  This paper identifies the probability of causation when there is sample
selection. We show that the probability of causation is partially identified
for individuals who are always observed regardless of treatment status and
derive sharp bounds under three increasingly restrictive sets of assumptions.
The first set imposes an exogenous treatment and a monotone sample selection
mechanism. To tighten these bounds, the second set also imposes the monotone
treatment response assumption, while the third set additionally imposes a
stochastic dominance assumption. Finally, we use experimental data from the
Colombian job training program J\'ovenes en Acci\'on to empirically illustrate
our approach's usefulness. We find that, among always-employed women, at least
10.2% and at most 13.4% transitioned to the formal labor market because of the
program. However, our 90%-confidence region does not reject the null hypothesis
that the lower bound is equal to zero.
