Re: st: Re: AIC and BIC values after ARIMA estimation

[Robert A Yaffee <bob.yaffee@nyu.edu>]

Alejandro,
  There are several different formulae for computing the information criteria.
The state manual addresses this issue.    You will find that some researchers
divide part of the formula by the sample size whereas others do not.   In your
command line, type    help BIC note
   Regards,
       Robert
   
Robert A. Yaffee, Ph.D.
Research Professor
Silver School of Social Work
New York University

Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf

CV:  http://homepages.nyu.edu/~ray1/vita.pdf

----- Original Message -----
From: Alejandro Mosiño <Alejandro.Mosino@univ-savoie.fr>
Date: Thursday, January 27, 2011 12:40 pm
Subject: st: Re: AIC and BIC values after ARIMA estimation
To: statalist@hsphsun2.harvard.edu


> Thank you very much for your answer,
> 
> Actually yes, i cheked the signs. They are all negatives, so... 
> believe 
> me, that's is not the problem.
> 
> I understand that AICs and BICs are not comparable across software, 
> but 
> i think the decision of what model to choose should be (if not equal) 
> 
> very similar. In my particular case, i'm using data for the yen / 
> dollar 
> exchange rate. The results using Eviews are published in a book by 
> Francis X. Diebold (Elements Forecasting, chapter 13). I replicated 
> the 
> analysis using the same data (that you can download from the author's 
> 
> web page or the book's companion site) on Gretl and Stata. As i told 
> you, Gretl is giving me similar results, but Stata does not.
> 
> I'm a big fan of Stata, so, i don't know. Maybe there is another way 
> of 
> computing AIC and BIC. Any suggestions?
> 
> Best,
> 
> Alejandro
> 
> 
> 
> 
> 
> 
> El 27/01/2011 04:18 p.m., Maarten buis escribió:
> > --- On Thu, 27/1/11, Alejandro Mosiño wrote:
> >> I have this problem. I'm selecting ARIMA models by using
> >> AIC and BIC criteria. However, i got very different results
> >> from different softwares (Eviews, Gretl and Stata). In one
> >> case for instance, Gretl and Eviews tell me that the right
> >> model is an ARMA(2,0), while Stata tells me that it is an
> >> ARMA(2,2). Another example, Gretl and Eviews tell me that
> >> some other model should be an ARIMA(1,1,0), while Stata
> >> tells me that the right model is an ARIMA(0,1,1).
> >>
> >> Then, while Gretl and Eviews agree, Stata gives me VERY
> >> different results. Do you know why?
> > The absolute numbers for (log) likelihood values and thus
> > BICs and AICs are often not comparable across software.
> > There is often a term in the likelihood function that does
> > not depend on the parameters, and programmers can choose
> > to leave that term in or out without changing the maximum.
> >
> > Did you check the sign and adjusted what you call small
> > and large accordingly (it may sound like a silly mistake
> > to make, but you do not want to know (and I do not want to
> > tell) how often I made a mistake like that...)
> >
> > Hope this helps,
> > Maarten
> >
> > --------------------------
> > Maarten L. Buis
> > Institut fuer Soziologie
> > Universitaet Tuebingen
> > Wilhelmstrasse 36
> > 72074 Tuebingen
> > Germany
> >
> > http://www.maartenbuis.nl
> > --------------------------
> >
> >
> >
> >
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> 
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