vec2var: Transform a VECM to VAR in levels
In cheaton/vars2: VAR Modelling

Description Usage Arguments Details Value Author(s) References See Also Examples

An object of formal class 'ca.jo' is transformed to a VAR in level presentation.

1	vec2var(z, r = 1)

`z`	An object of class 'ca.jo' generated by function `ca.jo()` in package 'urca'.
`r`	The cointegration rank (default is `r=1)`.

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 `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.

Bernhard Pfaff

Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton.

LÃ¼tkepohl, H. (2006), New Introduction to Multiple Time Series Analysis, Springer, New York.

ca.jo, predict, irf, fevd, Phi, Psi, normality.test, arch.test, serial.test, logLik, plot

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)