An annual time series from 1930 to 1983 with 2 variables.
chicken
number of chickens (December 1 population
of all US chickens excluding commercial broilers),
egg
number of eggs (US egg production in millions
of dozens).
Source
The data set was provided by Walter Thurman and made available
for R by Roger Koenker. Unfortunately, the data is slightly different
than the data analyzed in Thurman & Fisher (1988).
References
Thurman W.N. & Fisher M.E. (1988), Chickens, Eggs, and Causality, or
Which Came First?, American Journal of Agricultural Economics,
237-238.
Examples
## Which came first: the chicken or the egg?
data(ChickEgg)
## chickens granger-cause eggs?
grangertest(egg ~ chicken, order = 3, data = ChickEgg)
## eggs granger-cause chickens?
grangertest(chicken ~ egg, order = 3, data = ChickEgg)
## To perform the same tests `by hand', you can use dynlm() and waldtest():
if(require(dynlm)) {
## chickens granger-cause eggs?
em <- dynlm(egg ~ L(egg, 1) + L(egg, 2) + L(egg, 3), data = ChickEgg)
em2 <- update(em, . ~ . + L(chicken, 1) + L(chicken, 2) + L(chicken, 3))
waldtest(em, em2)
## eggs granger-cause chickens?
cm <- dynlm(chicken ~ L(chicken, 1) + L(chicken, 2) + L(chicken, 3), data = ChickEgg)
cm2 <- update(cm, . ~ . + L(egg, 1) + L(egg, 2) + L(egg, 3))
waldtest(cm, cm2)
}