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Re: st: RE: Noconst in cointegration relationship in VECM


From   Charles Koss <hqtiger@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Noconst in cointegration relationship in VECM
Date   Thu, 28 Apr 2011 13:36:49 -0500

After the clarification of Gustavo Sanchez from Stata.  Now, let's say
I choose 'trend(none)’ how to obtain the standard errors for the
estimated impulse response functions?

According to the reference manual, Stata version 10 can not do that.
Then, the analysis is incomplete using stata command vec. Usually, the
parameter estimates after vec is the beginning of the analysis.

Then the questions are: can Stata do it? If yes, how to do it?

e.g.
use http://www.stata-press.com/data/r11/urates
vec missouri indiana kentucky illinois, trend(none) rank(2) lags(4)
irf create vec1, set(vecirfs2) step(50)
irf graph oirf, impulse(indiana) response(missouri)
//stata does not provide the confidence inverval that could be constructed if
//standard errors were available.

Charles

-- 
Charles Koss
http://charlesonnet.blogspot.com

On Thu, Apr 28, 2011 at 1:09 PM,  <gsanchez@stata.com> wrote:
> Svein Olav wrote:
>
>> I am trying to have no constant in the cointegration vector in the VEC
>> model.
>>
>> … if I restrict (i.e.) the variable lnrent:
>>
>> constraint define 1 [_ce1]lnrent=1
>> vec lnprice lnrent lnAM, rank(1) lags(2) trend(constant) bconstraints(1)
>>
>> It works fine.
>> Then I am thinking that it should only be to restrict the constant in the
>> same way:
>>
>> constraint define 1 [_ce1]_cons=0
>> vec lnprice lnrent lnAM, rank(1) lags(2) trend(constant) bconstraints(1)
>>
>> But this do not work.
>
> The –vec- command provides five different options to restrict the
> deterministic components included in the VEC model specification. The five
> alternatives were referred by Eric de Souza in his response to Svein Olav
>
>>  trend(constant) include an unrestricted constant in model; the default
>>  trend(rconstant) include a restricted constant in model
>>  trend(trend) include a linear trend in the cointegrating equations and a
>>  quadratic trend in the undifferenced data
>>  trend(rtrend) include a restricted trend in model
>>  trend(none) do not include a trend or a constant
>> See page 477 of the time series manual for a detailed explanation
>
> Those five alternatives imply “different asymptotic distributions of the
> statistics used for inference on the number of cointegrating equations and a
> different asymptotic distribution of the ML estimator of the cointegrating
> equations” (see pages 480-1 in the time-series manual [TS]). This is discussed
> in Johansen (1995, chap. 11).
>
> Svein Olav may consider specifying the option ‘trend(none)’ to restrict the
> constant in the cointegrating equation to zero. However, that option would
> also restrict to zero the constant in the differenced portion of the model and
> it would exclude linear trends in the differenced data and linear trends in
> the cointegrating equations (page 477 in the [TS] provides additional details
> for the ‘trend()’ option).
>
> There is not an option to restrict the constant in the cointegrating equation
> without imposing any constraints in the other deterministic components of the
> model. That alternative is not allowed with the ‘bconstraints()’ option
> because it would modify the asymptotic distributions referred above and,
> therefore, it would invalidate the estimation and inference on the
> cointegrating equations.
>
> Reference:
>
>  Johansen, S. 1995. Likelihood-Based Inference in Cointegrated Vector
>        Autoregressive Models. Oxford: Oxford University Press.
>
>
>
> Gustavo Sanchez
> gsanchez@stata.com
>
> *
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> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>

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