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Ikke-lineær Granger-kausalitetstest×Vektorautoregression (VAR)×
FagområdeØkonometriØkonometri
FamilieRegression modelRegression model
Oprindelsesår1992-20061980
OphavspersonBaek & Brock (1992); Hiemstra & Jones (1994); Diks & Panchenko (2006)Christopher A. Sims
TypeNonparametric causality testMultivariate time-series model
Oprindelig kildeDiks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30(9-10), 1647-1669. DOI ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Aliassernonlinear causality test, BDS-based causality, Diks-Panchenko test, nonparametric Granger causalityVAR, VAR model, vector autoregressive model, multivariate autoregression
Relaterede65
ResuméNonlinear Granger causality extends the classic linear Granger causality framework to detect predictive relationships that operate through nonlinear dynamics. Using nonparametric or semi-parametric statistics based on correlation integrals or kernel density estimation, it identifies whether past values of one variable improve forecasts of another beyond what any linear model can capture.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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ScholarGateSammenlign metoder: Nonlinear Granger Causality · Vector Autoregression. Hentet 2026-06-17 fra https://scholargate.app/da/compare