Hi,

For my research I am examining private equity strategies and their subsequent exit-types. My data is Stset in the following way:

Code:
stset E_Date, failure(Successful==1) id(Strategy_Number) enter(time P_Date) origin(time P_Date)

                id:  Strategy_Number
     failure event:  Successful == 1
obs. time interval:  (E_Date[_n-1], E_Date]
 enter on or after:  time P_Date
 exit on or before:  failure
    t for analysis:  (time-origin)
            origin:  time P_Date

------------------------------------------------------------------------------
      1,197  total observations
          0  exclusions
------------------------------------------------------------------------------
      1,197  observations remaining, representing
      1,197  subjects
        251  failures in single-failure-per-subject data
  3,031,231  total analysis time at risk and under observation
                                                at risk from t =         0
                                     earliest observed entry t =         0
                                          last observed exit t =     8,216
For every ID I have one observation moment, event moment, the moment of exit (E_Date). The variables are observed only at one moment and are therefore static.
However, I want to control for fixed effects due to the type of industry, the year of exit, and the country of the firm. How should I proceed with my analysis? I have considered the xtstreg, but this is not applicable to my dataset, as it does not involve panel data, am I correct? When using the
Code:
xi
command for the three fixed effect variables,
Code:
i.CountryFE i.YearFE i.IndustryFE
the accelerated failure time (AFT) models are indicating 'cannot compute an improvement, discontinuous region encountered' and 'hessian is not negative semidefinite'. I hope someone is able to offer me some guidance. Including the three variables as regular variables in the parametric analysis would not be appropriate for my research?

Thanks in advance,

Michael