Granger causality
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another.1(http://en.wikipedia.org/wiki/Granger_causality#cite_note-0) Ordinarily, regressions reflect "mere" correlations, but Clive Granger, who won a Nobel Prize in Economics, argued that there is an interpretation of a set of tests as revealing something about causality.
A time series X is said to Granger-cause Y if it can be shown, usually through a series of t-tests and F-tests on lagged values of X (and with lagged values of Y also included), that those X values provide statistically significant information about future values of Y.
