Re: R: st: R: linear regression question

[dr kardos laszlo <l_kardos@chello.hu>]

dear carlo,

that is not exactly what i was suggesting. the way i see this, 
thoroughly checking that the base is natural is not enough. 100*beta% is 
practically always different from 100*(exp(beta)-1)%. one can use the 
former and go the extra step judging each time whether the deviance from 
the real thing is tolerable. i know i wouldn't. there is simply no gain 
in simplicity or anything.

best regards,
laszlo

Carlo Lazzaro wrote:
> Dear Laszlo,
> thanks for your remark. The potential misleading arises because the use of
> natural log is the reference in econometrics textbook. However, as you
> suggested, a thorough check of this requirement should be made, in order to
> avoid bewildering results. 
>
> Kind Regards,
> Carlo
>
> -----Messaggio originale-----
> Da: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di dr kardos laszlo
> Inviato: martedi` 17 marzo 2009 8.34
> A: statalist@hsphsun2.harvard.edu
> Oggetto: Re: st: R: linear regression question
>
> unless i got something wrong,
> the relative change in y associated with a unit change in x in such 
> models works out as antilog(beta) on the appropriate base. in this case, 
> because galina explicitly mentioned natural log, and using carlo's 
> example, it is exp(.2) = 1.2214, a 22.14% increase. try with base-10 and 
> you will get something completely different.
>
> the approximation 100*beta% works better and better as beta approaches 
> zero (and as the log-transformation base approaches 1, but that's not 
> typical in practice). in the stata journal article referred to below, 
> beta=.0741516 and exp(beta)=1.07697, arguably close to 1.07415. in other 
> cases, the difference might be to an extent you do not want to ignore.
>
> laszlo
>
> Galina Hayes wrote:
>   
> > Thanks very much everyone, very helpful.
> > Galina
> > ----- Original Message -----
> > From: "Maarten buis" <maartenbuis@yahoo.co.uk>
> > To: statalist@hsphsun2.harvard.edu
> > Sent: Sunday, March 15, 2009 11:48:52 AM GMT -05:00 US/Canada Eastern
> > Subject: Re: st: R: linear regression question
> >
> >
> > --- On Sun, 15/3/09, Carlo Lazzaro wrote:
> >   
> >     
> > > your thread seems to refer to a log-linear model, where
> > > only the dependent variable (i.e., Y) is log-transformed.
> > >
> > > In a log-linear model, a unit-change in the independent
> > > variable X (i.e., DeltaX=1)is associated with a 100*Beta% 
> > > change in Y.
> > >     
> > >       
> > This is one possible way of interpreting such a model. An 
> > alternative way is discussed in: Roger Newson (2003) "Stata
> > Tip 1: The eform() option with regress" The Stata Journal,
> > 3(4): 445. 
> > http://www.stata-journal.com/article.html?article=st0054
> >
> > Both interpretations are correct, they are just different
> > ways of looking at the same model.
> >
> > Hope this helps,
> > Maarten
> >
> > -----------------------------------------
> > Maarten L. Buis
> > Institut fuer Soziologie
> > Universitaet Tuebingen
> > Wilhelmstrasse 36
> > 72074 Tuebingen
> > Germany
> >
> > http://home.fsw.vu.nl/m.buis/
> > -----------------------------------------
> >
> >
> >       
> >
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