On Mon, 28 Mar 2011, Grzegorz Konat wrote:

> First of all, thank you [Jack] so much for the script - works
> perfectly fine for me!

In fact, the FEVD is available internally in gretl. I've now added
an accessor, $fevd, so you can grab it as a matrix.

> As far as the issue with different estimates is concerned [...]

>
> In gretl I do:
>
> vecm 2 1 X Y Z --ct
>

> However, when I use R's (urca):
>

> xyz.vecm <- ca.jo(gretldata[, c("X", "Y", "Z")], type = "trace", ecdet =

> "trend", K = 2, spec = "transitory")   /for all options in 'type' and
> 'spec'/
>

> and transform obtained VECM into VAR representation:
>
> vec2var.xyz <- vec2var(xyz.vecm, r = 1)
>

> the system I get has quite different parameters [...]

The model you're estimating in R is equivalent to using the --crt
flag (constant plus restricted trend) in gretl. If you use --crt
you should find that the VAR coefficients agree pretty well.

Allin Cottrell
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