Сравнение методов

	Нелинейный тест причинности по Грейнджеру Хиемстры-Джонса	Тест причинности по Грейнджеру
Область	Эконометрика	Эконометрика
Семейство	Hypothesis test	Regression model
Год появления	1994	1969
Автор метода	Craig Hiemstra & Jonathan Jones	Clive W. J. Granger
Тип	Nonparametric hypothesis test	Time-series predictive causality test
Основополагающий источник	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.
Другие названия	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
Связанные	3	5
Сводка	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.