When saying that A causes B, this means that A is the reason that B happens. This is the common definition of causality: which one causes the next one. The Granger causality test is used to determine whether one time series is a factor and offers useful information in forecasting the second one. In the following code, a dataset called ChickEgg is used as an illustration. The dataset has two columns, number of chicks and number of eggs, with a timestamp:
> library(lmtest)
> data(ChickEgg)
> dim(ChickEgg)
[1] 54 2
> ChickEgg[1:5,]
chicken egg
[1,] 468491 3581
[2,] 449743 3532
[3,] 436815 3327
[4,] 444523 3255
[5,] 433937 3156
The question is: could we use this year's egg numbers to predict the next year's chicken numbers? If this is true, our statement will be the number of chicks Granger causes the number of eggs. If this is not true, we...