10:37 a.m.
Thanks Stev.
I have used this procedure to study Granger causality from X to Y in a
trivariate VAR:
r=158 ## number of observation
ysim=Y
xsim=X
Zsim=Z
system method=sur
equation Y const Y(-1) Y(-2) Z(-1) Z(-2)
equation X const Y(-1) Y(-2) X(-1) X(-2) Z(-1) Z(-2)
equation Z const Y(-1) Y(-2) X(-1) X(-2) Z(-1) Z(-2)
end system
genr residui=$uhat
genr M=$coeff
loop for i=3..r --quiet
ysim[i]=M[1]+M[2]*ysim[i-1]+M[3]*ysim[i-2]+M[4]*zsim[i-1]+M[5]*zsim[i-2]
xsim[i]=M[6]+M[7]*ysim[i-1]+M[8]*ysim[i-2]+M[9]*xsim[i-1]+M[10]*xsim[i-2]+M[11]
*zsim[i-1]+M[12]*zsim[i-2]
zsim[i]=M[13]+M[14]*ysim[i-1]+M[15]*ysim[i-2]+M[16]*xsim[i-1]+M[17]*xsim[i-2]+M
[18]*zsim[i-1]+M[19]*zsim[i-2]
loop replics --quiet ### BOOTSTRAP
smpl full
Ysim=ysim
Xsim=xsim
Zsim=zsim
genr A=resample(residui)
loop for i=3..r --quiet
Ysim[i]=ysim[i]+A[i-2,1]
Xsim[i]=ysim[i]+A[i-2,2]
Zsim[i]=ysim[i]+A[i-2,3]
endloop
...................endloop
There is a strange result when I apply the bootstrap procedure. In fact the
statistic test based on observed data is very large, but the bootstrap p-value
is greater then 0.8 and I do not reject the null hypothesis of Granger non-
causality from X to Y. The results are different if I work considering only the
equation
equation Y const Y(-1) Y(-2) X(-1) X(-2) Z(-1) Z(-2)
Under the null hypothesis I replace the series Y. In this case the bootstrap p-
value is very small and I reject the null hypothesis of no-causality. I don't
understant the different between these p-values.
Best regards.
Alessandro
----Messaggio originale----
Da: gretl-users-request(a)lists.wfu.edu
Data: 16/02/2012 18.00
A: <gretl-users(a)lists.wfu.edu>
Ogg: Gretl-users Digest, Vol 61, Issue 11
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Today's Topics:
1. Bootstrap VAR models (alexkakashi(a)libero.it)
2. Re: Bootstrap VAR models (Sven Schreiber)
3. Gretl error/crash ((s) Simon Grenville-Wood)
4. Re: Gretl error/crash (Riccardo (Jack) Lucchetti)
5. Re: Gretl error/crash ((s) Simon Grenville-Wood)
6. Random-effects panel-data (Helgi Tomasson)
----------------------------------------------------------------------
Message: 1
Date: Thu, 16 Feb 2012 09:34:37 +0100 (CET)
From: "alexkakashi(a)libero.it" <alexkakashi(a)libero.it>
Subject: [Gretl-users] Bootstrap VAR models
To: gretl-users(a)lists.wfu.edu
Message-ID: <25986877.1523161329381277575.JavaMail.root@wmail22>
Content-Type: text/plain;charset="UTF-8"
Hi,
I have the following question. Let us consider a trivariate VAR model. The
parameters of the model are estimated using:
system method=sur
equation Y const Y(-1) X(-1) Z(-1)
equation X const Y(-1) X(-1) Z(-1)
equation Z const Y(-1) X(-1) Z(-1)
end system
I'd like study Granger causality from X to Y and the critical values are
calculated using bootstrap method based on residuals. Is this procedure
implemented in gretl?
Best regards.
Alessandro
------------------------------
Message: 2
Date: Thu, 16 Feb 2012 10:18:44 +0100
From: Sven Schreiber <svetosch(a)gmx.net>
Subject: Re: [Gretl-users] Bootstrap VAR models
To: gretl-users(a)lists.wfu.edu
Message-ID: <4F3CC9F4.4050602(a)gmx.net>
Content-Type: text/plain; charset=ISO-8859-1
On 02/16/2012 09:34 AM, alexkakashi(a)libero.it wrote:
> Hi,
>
> I have the following question. Let us consider a trivariate VAR model. The
> parameters of the model are estimated using:
>
> system method=sur
> equation Y const Y(-1) X(-1) Z(-1)
> equation X const Y(-1) X(-1) Z(-1)
> equation Z const Y(-1) X(-1) Z(-1)
> end system
>
> I'd like study Granger causality from X to Y and the critical values are
> calculated using bootstrap method based on residuals. Is this procedure
> implemented in gretl?
>
Not that I know of, but have a look at the varsimul() and resample()
functions, with those it's not too difficult to program it.
hth,
sven
------------------------------
Message: 3
Date: Thu, 16 Feb 2012 14:50:11 +0000
From: "(s) Simon Grenville-Wood"
<simon.grenville-wood(a)students.plymouth.ac.uk>
Subject: [Gretl-users] Gretl error/crash
To: "gretl-users(a)lists.wfu.edu" <gretl-users(a)lists.wfu.edu>
Message-ID:
<A775801493FD6643B49F9B292B0376FB2F63D3CC(a)AMSPRD0302MB113.eurprd03.prod.
outlook.com>
Content-Type: text/plain; charset="iso-8859-1"
Hi,
I'm currently attempting a multinomial logit model on a large sample of panel
data.
I'm having a problem where I need to be able to create dummies for
each
individual in the sample to control for the individual fixed effects.
In order to do so while using the logit model, I need to dummify the person
ID
(PID) in the sample.
I've opened the gretl console and I enter the following commands:
discrete PID <----transform the variable, 19,421 values, to be discrete
dummify PID <----create dummies for each individual to control for fixed
effects
The last command causes gretl to crash, giving a libcairo_32.dll error. This
happens on whichever computer I am using. Occasionally, if I use the menus
instead of the console, it will give an 'out of memory' error. My PC is
definitely sufficiently powerful.
>
>Does anyone have any ideas as to how I can get around this issue?
>
>Thanks,
>
>Simon
>
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