Ok, thank you for clarification. I have another question then: Since Gretl
has an option to bootstrap the confidence interval, does that mean that the
impulse-response functions are valid even though the residuals of each VEC
equation are non-normal it their distribution? I know the t- and p-values
of the VEC output are unreliable with non-normal residual distribution, but
doesn't bootstrapping remedy this, since it relies on the "true probability
distribution"? Forgive me if I got it totally wrong, I'm only a beginner at
this.
Best regards,
Lars
2017-08-18 15:16 GMT+02:00 Allin Cottrell <cottrell(a)wfu.edu>:
On Fri, 18 Aug 2017, lasses skola wrote:
Hi, and thank you for your response! I am not using any addons to my
> knowledge. I was a big vague maybe. There is an option to calculate
> confidence intervals of the IRFs using bootstrapping.
> I think I put the question in the wrong way as well. What unit is the
> shock
> in? One standard deviation? Or SE of regression?
>
You've had a reply from Sven, but I believe he's thinking about the SVAR
addon rather than the behavior of the built-in "var" and "vecm"
commands.
For the built-in commands, the shock is one standard deviation of the
innovations of the variable in question. Here's a trivial example (using
"var" rather than "vecm" but that doesn't make a substantive
difference):
<hansl>
open data9-7
var 4 UNEMP PRIME --quiet
matrix IRF = irf(1,1)
print IRF
matrix S = $sigma # covariance matrix of innovations
printf "std deviation of UNEMP innovation: %.5f\n", sqrt(S[1,1])
</hansl>
If you run the above you should see that the IRF vector begins:
0.24541
0.29007
0.27650 ...
while the printf on the last line shows
"std deviation of UNEMP innovation: 0.24541"
hence confirming that the shock is one standard deviation (and the
response is in the "natural" units of the target variable).
Allin Cottrell
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