RE: st: collin

[SR Millis <aa3379@wayne.edu>]

I would suggest that your examine the condition indexes: see if that are any that exceed 20-30.  For those that do, examine their associated variance decomposition proportions: see if any exceed .50.  For those that do, identify their associated variables---and you will find the sources of high collinearity.

SR Millis  


--- On Sat, 3/12/11, DE SOUZA Eric <eric.de_souza@coleurope.eu> wrote:

> From: DE SOUZA Eric <eric.de_souza@coleurope.eu>
> Subject: RE: st: collin
> To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
> Date: Saturday, March 12, 2011, 6:16 AM
> I haven't been following this thread
> till now.
> Jeffrey Wooldridge in his introductory textbook (page 99,
> international edition) does not encourage use of the VIF .
> The variance of a coefficient depends on three factors: the
> standard error of the regression, the total sample variation
> in the variable attached to the coefficient and the partial
> R2 . Concentrating on the partial R2 has no justification,
> even less so the rule of 10.
> 
> However, in this case, the referee will probably have to be
> satisfied in some way or the other.
> 
> Aggie, when you say that the dummies were dropped on
> account of collinearity, what exactly do you mean? 
> 
> Eric 
> 
> 
> Eric de Souza
> College of Europe
> Brugge (Bruges), Belgium
> http://www.coleurope.eu
> 
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu]
> On Behalf Of Syed Basher
> Sent: 12 March 2011 11:57
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: collin
> 
> Dear Aggie,
> 
> I recently used VIF in one of my papers. You can find the
> discussion here:
> http://ideas.repec.org/p/pra/mprapa/27348.html
> -- See p. 14 (footnote 23) and p. 22
> 
> A general rule of thumb in economics is a VIF>10
> indicates harmful collinearity. 
> Hope you find this useful.
> 
> Syed Basher
> Doha, Qatar.
> 
> 
> 
> 
> ----- Original Message ----
> From: Aggie Chidlow <mojamalarybka@googlemail.com>
> To: statalist@hsphsun2.harvard.edu
> Sent: Sat, March 12, 2011 1:36:26 AM
> Subject: Re: st: collin
> 
> Dear Charls and Syed,
> Thank you very much for your comments and suggestions.
> 
> I would be thankful very much for your help Syed regarding
> how to interpret VIF professionaly. Any advice/references
> would be very much appreciated.
> 
> Many thanks,Aggie
> 
> On Thu, Mar 10, 2011 at 3:14 PM, Syed Basher <syed.basher@yahoo.com>
> wrote:
> > Hi Aggie,
> >
> > I think diagnostic checking such as VIF comes before
> estimation, that 
> > is we first check the extent of collinearity among
> variables using VIF 
> > then decide which variables to include in the
> estimation. After 
> > running VIF, you can do
> two
> > sets of estimation: one with all dummies (what the
> reviewer asked for) 
> > and another with least collinear dummies (as you
> already did), this 
> > way the difference between two results will show up.
> As Charles 
> > mentioned, it is
> better
> > to follow what the reviewer has asked for. If you
> wanted to know how 
> > to interpret VIF results professionally, let me know.
> >
> > Syed Basher
> > Doha, Qatar
> >
> >
> >
> > ----- Original Message ----
> > From: Aggie Chidlow <mojamalarybka@googlemail.com>
> > To: statalist@hsphsun2.harvard.edu
> > Sent: Thu, March 10, 2011 4:30:51 PM
> > Subject: st: collin
> >
> > Dear Stata users,
> >
> > I was appreciate some help regarding "collin"
> >
> > I just got a paper back from a reviewer and he/she
> wants me to include 
> > all my year dummies (i.e. y98 y99 y00 y01 y02 y03) in
> the following
> > model: probit  y x1 x2 x3 lnx4  x5 y98 y99
> y00 y01 y02
> >
> > Previusly in the model I only included two year
> dummies (i.e y99 and
> > y01) as the others we omitted automatically due to
> collinearity.
> > I mentioned that in the paper, however, he/she says it
> is 
> > unsatisfactory and I should include them all and than
> comment on VIF.
> >
> > Please, can somebody tell me how I can go about this?
> > Any advise and/or references will be more than
> appreciated.
> >
> > Many thanks in advance.
> > Aggie
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