Dear Statalisters,
I am using discrete-time panel data for carrying out a survival analysis on
the instant likelihood of finding a JOB MATCH; that is, a match between
educational attainment and occupation. I'm afraid, though, that many of the
covariates affecting the instant likelihood of occurrence of this event
might be also affecting the entrance into the risk set. In other word, my
independent variables might not be just explaining the occurrence of that
event, but also the entrance into the population of risk, constituted by all
those who are MISMATCHED.
Put in this way, my research question would be actually the following:
"Conditional on [a number of endogenous variables possibly affecting the
entrance in a population of risk], which is the effect of some of them over
the individual likelihood of leaving this state (job mismatch) and finding a
job match"?.
I suppose this endogeneity problem should be dealt with INSTRUMENTAL
VARIABLES, and the corresponding commands using this approach in STATA (i.e.
ivreg2 or xtivreg2), but finding a suitable, reliable IV is not always easy,
and might just not be available in my data. Were this not feasible, as an
approach, is there any other way of dealing with the endogeneity problem
mentioned that could be easily implemented with STATA?
Many thanks for your attention
Luis Ortiz
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