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.    



John C Frain
3 Aranleigh Park


On Fri, 15 Jun 2018 at 22:36, Periklis Gogas <perrygogas@gmail.com> wrote:
​I disagree 95%.

If we start taking out all the functions, methodologies, menu items that can be miss-used then we are left only with a spreadsheet...​
OLS can be misused, VARs, R2, p-values and so on. Everything can be misused.

Even trying to teach students the disadvantages of these methods it is worth the while. 



On Fri, Jun 15, 2018 at 11:55 PM Sven Schreiber <svetosch@gmx.net> wrote:
Am 15.06.2018 um 21:57 schrieb Clive Nicholas:
I agree with John 150%:stepwise regression models (and their ilk) are a poor substitute for proper thinking about model specification and simply shouldn't be used, for _anything_!

I agree maybe about 95% :-)

The statistical points you remind us of are of course valid. Still that doesn't mean that a formalized model specification search is never to be used. The question is indeed how to communicate that problem in a software package (including the existing omit --auto option). Perhaps the result of such a procedure should be presented wihtout standard errors or something like that. An easier solution would probably be to include a warning message.

BTW, the Lasso and other modern tools haven't been mentioned yet. Indeed I wouldn't currently recommend to try to reinvent the wheel in hansl. It is relatively easy to wrap the R packages glmnet and sparsenet in a gretl function.

cheers,
sven
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