What is t2-t30, a set of time dummies? That may be the problem, I am not
sure. Have you tried it without t2-t30?
Hope this helps.
A fellow berkeleyan.
Sam
On Mon, 2 Sep 2002, Laura Giuliano wrote:
> Dear Statalisters,
>
> I am trying to estimate a fixed effects (conditional) logit model
> predicting the probability that a newly hired employee in a given
> establishment is white as a function of the hiring manager's race,
> conditional on the number of white hires in the establishment. I have
> many observations (typically over 100) per store and many positive outcomes
> per establishment (also many negative ones). The race of the hiring
> manager changes in many, but not all, establishments. There are about 1500
> establishments.
>
> After the first iteration, I get log likelihood = -8.988e+307, and stata
> stops and prints out an empty table (see output below).
>
> I have had some success running the same regression using smaller
> subsamples -- with fewer observations per store -- from the same data set.
>
> I'd greatly appreciate any explanations and/or suggestions.
>
> Thanks very much!
> - Laura Giuliano
>
> . clogit white mblack mhisp masian mother t2-t30, group(store)
>
> note: multiple positive outcomes within groups encountered.
> note: 114 groups (6827 obs) dropped due to all positive or
> all negative outcomes.
> Iteration 0: log likelihood = -8.988e+307
>
> Conditional (fixed-effects) logistic regression Number of obs = 253398
> LR chi2(33) = .
> Log likelihood = . Prob > chi2 = .
>
> ------------------------------------------------------------------------------
> white | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> mblack | . . . . .
> mhisp | . . . . .
> masian | . . . . .
> mother | . . . . .
> t2 | . . . . .
> t3 | . . . . .
>
> etc.
>
>
>
> ---------------------------------------------------
> Laura Giuliano
> Department of Economics
> 549 Evans Hall, MC 3880
> University of California, Berkeley
> phone: (510) 526-9490
> email: [email protected]
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