Dear all ,
I would like to run a Nested logit Model .
The data are such as for each observation, I have one possible choice (the
number of alternative for the choice is 4 for level 1 - bottom level- and 2
for level 2 - top level) and the dependant variables are related to the
observations, not the alternatives. Here is an example of the row data
id Choice _top choice_bottom age education ...
1 1 1 45
3
2 1 2 56
6
3 2 1 39
4....
The top choice has 2 alternatives and each alternative of the top choice
has 2 alternatives. At the end, I have 4 alternatives (at the bottom).
The dependant variables are linked to the observations, not the
alternatives.
I transformed the data before the procedure nlogit estimation as stated the
the stata manual:
id Choice _top decision age_1 edu_1 edu_2 edu_3
choice ...
1 1 1 45 3 0
0 1
1 1 0 45 0 3
0 2
1 0 0 0 0 0
0 3
1 0 0 0 0 0
0 4
2 1 0 56 6 0
0 1
2 1 1 56 0 6
0 2
2 0 0 0 0 0
6 3
2 0 0 0 0 0
0 4
.....
Below is the code I used:
nlogit chosen (decision = edu_1 edu_2 edu_3) (choice_top= age_1), group(id)
robust
edu_1~edu_3 are the bottom level dependent variables and age_1 is the top
level dependant variable
Unfortunately, when I ran this model it doesn't converge and I tries several
specification for the variables. But after a few hours, there is no converge
for the ML procedure.
I have 2 questions:
1. How to set up the data in my case to run this model? Is the way I have
that is correct?
2. How to interpret the result I will get? I know how to interpretre the
data for the dummy regressor I created but what about the other other
variables?
Thanks in advance for any help you can give me.
Gaston Gohou
PhD Candidate
University of Maryland, College Park
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