ChickEgg: Chickens, Eggs, and Causality

In lmtest: Testing Linear Regression Models

Chickens, Eggs, and Causality

Description

US chicken population and egg production.

Usage

data(ChickEgg)

Format

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)
}

lmtest documentation built on March 22, 2022, 1:06 a.m.