A general nonparametric bootstrap test for Granger causality

We introduce an information theoretic test statistic for Granger causality, which can be estimated by means of correlation integrals. The significance of the test statistic is determined using bootstrap methods rather than asymptotic distribution theory. Several bootstrap strategies are suggested and compared by Monte Carlo simulations. All these bootstrap methods appear to work well, but only bootstrapping the hypothesized noncausing time series has the additional advantage that a simplified test statistic can be used.

[1]  Joseph P. Romano,et al.  The stationary bootstrap , 1994 .

[2]  M Eiselt,et al.  Using mutual information to measure coupling in the cardiorespiratory system. , 1998, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[3]  J. Viel,et al.  A model selection tool in multi-pollutant time series : The Granger-Causality diagnosis , 1999 .

[4]  Wan Mansor Wan Mahmood,et al.  Non-linear Granger causality in the currency futures returns , 2000 .

[5]  F. Longin,et al.  Is the Correlation in International Equity Returns Constant: 1960-90? , 1995 .

[6]  James Theiler,et al.  Generalized redundancies for time series analysis , 1995 .

[7]  Floris Takens,et al.  DETECTING NONLINEARITIES IN STATIONARY TIME SERIES , 1993 .

[8]  F. Marriott,et al.  Barnard's Monte Carlo Tests: How Many Simulations? , 1979 .

[9]  A. Hope.  A Simplified Monte Carlo Significance Test Procedure , 1968 .

[10]  Craig Hiemstra,et al.  Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation , 1994 .

[11]  B. LeBaron,et al.  A test for independence based on the correlation dimension , 1996 .

[12]  Lilian K. Ng,et al.  A causality-in-variance test and its application to financial market prices , 1996 .

[13]  W. Singer,et al.  Testing non-linearity and directedness of interactions between neural groups in the macaque inferotemporal cortex , 1999, Journal of Neuroscience Methods.

[14]  R. Savit,et al.  Time series and dependent variables , 1991 .

[15]  K. Tan,et al.  The causal nexus of money, output and prices in Malaysia , 1995 .