Sammenlign metoder

	Hiemstra-Jones' test for ikke-lineær Granger-kausalitet	Granger-kausalitetstest
Fagfelt	Økonometri	Økonometri
Familie	Hypothesis test	Regression model
Opprinnelsesår	1994	1969
Opphavsperson	Craig Hiemstra & Jonathan Jones	Clive W. J. Granger
Type	Nonparametric hypothesis test	Time-series predictive causality test
Opprinnelig kilde	Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price-volume relation. The Journal of Finance, 49(5), 1639–1664.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.
Alias	HJ Nonlinear Causality Test, Hiemstra-Jones Test, Nonlinear Granger Causality (Hiemstra-Jones), HJ Nedensellik Testi	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Relaterte	3	5
Sammendrag	The Hiemstra-Jones test, introduced in 1994, is a nonparametric procedure for detecting nonlinear causal relationships between two time series after removing their linear interdependencies. Developed in the context of stock price and trading volume dynamics, it extends the standard linear Granger causality framework by using correlation integral statistics to detect predictability arising from nonlinear mechanisms that linear VAR models cannot capture.	The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.