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Re: st: restricted VAR for preselection of instruments


From   Robert A Yaffee <[email protected]>
To   [email protected]
Subject   Re: st: restricted VAR for preselection of instruments
Date   Wed, 24 Dec 2008 16:16:32 -0500

Sebastien,
   Alternatively, you could try something like
var dln_inv dln_inc dln_consump, lags(1/3) lutstats
est store mod1
var dln_inv dln_inc dln_consump, lags(1/2) lutstats
est store mod2
var dln_inv dln_inc , lags(1/2) lutstats
est store mod3
est stats _all
        
     Regards,
              Bob



Robert A. Yaffee, Ph.D.
Research Professor
Silver School of Social Work
New York University


Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2008.pdf

CV:  http://homepages.nyu.edu/~ray1/vita.pdf

----- Original Message -----
From: Robert A Yaffee <[email protected]>
Date: Wednesday, December 24, 2008 4:10 pm
Subject: Re: st: restricted VAR for preselection of instruments
To: [email protected]


> Sebastien,
>   I think you could set up a do file with your sequential VAR 
> equations specified within it.
> After each equation, you could save the e(hqic) or e(sbic) and compare 
> them to ascertain
> which is the lowest.
>   Regards,
>           Bob Yaffee
> 
>   
> 
> Robert A. Yaffee, Ph.D.
> Research Professor
> Silver School of Social Work
> New York University
> 
> 
> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2008.pdf
> 
> CV:  http://homepages.nyu.edu/~ray1/vita.pdf
> 
> ----- Original Message -----
> From: Sebastian Kruk <[email protected]>
> Date: Wednesday, December 24, 2008 3:05 pm
> Subject: st: restricted VAR for preselection of instruments
> To: [email protected]
> 
> 
> > Dear stalistusers,
> > 
> >  I would like to do a preselection of possible instruments within a
> > VAR. The two endogenous variables variables π(t+1) and s(t) are
> > regressed on all potential instruments. This specification can be
> > formalized as:
> > 
> > π(t+1)=v1+A11*π(t-1)+A12*π(t-2)+...+A1j*π(t-j)+B11*x(t-1)+B12*x(t-2)+...+B1j*x(t-j)
> > s(t)=v2+A21*s(t-1)+A22*s(t-2)+...+A2j*π(t-j)+B21*x(t-1)+B22*x(t-2)+...+B2j*x(t-j)
> > 
> > with v1,v2 a a deterministic term, and x(t−j) the vector of all other
> > predetermined variables with lag j. The maximal lag length is L1 = 10
> > and L2 = 5.
> > 
> > Can I apply a model reduction procedure that works through a
> > sequential elimination of regressors in order to obtain a model that
> > lead to the smallest value of the particular information criterion as
> > Lutkepohl, H. (2005). New introduction to multiple time series
> > analysis, Springer?
> > 
> > I follow Scheufele R. (2008). Evaluating the German (New Keynesian)
> > Phillips Curve, IWH-Diskussionspapiere 10/2008.
> > 
> > Thanks in advance,
> > 
> > Sebastian.
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