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Re: st: comparing coefficients across models

From   Dalhia <>
To   "" <>
Subject   Re: st: comparing coefficients across models
Date   Thu, 2 Aug 2012 19:13:25 -0700 (PDT)

David, thanks. the previous post on this issue, and James' summary of it has been really helpful. 

To answer your question, I tried centering the variables but it doesn't help with collinearity. The reason is that I have 3 network variables in the model. The interaction term multiplies one of these with another network derived measure. 

Here is how I ran the model (with interaction term):

xtreg y x1 x2 x3 x3*group_dummy, fe robust

where y is log of Tobin's q (a measure of firm performance)
x2 is degree centrality (a network measure - continuous)
x3 is business group dummy (codes whether or not a firm belongs to a cluster of firms)
x3 is betweenness centrality (a network measure - continuous)
group_dummy is whether or not the firm belongs to a particular component in the network. 

x2 and x3 are the most  highly correlated (-0.73).

Any thoughts are welcome. I really appreciate the help.

----- Original Message -----
From: David Hoaglin <>
Sent: Friday, August 3, 2012 3:33 AM
Subject: Re: st: comparing coefficients across models

Hello, Dalhia.

Others have already given a useful suggestion for comparing the two

You should investigate the reason(s) for the collinearity problem that
you are reporting.  If x1 and x2 are continuous variables, it may be
helpful to center them (at their mean or at some other convenient

What was the actual model that produced the collinearity problem?

David Hoaglin

On Thu, Aug 2, 2012 at 4:41 PM, Dalhia <> wrote:
> Hello,
> I have two groups and need to run the same regression model
> on both groups (number of observations differ but variables are all the
> same). I am interested in the difference in the coefficients for one
> particular variable.
> here are the two models I am running:
> xtreg y x1 x2, fe robust if group==1
> xtreg y x1 x2, fe robust if group==2
> I cannot put the two groups together, and run the model with an
> interaction with dummy variable for group, because then the model becomes highly
> multicollinear, and the coefficients are not stable.
> Is there a test that can help me check if the coefficient on x2 differs significantly across the two groups?
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