Heckman procedures have been widely used in empirical research to correct for selection bias. However, for duration models (survival analysis/time-to-event data), selection correction is still under development. There is an important contribution by Boehmke et al (2006) in American Journal of Political Science, which resulted in the program "DURSEL" for STATA.
Does anyone know any subsequent advance to correct for selection bias in duration models, especially for STATA?
Thanks in advance!
Hi Vera, I guess the answer depends upon what you mean by selection. While static models focus usually on self-selection, dynamic models face the additional problem of dynamic selection. That is, treatment is only observed for the survivors. The statistics/epidemiology literature has made some advances on the problem of dynamic selection. You might be interested in checking out the (shinny new) STATA routine "gformula". I am working on this sort of stuff at the moment trying to relate it to economics. It's tricky business. Good luck.
Hi Vera, I am not aware of the paper by Boehmke et al. (2006), but with single observation per unit data you can control uncorrelated (with X) unobserved heterogeneity(UH), with multiple observation per unit even for correlated UH (see eg Van den Berg, 2001, Handbook). Concerning dynamic selection, you should have a look at the so called "Timing of events" approach by Abbring/Van den Berg (2003). In addition, I do remember having seen something on selection and duration models by Denis Fougère or Jen-Pierre Florens. I haven't found it now on the spot, but it might be worthwile looking at Florens/Fougère/Mouchart (2008) or Fougère/Kamionka (2008). Best Alfred
Hi everyone, I am looking for a way to run in Stata the timing-of-events approach by Abbring and Van der Berg (2003). Do you know if there is a code to do so?
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