Re: st: Re: Making Cohorts

[Maarten buis <maartenbuis@yahoo.co.uk>]

--- On Thu, 28/10/10, ajjee <wrote:
> I want to implement the following strategy on my data.
> 
> 
> Consider now the basic linear individual effect model
> 
> yit = ai + bXit + uit    i = 1,..N; t = 1,..T       eq(1)
> 
> where Xit is a (K x 1) vector of explanatory variables
> which we assume exogenous to the model, index t and
> i refer to time and individuals respectively.
> Assuming, for simplicity, that there is a unique regressor
> (K = 1), if we aggregate all observations to cohort level,
> the resulting model can be written as
> 
> (y-bar)_ct = (a-bar)_ct + b(x-bar)_ct + (u-bar)_ct  c = 1,..C
> 
> 
> where (x-bar)_ct is the average value of all observed
> xit’s in cohort c at time t, and analogously for the other
> variables in the model. The resulting data set is a pseudo
> panel with repeated observations over T periods and C
> cohorts.
> 
> now I want to make cohorts (say for) birth year and then
> want to aggregate the data as above.  But I have 15 countries
> also and I want to analyse particular attitudes in countries
> based on three year surveys(6 waves).

You earlier stated that you wanted to do a -logit- analysis. 
This type of averaging does not work in non-linear models, 
like -logit-. You can do the computations, but the results 
just don't mean what you think they mean. Instead you should 
look at -xtlogit- and -xtmelogit-.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------



      

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