MTS (version 1.2.1)

ECMvar: Error-Correction VAR Models

Description

Performs estimation of an Error-Correction VAR(p) model using the Quasi Maximum Likelihood Method.

Usage

ECMvar(x, p, ibeta, include.const = FALSE, fixed = NULL,
                 alpha = NULL, se.alpha = NULL, se.beta = NULL, phip =
                 NULL, se.phip = NULL)

Arguments

x

A T-by-k data matrix of a k-dimensional co-integrated VAR process

p

VAR order

ibeta

Initial estimate of the co-integrating matrix. The number of columns of ibeta is the number of co-integrating series

include.const

A logical switch to include a constant term in the model. The default is no constant

fixed

A logical matrix to set zero parameter constraints.

alpha

Initial estimate of alpha, if any

se.alpha

Initial estimate of the standard error of alpha, if any

se.beta

Initial estimate of the standard error of beta, if any

phip

Initial estimate of the VAR coefficients, if any

se.phip

Initial estimate of the standard error of the VAR coefficients, if any

Value

data

The vector time series

ncoint

The number of co-integrating series

arorder

VAR order

include.const

Logical switch to include constant

alpha,se.alpha

Estimates and their standard errors of the alpha matrix

beta,se.beta

Estimates and their standard errors of the beta matrix

aic,bic

Information criteria of the fitted model

residuals

The residual series

Sigma

Residual covariance matrix

Phip,se.Phip

Estimates and their standard errors of VAR coefficients

References

Tsay (2014, Chapter 5)

See Also

ECMvar1

Examples

# NOT RUN {
phi=matrix(c(0.5,-0.25,-1.0,0.5),2,2); theta=matrix(c(0.2,-0.1,-0.4,0.2),2,2)
Sig=diag(2)
mm=VARMAsim(300,arlags=c(1),malags=c(1),phi=phi,theta=theta,sigma=Sig)
zt=mm$series[,c(2,1)]
beta=matrix(c(1,0.5),2,1)
m1=ECMvar(zt,3,ibeta=beta)
names(m1)
# }