Re: [Gretl-users] Variable selection
On Sat, 16 Jun 2018, John C Frain wrote:
Perhaps there is some justification in model reduction as implemented
in
David Hendry's Pc-gets or in the Grocer package in Scilab. This does use a
form of model reduction but it is very restricted. Otherwise what are the
benefits of systems of stepwise regression. If you do arrive a a somewhat
sensible looking answer you can make no structural econometric inference.
How do you overcome the problems mentioned by Clive Nicolas. You then
need a completely new and independent data set to make statistical
inferences on the new theory. Perhaps you are simply interested in data
reduction.
Can you give me one good example in which a stepwise regression program
produces results that are not subject to the objections mentioned by
Clive. OLS, VARS etc may be abused by some but such routines are the basis
of much good work. Stepwise regression is not.
On a personal level, I agree 100%. As Clive remarked, the statistical
issues implied by automatic model selection are indeed thorny. The only
convincing framework in which you can (to some extent) substitute human
judgement with CPU cycles is BMA, but apart from that I myself would never
base any critical statistical procedure on tools like stepwise regression.
Having said that, however, I believe that the purpose of the gretl project
is not to tell the world how econometrics should be done. I've never liked
those schools of econometric thought that lend themselves to almost
religious allegiance: I'm old enought to remember (and shudder at) the
zeal of some converts to the LSE approach back in the 80s and I'm frankly
puzzled by the gospel-like status a certain not-so-harmless book has
gained in recent years.
In my opinion, our goal is to provide a tool for doing econometrics, whose
two main features are
1) political: gretl is free (in the "libre" sense: see
https://en.wikipedia.org/wiki/Gratis_versus_libre)
2) technical: gretl should offer the best possible compromise between ease
of use and technical efficiency (where the word "best" is of course open
to interpretation).
One of the consequences of the points above is that allowing people to
make mistakes is part of our job. Sometimes you will want to do the wrong
thing: when teaching, for example, to expose fallacies. Or, in a research
context, you may want to replicate other people results, and do so by
using free tools. Gretl must be up to the job, and therefore I'm all in
favour of implementing statistical techniques I would never trust myself.
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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