Hi Martin,
thanks for your input. I have actually traced the problem to the (low)
number of individuals for whom the outcome and the variable of
interest switched simultaneously (see my previous mail) in each year.
Simple idiosyncracies, inconsistencies and stuff like that were my
first idea, but the fact that I had the problem with various datasets
in the context of different questions made this somewhat unlikely.
Best,
Nils
On Tue, Jan 5, 2010 at 3:42 PM, Martin Weiss <[email protected]> wrote:
>
> <>
>
> 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
> seconds...
>
>
>
> HTH
> Martin
>
> -----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
> dummies
>
> 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
> sort
> 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,
> Nils
>
>
> On Tue, Jan 5, 2010 at 2:35 PM, Maarten buis <[email protected]>
> wrote:
>> --- 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
>>
>> http://www.maartenbuis.nl
>> --------------------------
>>
>>
>>
>>
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>>
>
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