Transform a VECM to VAR in levels
An object of formal class 'ca.jo' is transformed to a VAR in level presentation.
vec2var(z, r = 1)
z |
An object of class 'ca.jo' generated by function
|
r |
The cointegration rank (default is |
This function enables the user to transform a vector-error-correction
model (VECM) into a level-VAR form. The rank of the matrix
\bold{Π} has to be submitted, i.e. how many
cointegration relationships have been determined according to the
outcome of ca.jo().
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 |
vecm |
The supplied object |
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. |
Bernhard Pfaff
Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.
Lütkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.
library(urca) data(finland) sjf <- finland sjf.vecm <- ca.jo(sjf, ecdet = "none", type = "eigen", K = 2, spec = "longrun", season = 4) vec2var(sjf.vecm, r = 2)
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