

	Panel VARX	VAR global	VAR llindar de Panell
Camp	Econometria	Econometria	Econometria
Família	Regression model	Regression model	Regression model
Any d'origen	2013	2004	1996
Autor original	Canova and Ciccarelli	Pesaran, Schuermann, and Weiner	Bruce Hansen and colleagues
Tipus	Multi-equation panel model	International system model	Nonlinear panel model
Font seminal	Canova, F., & Ciccarelli, M. (2013). Panel vector autoregressive models: A survey. Advances in Econometrics, 32, 205-246.	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.	Hansen, B. E. (1996). Inference when a nuisance parameter is not identified under the null hypothesis. Econometric Theory, 12(3), 386-414.
Àlies	Panel VAR-X	GVAR, Multi-country VAR	Panel-VAR with regime switching
Relacionats	3	3	3
Resum	Panel VARX extends vector autoregression to heterogeneous panels with exogenous variables, enabling simultaneous modeling of multiple endogenous variables alongside observed external factors across many units. Introduced by Holtz-Eakin et al. (1988) and advanced by Canova and Ciccarelli (2013), it captures dynamic relationships within units while allowing parameters to vary across units. This framework is essential for macroeconomic panels and understanding cross-unit heterogeneity in responses to common shocks.	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.	The Threshold Panel VAR extends the standard vector autoregression framework to accommodate regime-switching behavior where relationships change when a threshold variable crosses a critical level. Introduced by Hansen (1996) and applied to panels by Caner and Hansen (2001), it allows different dynamic relationships across regimes (e.g., expansions versus recessions) while exploiting the cross-sectional dimension of panel data. This nonlinear framework captures state-dependent policy effects and economic mechanisms.