Dear Listmembers,
I have the following data set (there are many more variables and observations;
this is an example only):
id time income restaurant kid
1. 10105 15 3931.572 3
2. 10106 15 3931.572 3
3. 10107 15 3931.572 Freebirds 3
4. 10206 30 4289.5 MamasPizza 4
5. 10207 30 4289.5 4
6. 10208 30 4289.5 Madcows 4
7. 10210 30 4289.5 4
8. 10405 15 6843.571 Christophers 3
9. 10406 15 6843.571 CafeEccel 3
10. 10407 15 6843.571 3
11. 10504 30 7223.5 Losnortenos 3
12. 10505 30 7223.5 3
13. 10506 30 7223.5 3
14. 10710 30 13809.57 Wingsnmore 1
15. 10805 30 2809.111 4
I want to model the decision to eat at one of the restaurants using nlogit. My
problem differs from the famous STATA example as follows:
Not all individuals in the sample go to a restaurant for dinner. Some may not
feel hungry (i.e. they skip their dinner for this evening), those who feel
hungry may wish to cook at home. Only those who decide to go out choose one of
the six restaurants. The missing values in restaurant column above therefore
represent either "no-hungry" individuals or "love-homefood" individuals.
Typically, the decisions are:
Stage 1: Hungry (0=No; 1=Yes)
Stage 2: Eating place (0=Cook at home; 1=Go to Restaurant)
Stage 3: Restaurant (1= MamasPizza; 2=Freebirds; .........7=MadCows)
Does anyone help me how to generate nlogittree for this problem, and
subsequently estimating it? Do I need to reshape the data to long format
before generating the tree?
Thanks. I would appreciate receiving (preferably a quick) feedback.
Subhash.
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