How to perform a recursive VAR

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Esteban
Posts: 1
Joined: Wed Mar 21, 2012 6:19 am

How to perform a recursive VAR

Postby Esteban » Wed Mar 21, 2012 6:49 am

Hi, I would like to estima a recursive VAR in eviews 7, following this model. But I'm not sure how to do it. Should I estimate a VAR and then use the "Cholesky - dof adjusted" option at the "Impulse definition" section of the impulse response function?

Could you enlighten me please?

Thanks
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ericasm
Posts: 1
Joined: Fri Mar 23, 2012 9:45 am

Re: How to perform a recursive VAR

Postby ericasm » Fri Mar 23, 2012 9:48 am

Yes, I would like to know this as well. Please help!

einstein999
Posts: 3
Joined: Thu Mar 29, 2012 7:07 am

Re: How to perform a recursive VAR

Postby einstein999 » Thu Mar 29, 2012 7:10 am

Hi,

I ve just got exact same question and cannot figure out how to do it in Eviews... Please, can someone help?

einstein999
Posts: 3
Joined: Thu Mar 29, 2012 7:07 am

Re: How to perform a recursive VAR

Postby einstein999 » Sun Apr 01, 2012 4:37 am

Is the approach of using reduced-form VAR with Choleski decomposition equivalent to recursive var?

shouvik
Posts: 1
Joined: Sat Dec 05, 2015 6:10 am

Re: How to perform a recursive VAR

Postby shouvik » Sat Dec 05, 2015 6:33 am

Hi,

I am new to the forum and still struggling to figure out how to post a new topic. But, I thought to continue this discussion on Recursive VAR since I could not find any suitable reply to this question. I am using EVIEWS9 and trying to replicate a Blanchard and Perotti (2002) paper published at QJE. The authors seem to have done Recursive VAR model.

Their model specifications are as follows:

The basic VAR specification is
(1) Yt=A(L,q)Yt-1+ Ut,
where Yt [Tt,Gt,Xt]' is a three-dimensional vector in the logarithms of quarterly taxes, spending, and GDP, all in real, per capita, terms.
Ut [tt ,gt,xt]' is the corresponding vector of reduced-form residuals, which in general will have nonzero cross correlations.
I have been able to solve for this VAR. Now the authors use the following identification methodology:

Without loss of generality, we can write
(2)tt, = a1 xt + a2 egt + et
(3) gt= b1 xt + b2 ett + egt
(4) xt = c1tt, + c2gt + et,
where et, ef , and et are the mutually uncorrelated structural shocks that we want to recover.

Can anyone please help us to specify this model in Eviews. I am struggling to incorporate this uncorrelated structural shocks in Eviews. I have able to get the residues from the VAR (eq 1) model. Any help on this will be really appreciated.


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