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This post is as a consequence of the following post: http://forums.eviews.com/viewtopic.php?f=4&t=21036 To illustrate the bug, I am using the sample code provided by Matt in responding to that post: create u 50 series x = rnd series y = x + rnd series z = nrnd var v.ls 1 2 x y z vector(3) struct...

Thank you very much, this is very helpful. Re (2), yes, obeying a specific Cholesky ordering (i.e. a structural VAR), I would like is to simultaneously increase by one unit the structural residuals associated with the first two variables (as opposed to conduct the standard exercise, whereby one incr...

I believe I have figured out the answer to my Re (1). What Eviews labels as "Cholesky One S.D. Innovation" is an increase in a structural residual by one unit; or, equivalently, an increase in the structural residual by 1SD of structural residual (given that the varcov matrix of structural...

Thank you for the response. I apologize for the following, I believe there is still some confusion on my end and I might not have articulated my question sufficiently accurately. Re (1): I was under the impression that, after estimating a VAR, the default choice of View->Impulse Response, using Chol...

I am trying to figure out how to properly use the user-specified impulse option after estimating a VAR. Specifically, I am having a hard time figuring out how to correctly specify the user-specified matrix/vector for the problem at hand. Suppose that I estimate a reduced-form VAR: var myvar.ls 1 4 g...

Got it, thank you. I also realized it's referred to as the S matrix in the structural-VAR part of the Eviews documentation, and thus that one can also get to it via performing Structural Factorization upon estimating a reduced-form VAR and then imposing identification restrictions that boil down to ...

Suppose I estimate a VAR and then impose a Cholesky ordering assumption to conduct some structural analysis (IRFs, historical decompositions). Eviews allows one to access both the reduced-form residuals (e) and the structural residuals (u). But how can one access the corresponding matrix, as implied...

After estimating a VAR and using a certain Cholesky ordering assumption, I’d like to access the numbers for Kilian’s unbiased bootstrap-based standard errors for the IRFs for different cilevels. To do so, I first estimate a VAR and name it myvar. Then I run, for example: myvar.impulse(30, m, se=boot...