# Determining suitable time lag in Granger causality test

In order to determine the right time lag for the Granger causality test, I applied a cross correlation function (CCF) among EU and National legislation and the CCF figure is attached. I would be grateful if you could kindly help me in resolving the following concerns:

• I am wondering what time-lag you recommend based on the attached figure?
• To find the greatest value in CCF figure, should I consider absolute values or just the raw values?
• If we consider the negative values in CCF Figure, then I assume the result of Granger causality test would show the negative causality, correct?
• I am interested in one side of the causality (Effect of EU on National and Not the vice versa), so, should I only consider the bound [-5...0]?
• You need more reputation to post images, but you are able to post data and/or printed output from the software you used, such as numeric tabulation of CCF. – Nick Cox Aug 7 '13 at 11:00
• The OP says the figure is attached but there is no figure here. It seems to be lost during the editing. – Metrics Aug 12 '13 at 2:06

Does the lag identification procedure have to be applied using the cross correlation? If not, I would recommend the function VARselect() from the package vars in the R programming environment. This function suggests different optimal lags according to some information criteria (AIC, HQ, SC and FPE). Once you have chosen the lag, you can perform a Granger causality test using another function from the same package causality().