Well yes, that was my first suggestion. That's the difference between "doesn't react" or "doesn't move (at all)".

But for the IRFs it shouldn't make a difference whether you put y2 as exogenous or if you explicitly estimate this restricted structure with a univariate y2 equation. Assuming you don't care about the shock in this y2 equation, only about the shocks in y1 and y3.

Where it would make a difference AFAICS is if either you want to do actual forecasts, or perhaps if you want to get confidence bands with parameter uncertainty. [Without further thinking I'm not 100% sure about this latter point, however, but it seems plausible.]

-sven

Ok, I will try to estimate the SVAR with x_1 as exogenous, I am also quite sure that the SVAR package allows it. But I am getting a little but confused!

Actually I am trying to follow a paper where the authors do this exercise, they have

Yt=(y1, y2, y3).

They shock y1, and they check the effects on y2 and y3. As for y3, they say that there is a direct effect, and an indirect effect (via y2). To isolate these 2 effects, what they do is:

"to restrict the coefficients of the underlying VAR in such a way as to force the response of y2 to a shock in y1 to be zero [...] we postulate a different (restricted) economic structure, i.e. y2 is structurally not allowed to respond to y1 and y3 shocks [...]. A necessary condition is to set the impact reaction =0. This plus restricting the AR coefficients on lagged y1 and y3 in the y2 equation will be sufficient for imposing that y2 does not react to a y1 shock at any horizon"

It seems that your first suggestion was the way to replicate what they do, isn't it? But I don't know how to do it in gretl!

Gabriela

2013/6/4 Sven Schreiber <svetosch@gmx.net>

Am 04.06.2013 16:20, schrieb Gabriela Nodari:> Dear Sven,Well, if a system variable is not endogenously responding, we typically

>

> Thanks for your timely answer! I guess you understood right. But let me

> try to be more precise.

>

> I want to check the effects of a shock within the VAR by restricting the

> x_1 variable to not move.

call it exogenous instead. To me it seems that that's what you

(implicitly) want to do: create a scenario where x_1 is treated as

exogenous.

My first suggestion was to implement that by changing the x_1 equation

to a univariate equation only including lagged values of x_1. But if you

say "x_1 shouldn't change" that would probably not be the correct

implementation: Instead you would replace the x_1 equation by some

totally pre-specified scenario path, presumably a constant value. (If

you don't do actual forecasting but just IRFs, then I guess you don't

really have to specify these paths.)

I'm not up to date on the capabilities of the SVAR package,

unfortunately -- wait, I'm actually curious myself, so I'll check the

docs... and in the help file it says that that you can specify a list of

exogenous variables, so it seems you should be alright.

hth,sven

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