Well, without further information, I do not know, but try the following
library(urca)
example(ca.jo)
trend <- matrix(1:nrow(sjf), ncol = 1)
colnames(trend) <- "trd"
ca.jo(sjf, type = "trace", ecdet = "const", K = 2, spec = "longrun", dumvar =
trend)
Best,
Bernhard
________________________________
Von: Grzegorz Konat [mailto:grzegorz.ko...@ibrkk.pl]
Gesendet: Donnerstag, 31. März 2011 14:40
An: Pfaff, Bernhard Dr.; r-help@r-project.org
Betreff: Re: [R] VECM with UNRESTRICTED TREND
'time' was a trend variable from my.data set. Equivalent to the output
of the command 'matrix' you just gave me.
So now I did:
library(urca)
data(my.data)
names(my.data)
attach(my.data)
dat1 <- my.data[, c("dY", "X", "dM")]
mat1 <- matrix(seq(1:nrow(dat1)), ncol = 1)
args('ca.jo')
yxm.vecm <- ca.jo(dat1, type = "trace", ecdet = "const", K = 2, spec =
"longrun", dumvar=mat1)
and the output is:
Error in r[i1, , drop = FALSE] - r[-nrow(r):-(nrow(r) - lag + 1L), ,
drop = FALSE] :
non-numeric argument to binary operator
In addition: Warning message:
In ca.jo(dat1, type = "trace", ecdet = "const", K = 2, spec =
"longrun", :
No column names in 'dumvar', using prefix 'exo' instead.
What do I do wrong?
Best,
Greg
2011/3/31 Pfaff, Bernhard Dr. <bernhard_pf...@fra.invesco.com>
Hello Bernhard,
thank You so much one again! Now I (more or less)
understand the idea, but still have problem with its practical application.
I do (somewhat following example 8.1 in your textbook):
library(urca)
data(my.data)
names(my.data)
attach(my.data)
dat1 <- my.data[, c("dY", "X", "dM")]
dat2 <- cbind(time)
What is 'time'? Just employ matrix(seq(1:nrow(dat1)),
ncol = 1) for creating the trend variable.
Best,
Bernhard
args('ca.jo')
yxm.vecm <- ca.jo(dat1, type = "trace", ecdet =
"trend", K = 2, spec = "longrun", dumvar=dat2)
The above code produces following output:
Error in r[i1, , drop = FALSE] - r[-nrow(r):-(nrow(r) -
lag + 1L), , drop = FALSE] :
non-numeric argument to binary operator
What does that mean? Should I use cbind command to dat1
as well? And doesn't it transform the series into series of integer numbers?
Thank you once again (especially for your patience).
Best,
Greg
2011/3/31 Pfaff, Bernhard Dr.
<bernhard_pf...@fra.invesco.com>
Hello Greg,
you include your trend as a (Nx1) matrix and
use this for 'dumvar'. The matrix 'dumvar' is just added to the VECM as
deterministic regressors and while you are referring to case 5, this is
basically what you are after, if I am not mistaken. But we aware that this
implies a quadratic trend for the levels.
Best,
Bernhard
________________________________
Von: Grzegorz Konat
[mailto:grzegorz.ko...@ibrkk.pl]
Gesendet: Mittwoch, 30. März 2011 20:50
An: Pfaff, Bernhard Dr.;
r-help@r-project.org
Betreff: Re: [R] VECM with UNRESTRICTED
TREND
Hello Bernhard,
Thank You very much. Unfortunately I'm
still not really sure how should I use dummy vars in this context...
If I have a system of three variables
(x, y, z), lag order = 2 and 1 cointegrating relation, what should I do? I
mean, what kind of 'pattern' should be used to create those dummy variables,
what should they represent and how many of them do I need?
Many thanks in advance!
Best,
Greg
2011/3/30 Pfaff, Bernhard Dr.
<bernhard_pf...@fra.invesco.com>
Hello Greg,
you can exploit the argument 'dumvar'
for this. See ?ca.jo
Best,
Bernhard
> -----Ursprüngliche Nachricht-----
> Von: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org]
Im Auftrag von Grzegorz Konat
> Gesendet: Mittwoch, 30. März 2011
16:46
> An: r-help@r-project.org
> Betreff: [R] VECM with UNRESTRICTED
TREND
>
> Dear All,
>
> My question is:
>
> how can I estimate VECM system with
"unrestricted trend" (aka
> "case 5") option as a deterministic
term?
>
> As far as I know, ca.jo in urca
package allows for "restricted trend"
> only [vecm
> <- ca.jo(data, type =
"trace"/"eigen", ecdet = "trend", K =
> n, spec = "transitory"/"longrun")].
> Obviously, I don't have to do this in
urca, so if another
> package gives the possibility, please
let me know too!
>
> Thanks in advance!
>
> Greg
>
> [[alternative HTML version
deleted]]
>
>
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