An object of formal class 'ca.jo' is transformed to a VAR in level
presentation.
Usage
vec2var(z, r = 1)
Value
A list with class attribute ‘vec2var’ holding the
following elements:
deterministic
The matrix of deterministic coefficients.
A
A list with matrix object(s) containing the coefficients for
the lagged endogenous variables.
p
The lag-order of the estimated VAR-process.
K
The count of endogenous variables.
y
A dataframe with the endogenous variables in levels.
obs
An integer signifying the count of used observations.
totobs
An integer signifying the total number of observations,
i.e including observations taken as starting values..
call
The call to vec2var.
vecm
The supplied object z of formal class ca.jo.
datamat
A dataframe with the used dataset.
resid
A matrix with the residuals from the empirical VAR(p).
r
Intefer, the assigned co-integration rank from the call.
Arguments
z
An object of class 'ca.jo' generated by function
ca.jo() in package 'urca'.
r
The cointegration rank (default is r=1).
Author
Bernhard Pfaff
Details
This function enables the user to transform a vector-error-correction
model (VECM) into a level-VAR form. The rank of the matrix
\(\bold{\Pi}\) has to be submitted, i.e. how many
cointegration relationships have been determined according to the
outcome of ca.jo().
References
Hamilton, J. (1994), Time Series Analysis, Princeton
University Press, Princeton.
Lütkepohl, H. (2006), New Introduction to Multiple Time Series
Analysis, Springer, New York.