Dear Statalisters,

I am trying to analyze an unbalanced panel dataset with appr. 10,000 firm-year observations by running a GEE regression. I am using Stata 17.

My dependent variable "event_count" is a count variable, which seems to be overdispersed (the variance is much larger than the mean value). Hence, I am specifying a negative binomial family distribution and link function.
The independent variable is a binary variable and equals either 0 or 1. As you can see in the code below, my data also contains a set of different control variables. Some of those controls are also binary or categorical.

Code:
xtset turnover_id fiscal_year

xtgee event_count i.award_win i.inside_ceo age i.ind_div_num i.fiscal_year i.dual_ceo ln_pred_tenure i.ceo_dismissal i.male_ceo ln_ceo_so board_size_0101 pct_ind_directors_0101 pre_succ_roa_indadj ln_assets_tot_0101 i.retained_ceo i.successor_tenure event_count_lag2, corr(ar) family(nbinomial 0.2686892) link(nbinomial) vce(robust)
The value of 0.2686892 represents the dispersion parameter "α" that was obtained by running nbreg.

However, after running the command, I receive the error message "estimates diverging (missing predictions) r(430)". I suspect that this might happen due to the large number of categorical variables, but I am not sure about that.

Interestingly, Stata manages to converge to a solution, when I specify a log link function or a possion distribution.

Does someone have an idea if (i) there is a way to converge to a solution with a nbinomial link function and (ii) if it is problematic to combine an nbinomial family distribution with a log link function?
Many thanks in advance!

Best regards,
Bono