Thank you Michael.

>From the below data, can we say:

We cannot reject "r<=3", "r<=2", "r<=1",

but we can reject "r=0".

Combining the above results, we have the following four inequalities:

r<=3
r<=2
r<=1
r>0

Taking the intersection of the above four inequalities, we reach:

r=1

The order of reading the 4 rows doesn't matter...

Am I doing it correctly?

Thank you!

> sjd.vecm@teststat
[1]  2.352233  6.342730 10.361950 30.087451
> sjd.vecm@cval
         10pct  5pct  1pct
r <= 3 |  7.52  9.24 12.97
r <= 2 | 13.75 15.67 20.20
r <= 1 | 19.77 22.00 26.81
r = 0  | 25.56 28.14 33.24

On Fri, Mar 30, 2012 at 8:27 PM, R. Michael Weylandt <
michael.weylandt@gmail.com> wrote:

> Your example is actually from the urca package which is a dependency
> of vars -- both are by Dr. Pfaff and I'd highly recommend his book on
> all this jazz: Analysis of Integrated and Cointegrated Time Series
> with R
>
> DISCLAIMER: I am not a scholar [nor even a particularly well read
> student] of unit root analysis so the following is complete bunk at p
> < 0.02.
>
> Like I said: just like (almost?) every other statistical test, it
> depends on your desired significance level. Fix that and then then you
> simply compare the test statistics for different cointegration orders
> to see if any of them are statistically significant at that level.
> However, this has to be done correctly and here's why my memory gets
> fuzzy:
>
> Something like:
>
> sjd.vecm@teststat > sjd.vecm@cval[, "10pct"]
>
> being higher than the critical value is "good" for this test.
>
> In my quick study of Johansen, I thought one had to start from r=0 and
> test sequentially up to r<=3 to do these things "properly" [i.e., if
> you can't eliminate the null hypothesis of no cointegrating vector,
> you shouldn't move on to testing the null hypothesis of one
> cointegrating vector] but that doesn't seem to be suggested by the
> summary tables ... one idea that comes to mind (and I'm really just
> guessing here) is that r is the opposite of what I think it is -- so
> one starts at r <=3 which is the more general hypothesis and
> progresses to the stricter r = 0.
>
> Whatever the correct procedure is, it seems that one needs to be
> careful of unpenalized model selection here, but that might be already
> taken care of in Johansen's method: I simply don't know. If you get
> Pfaff's book I'm sure this is explained: I don't have a copy handy and
> it's far too cold and rainy to walk to the library right now.
>
> Sorry I can't be of more help,
>
> Michael Weylandt
>
> On Fri, Mar 30, 2012 at 4:43 PM, Michael <comtech.usa@gmail.com> wrote:
> > Thank you for your help!
> >
> > I am following the example in the "vars" package in R, shown below:
> >
> > data(denmark)
> > sjd <- denmark[, c("LRM", "LRY", "IBO", "IDE")]
> > sjd.vecm <- ca.jo(sjd, ecdet = "const", type="eigen", K=2,
> spec="longrun",
> > season=4)
> > summary(sjd.vecm)
> >
> > I got the following stats:
> >
> >> sjd.vecm@teststat
> > [1]  2.352233  6.342730 10.361950 30.087451
> >> sjd.vecm@cval
> >          10pct  5pct  1pct
> > r <= 3 |  7.52  9.24 12.97
> > r <= 2 | 13.75 15.67 20.20
> > r <= 1 | 19.77 22.00 26.81
> > r = 0  | 25.56 28.14 33.24
> >
> >
> > How shall I draw a conclusion of "pass/fail" automatically and
> > programmatically?
> >
> > Could you please show me using the above example?
> >
> > Thank you!
> >
> >
> > On Fri, Mar 30, 2012 at 11:08 AM, R. Michael Weylandt
> > <michael.weylandt@gmail.com> wrote:
> >>
> >> Actually, it looks like ca.jo objects are S4 so it's a little bit
> >> harder: take a look at ?`ca.jo-class` (note the backticks) to see the
> >> 26 slots available. I'm not sure if the ones you want have dedicated
> >> extractor methods but you can get them with ?slot directly. There's
> >> not an absolute pass/fail (like most other statistical tests) so you
> >> have to pick your desired significance threshold, but that's not hard.
> >> As Brian said though, it makes most sense to do this inside your loop
> >> construction.
> >>
> >> Hope this helps,
> >>
> >> Michael Weylandt
> >>
> >> On Fri, Mar 30, 2012 at 12:00 PM, Brian G. Peterson <
> brian@braverock.com>
> >> wrote:
> >> > On Fri, 2012-03-30 at 10:53 -0500, Michael wrote:
> >> >> How to automatically extract test result from Johansen test?
> >> >>
> >> >> Hi all,
> >> >>
> >> >> I am using the "ca.jo" function to do the Johansen test.
> >> >>
> >> >> It's outputting a lot of results.
> >> >>
> >> >> If I am running this on a large number of assets, is there a way to
> >> >> automatically extract and condense the test outputs to just
> "pass/fail"
> >> >> and
> >> >> "residuals"?
> >> >>
> >> >> Thanks a lot!
> >> >
> >> > Like all R objects, it is a list internally. Extract what you need in
> >> > the same loop that's doing the test.
> >> >
> >> > Please at least try before posting.
> >> >
> >> > --
> >> > Brian G. Peterson
> >> > http://braverock.com/brian/
> >> > Ph: 773-459-4973
> >> > IM: bgpbraverock
> >> >
> >> > _______________________________________________
> >> > R-SIG-Finance@r-project.org mailing list
> >> > https://stat.ethz.ch/mailman/listinfo/r-sig-finance
> >> > -- Subscriber-posting only. If you want to post, subscribe first.
> >> > -- Also note that this is not the r-help list where general R
> questions
> >> > should go.
> >
> >
>

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