Hi all,
I have a kind of specific question. I am working on a
multinomial logit model with social interactions, in
line with the work of Durlauf. (I already grouped the
people in my dataset according to their socioeconomic
status.) However the estimation results are kind of
strange.
To see the social interactions (endogeneous and
contextual effects) I have four variables:
- The percentage of people making the same choice as
oneself within his reference group
- Three variables of group averages (average culture,
education and income levels within the reference group
of oneself)
In the results, the coefficients of all choices except
one seems ok. For one of the choices the vairance of
all estimated coefficients are so big that the
associated p-values are equal to 1.
The reason that I considered was a high correlation
between these variables within the group of people
having this problematic choice. However, it is the
contrary: the correlations within the groups of people
with other choices are much higher, in fact around
0.9. On the other hand, within this problematic choice
the correlations are all less than 0.5.
Is there anyone who can figure out what the problem
might be? Can it be multicollinearity? If needed, I
can send my estimation output, and discuss more about
the subject, which I need desperately :)
Thanks.
Uygar
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