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AW: st: Some problems with clogit convergence when adding year dummies

From   "Martin Weiss" <[email protected]>
To   <[email protected]>
Subject   AW: st: Some problems with clogit convergence when adding year dummies
Date   Tue, 5 Jan 2010 15:42:23 +0100


Are you sure you are familiar with all idiosyncracies of your data? Use
-codebook- and -inspect- to check. Sometimes convergence problems can be
traced back to issues with the data which the two commands make plain within


-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Nils Braakmann
Gesendet: Dienstag, 5. Januar 2010 15:00
An: [email protected]
Betreff: Re: st: Some problems with clogit convergence when adding year

Hi Maarten,

thanks for your input, but I'm not sure that this is the problem. The
year effects are identical for everyone, while my variables of
interest (assume a dummy for the sake of simplicity) switch in
different years for different people. In other words, the model is

y_it = 1{a_i + g_t + tau*d_it + u_it > 0}, where a_i is the individual
fixed effect, g_t is the common time effect and d_it is the variable
of interest. What you have in mind sound to me like a model of the
y_it = 1{a_i* g_t + tau*d_it + u_it > 0}, that is a model with
individual specific time effects which would indeed exhaust all
available information.

What could be the case though is that I end with too few individuals
for whom the dependent variable and the variable of interest change
jointy in each year. In fact, I just tried to use two-year intervals
annd now everything runs fine and looks reasonable (at least at a
first glance).

Thanks again and best wishes,

On Tue, Jan 5, 2010 at 2:35 PM, Maarten buis <[email protected]>
> --- On Tue, 5/1/10, Nils Braakmann wrote:
>> I have a large panel of roughly 50,000 observations over 20
>> years. I model the effects of a time-varying variable on individual
>> employment probabilities using -clogit- with the individuals as
>> groups. The trouble starts when I add year dummies, which leads to
>> severe convergence problems (nonconcave likelihood for several
>> hundred iterations, etc.).
> So you have data on individuals observed for multiple years.
> With a fixed effects model you have taken out all the information
> you might obtain from comparing individuals. This is a good thing
> in the sense that by only comparing individuals with themselves
> you are more likely to compare like with like, but it is also a
> bad thing as you are throwing away information. If your data is
> collected annually, and you added year dummies, then it seems to
> me that the fixed effects in combination with the year dummies
> will have exhausted all the information that is present in your
> data, and that the effect of any additional variables are thus not
identified, and Stata will show that by not converging.
> Hope this helps,
> Maarten
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
> --------------------------
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