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RE: st: collin


From   DE SOUZA Eric <[email protected]>
To   "[email protected]" <[email protected]>
Subject   RE: st: collin
Date   Sat, 12 Mar 2011 16:52:49 +0100

This is exactly what I thought you had, not just collinearity but perfect collinearity.
The question is: why are you getting perfectly collinearity?
Your y's appear to be constants.
Could you produce the results of  -summarize y*- ?

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Aggie Chidlow
Sent: 12 March 2011 16:45
To: [email protected]
Subject: Re: st: collin

Dear Eric,
Thank you for your advice... will definetly look this reference up.

When I run my model with all dummies as the reviewer wants me to:

probit  y x1 x2 x3 lnx4  x5 y98 y99 y00 y01 y02

where:
y98=463
y99=494
y00=425
y01=406
y02=376
y03=88 -not included in the model due to dummies trap

I get the regression results that say the follwing:
note: y00 omitted because of collinearity
note: y01 omitted because of collinearity
note: y02 omitted because of collinearity

The coefficients for y00 y01 and y02 are not reported in the model and there is a note which says y00 (omitted); y01 (omitted) and y02 (omitted).

By the way the collin for year dummies is as follow:
 Collinearity Diagnostics

                        SQRT                   R-
  Variable      VIF     VIF    Tolerance    Squared
----------------------------------------------------
      y98 -3.37e+13       .   -0.0000      1.0000
      y99 -3.53e+13       .   -0.0000      1.0000
      y00 -3.16e+13       .   -0.0000      1.0000
      y01 -3.05e+13       .   -0.0000      1.0000
      y02 -2.87e+13       .   -0.0000      1.0000
      y03 -7.74e+12       .   -0.0000      1.0000
----------------------------------------------------
  Mean VIF -2.79e+13

                           Cond
        Eigenval          Index
---------------------------------
    1     2.0000          1.0000
    2     1.0000          1.4142
    3     1.0000          1.4142
    4     1.0000          1.4142
    5     1.0000          1.4142
    6     1.0000          1.4142
    7     0.0000               .
---------------------------------
 Condition Number              .
 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept)
Det(correlation matrix)   -0.0000


I would appreciate any suggestions.

Many thanks in advance.
.


On Sat, Mar 12, 2011 at 11:16 AM, DE SOUZA Eric <[email protected]> wrote:
> 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: [email protected] 
> [mailto:[email protected]] On Behalf Of Syed Basher
> Sent: 12 March 2011 11:57
> To: [email protected]
> 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 <[email protected]>
> To: [email protected]
> 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 <[email protected]> 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 <[email protected]>
>> To: [email protected]
>> 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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