GrangerTest {MTS}

Granger Causality Test

Description

Performs Granger causality test using a vector autoregressive model

Usage

GrangerTest(X,p=1,include.mean=T,locInput=c(1))

Arguments

X

a T-by-p data matrix with T denoting sample size and p the number of variables

p

vector AR order.

include.mean

Indicator for including a constant in the model. Default is TRUE.

locInput

Locators for the input variables in the data matrix. Default is the first column being the input variable. Multiple inputs are allowed.

Details

Perform VAR(p) and constrained VAR(p) estimations to test the Granger causality. It uses likelihood ratio and asymptotic chi-square.

Value

data

Original data matrix

cnst

logical variable to include a constant in the model

order

order of VAR model used

coef

Coefficient estimates

constraints

Implied constraints of Granger causality

aic, bic, hq

values of information criteria

residuals

residual vector

secoef

standard errors of coefficient estimates

Sigma

Residual covariance matrix

Phi

Matrix of VAR coefficients

Ph0

constant vector

omega

Estimates of constrained coefficients

covomega

covariance matrix of constrained parameters

locInput

Locator vector for input variables

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 2)