6:26 a.m.
Am 14.09.2020 um 09:30 schrieb Adam Elderfield:
Yes, that is how I think I would attack it. I think a simple solution
would be to create a function that takes estimated parameters and writes them to a text
file which BIMETS will read as an identity.
I don't think it would be correct to
label these equations as
identities. (If I'm not misunderstanding what you meant.) The simulation
will often be stochastic and thus an error term plus estimated variance
would be needed. I don't think that's a problem per se, but so far I
don't know how to tell bimets the estimation results including those
variances and so on, or more fundamentally if there's some kind of
interface in bimets for this "injection" of already estimated but
non-identity equations.
One challenge would be translating what is an acceptable way to
express an equation in GRETL into something that can be read in BIMETS for example:
"ln (Y/Y(-1)) = coef(1)*(ln(Y(-1))-coef(2)*ln(X(-1)))+coef(3)*ln (Y(-1)/ Y(-2)) +
coef(4)*ln(X/X(-1))"
While BIMETS it would be something like:
"TSDELTALOG(Y) =
coef(1)*(TSLAG(LOG(Y),1)-coef(2)*TSLAG(LOG(X),1))+coef(3)*TSDELTALOG(Y,1) +
coef(4)*TSDELTALOG (X)"
So I think a small task would be to parse a GRETL acceptable language (I'm not sure
if my equation above is an acceptable format for GRETL, but I hope illustrates the point?)
into something readable by BIMETS, i.e. replace the (-1) with TSLAG etc and hard code the
coefficient estimates from various estimation outputs in the GRETL environment to the text
file.
All very adequate thoughts, but I will reply to Jack's answer first, as
it is more fundamental...
cheers
sven
7:27 a.m.
New subject: Simulate simultaneous equation model
Stochastic simulation would be a nice option. However, I don't think it is currently
available in BIMETS, I spoke with Andrea Luciani a while ago who told me that it was on
the to do list. Andrea actually referred to it as
* "Perturbation analysis": e.g. add noise (normal, uniform, etc ) to
selected exogenous and return average, stddev, etc... of simulated endogenous
However, I took that as meaning stochastic simulation. This was a few months ago, so this
could very well be underway now.
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________________________________
From: Sven Schreiber <svetosch(a)gmx.net>
Sent: Monday, 14 September 2020, 8:26 pm
To: gretl-devel(a)gretlml.univpm.it
Subject: [Gretl-devel] Re: Simulate simultaneous equation model
Am 14.09.2020 um 09:30 schrieb Adam Elderfield:
Yes, that is how I think I would attack it. I think a simple solution
would be to create a function that takes estimated parameters and writes them to a text
file which BIMETS will read as an identity.
I don't think it would be correct to
label these equations as
identities. (If I'm not misunderstanding what you meant.) The simulation
will often be stochastic and thus an error term plus estimated variance
would be needed. I don't think that's a problem per se, but so far I
don't know how to tell bimets the estimation results including those
variances and so on, or more fundamentally if there's some kind of
interface in bimets for this "injection" of already estimated but
non-identity equations.
One challenge would be translating what is an acceptable way to
express an equation in GRETL into something that can be read in BIMETS for example:
"ln (Y/Y(-1)) = coef(1)*(ln(Y(-1))-coef(2)*ln(X(-1)))+coef(3)*ln (Y(-1)/ Y(-2)) +
coef(4)*ln(X/X(-1))"
While BIMETS it would be something like:
"TSDELTALOG(Y) =
coef(1)*(TSLAG(LOG(Y),1)-coef(2)*TSLAG(LOG(X),1))+coef(3)*TSDELTALOG(Y,1) +
coef(4)*TSDELTALOG (X)"
So I think a small task would be to parse a GRETL acceptable language (I'm not sure
if my equation above is an acceptable format for GRETL, but I hope illustrates the point?)
into something readable by BIMETS, i.e. replace the (-1) with TSLAG etc and hard code the
coefficient estimates from various estimation outputs in the GRETL environment to the text
file.
All very adequate thoughts, but I will reply to Jack's answer first, as
it is more fundamental...
cheers
sven
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