lmtest (version 0.9-2)

grangertest: Test for Granger Causality

Description

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

Usage

## S3 method for class 'default':
grangertest(x, y, order = 1, na.action = na.omit, \dots)
## S3 method for class '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

## 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)