Módszerek összehasonlítása

	Nemlineáris Granger-kauzalitási teszt	Vektorautoregresszió (VAR)
Tudományterület	Ökonometria	Ökonometria
Módszercsalád	Regression model	Regression model
Keletkezés éve	1992-2006	1980
Megalkotó	Baek & Brock (1992); Hiemstra & Jones (1994); Diks & Panchenko (2006)	Christopher A. Sims
Típus	Nonparametric causality test	Multivariate time-series model
Alapmű	Diks, 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.	Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48.
Alternatív nevek	nonlinear causality test, BDS-based causality, Diks-Panchenko test, nonparametric Granger causality	VAR, VAR model, vector autoregressive model, multivariate autoregression
Kapcsolódó	6	5
Összefoglaló	Nonlinear 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.