st: two level model

[Viktor Slavtchev <viktor.slavtchev@uni-jena.de>]

dear,
I have followed model.
People can make (multiple) choices. For example, people can invest their 
money in different countries, whereat multiple investment options are 
possible at the same time.
Some people decide to invest all the money in (say) Germany, other 
decide to invest in both Germany and US, third group invests in Germany, 
US and UK.
The decision depends on country specific characteristics and on 
individual characteristics.
The estimation of the impact of country specific characteristics on the 
investment decision should be not problem since these characteristics 
are unique for each country.
But how to estimate the impact of individual characteristics on the 
investment decision since these are the same for each individual (do not 
differ with the different countries within one person)?
Example

id 	country 	investment_share 	interest_rate 	gender
1 	Germany 	.2 	.02 	0
1 	US 	.5 	.03 	0
1 	UK 	.1 	.025 	0
1 	France 	.1 	.022 	0
1 	Italy 	.1 	.023 	0
2 	Germany 	.6 	.02 	1
2 	US 	.1 	.03 	1
2 	UK 	.1 	.025 	1
2 	France 	.1 	.022 	1
2 	Italy 	.1 	.023 	1
3 	Germany 	.2 	.02 	0
3 	US 	.5 	.03 	0
3 	UK 	.1 	.025 	0
3 	France 	.1 	.022 	0
3 	Italy 	.1 	.023 	0



I've just tried followed:
xi: glm investment_share interest_rate gender i.id, family(binomial) 
link(logit) scale(x2)

Is this an appropriate way to solve the problem?
Or should I use some kind of multilevel approach?
Could -xtmixed- be an appropriate method?
Or perhaps there is another way?
Tanks for any help.
best
viktor



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