Riccardo (Jack) Lucchetti schrieb:
My take on SVARs: if you want to do Structural VARs with free software,
the possible alternatives that come to my mind are:
1) use R + urca + vars
2) use jMulti
3) use my collection of scripts
I am deliberately excluding A. Warne's program since it isn't free
software (which is a shame, since it's very very good).
That's a bit harsh because the code is GPLed, "only" the platform
isn't.
Does anybody have an idea how much work it would be to adapt it to
run successfully in Octave (graphical stuff aside)?
Why not jMulti? Well, because despite being a very good package when it
comes to the algorithms, I'm sorry to say it's pretty much dead. A Linux
version hasn't been released for ages, and all the progress I've seen
for a while was some occasional bugfix. Plus, I'm not exactly
enthusiastic about the combination of gauss (or R) for number crunching,
java for the GUI and postscript for the output (too many things that can
go wrong). Last but not least, it's not scriptable.
Well as you may know because you mention R, the long-term plan by the
developer (Markus) indeed is to replace the Gauss engine with R code.
Then you would also get R graphics. (And BTW, the Gauss runtime engine
on Linux is buggy as I have experienced myself, so that's also a reason
why no current Linux version.) I have started to try to help with the
transition, but got stuck fairly early on because the structure of the
Gauss code in Jmulti needs "getting used to". (It's very well tested
though.) And I was basically trying to port _from_ a language I don't
know much about _to_ a language I don't know well either. So I guess
it's a call to the "community" -- if you want Jmulti to be alive you
need to do something about it. (No not you personally Jack.)
Why not R, then? To begin with, I think our own implementation of VARs +
cointegration-related stuff is better. Next, there's the usual gripe I
have with R: either you work with it all the time, or its syntax is,
let's say, unpleasant. I like to think that gretl's now excellent
interface to R allows us to use R as a fallback tool. But in the
long-term, I'd rather use gretl as much as possible.
Yes.
PS: Sven, with my functions you CAN do restricted SVECMs. The \beta
matrix is one of the inputs, and the function by itself doesn't care
about the way it was estimated (assistance by superconsistency is
gratefully acknowledged).
Ah very good, I should have noticed that. I guess that could be another
reason for working on the gretl code instead of the other solutions.
thanks,
sven