ECMvar function

Error-Correction VAR Models

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

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

Returns

• 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)

Author(s)

Ruey S. Tsay

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)