Granger Causality
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another. 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.
Read more about Granger Causality: Method, Limitations, Mathematical Statement, Extensions
Famous quotes containing the word causality:
“Any important disease whose causality is murky, and for which treatment is ineffectual, tends to be awash in significance.”
—Susan Sontag (b. 1933)