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Global VAR×Lokalne projekcije×Pragovni panel VAR×
PodručjeEkonometrijaEkonometrijaEkonometrija
ObiteljRegression modelRegression modelRegression model
Godina nastanka200420051996
TvoracPesaran, Schuermann, and WeinerOscar JordaBruce Hansen and colleagues
VrstaInternational system modelMulti-horizon regressionNonlinear panel model
Temeljni izvorPesaran, 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 ↗Jorda, O. (2005). Estimation and inference of impulse responses by local projections. American Economic Review, 95(1), 161-182. DOI ↗Hansen, B. E. (1996). Inference when a nuisance parameter is not identified under the null hypothesis. Econometric Theory, 12(3), 386-414. DOI ↗
Drugi naziviGVAR, Multi-country VARLP-IR, Multi-horizon regressionPanel-VAR with regime switching
Srodne333
SažetakGlobal 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.Local Projections (LP) is a semi-parametric method for estimating impulse responses directly via multi-horizon regressions, bypassing VAR-model specification. Introduced by Jorda (2005), it projects outcomes h periods ahead onto current shocks and lags, producing impulse-response functions without assuming a particular lag structure or VAR order. This flexibility has made it the dominant approach in applied macroeconomics for measuring policy effects and shock transmission.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.
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ScholarGateUsporedite metode: Global VAR · Local Projections · Threshold Panel VAR. Preuzeto 2026-06-20 s https://scholargate.app/hr/compare