Salīdzināt metodes

	Nelineārās Grangera koincidences tests	Vektora autoregresija (VAR)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	1992-2006	1980
Autors	Baek & Brock (1992); Hiemstra & Jones (1994); Diks & Panchenko (2006)	Christopher A. Sims
Tips	Nonparametric causality test	Multivariate time-series model
Pirmavots	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.
Citi nosaukumi	nonlinear causality test, BDS-based causality, Diks-Panchenko test, nonparametric Granger causality	VAR, VAR model, vector autoregressive model, multivariate autoregression
Saistītās	6	5
Kopsavilkums	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.