ECMvar: Error-Correction VAR Models

In MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

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

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 5)

See Also

ECMvar1

Examples

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)

MTS documentation built on April 11, 2022, 5:07 p.m.