lmtest (version 0.9-35)

grangertest: Test for Granger Causality

Description

grangertest is a generic function for performing a test for Granger causality.

Usage

# S3 method for default
grangertest(x, y, order = 1, na.action = na.omit, …)
# S3 method for formula
grangertest(formula, data = list(), …)

Arguments

x

either a bivariate series (in which case y has to be missing) or a univariate series of observations.

y

a univariate series of observations (if x is univariate, too).

order

integer specifying th order of lags to include in the auxiliary regression.

na.action

a function for eliminating NAs after aligning the series x and y.

…

further arguments passed to waldtest.

formula

a formula specification of a bivariate series like y ~ x.

data

an optional data frame containing the variables in the model. By default the variables are taken from the environment which grangertest is called from.

Value

An object of class "anova" which contains the residual degrees of freedom, the difference in degrees of freedom, Wald statistic and corresponding p value.

Details

Currently, the methods for the generic function grangertest only perform tests for Granger causality in bivariate series. The test is simply a Wald test comparing the unrestricted model---in which y is explained by the lags (up to order order) of y and x---and the restricted model---in which y is only explained by the lags of y.

Both methods are simply convenience interfaces to waldtest.

See Also

waldtest, ChickEgg

Examples

# NOT RUN {
## Which came first: the chicken or the egg?
data(ChickEgg)
grangertest(egg ~ chicken, order = 3, data = ChickEgg)
grangertest(chicken ~ egg, order = 3, data = ChickEgg)

## alternative ways of specifying the same test
grangertest(ChickEgg, order = 3)
grangertest(ChickEgg[, 1], ChickEgg[, 2], order = 3)
# }