group minus the attrition rate of the treatment group) was much lower in Mombasa where there were similar attrition rates among females assigned to the treatment and control groups.

Table 8 reports results from regressions of the probability of dropping out (in other words, not participating in the endline surveys) over indicators of whether the person was randomly assigned to the T1 group (life skills training only) or the T2 group (the full program) and on strata fixed effects in Nairobi and Mombasa separately and in the overall sample. Similar regressions were run that also included baseline characteristics. The results indicated that attrition was selectively related to which group an individual was assigned to in Nairobi (which represented 68 percent of the overall sample), with individuals who were assigned to the control group being significantly more likely to drop out of both endline surveys than those assigned to the treatment groups. However, no significant differences were found in the probability of continuing to be in the endline 2 sample between the treatment and control groups in Mombasa.

Results for Nairobi showed a significant relationship between the probability of continuing in the sample and being assigned to a treatment group, especially for those assigned to the two weeks of life skills training only (the T1 group) who were 0.08 more likely to be interviewed in the endline surveys. Those assigned to participate in the full program (the T2 group) did not differ from the control group in the first endline survey (when controlling for the baseline data) but were 0.07 more likely to continue in the second endline survey than control group members. In contrast, individuals in the T2 group did not differ from those in the control group in the second endline survey but were 0.06 more likely to be interviewed in the first endline in Mombasa survey. These results imply that the labor market outcome variables collected in the second endline survey in Nairobi are biased and should be interpreted with caution as well as the skills and other outcome variables collected in endline 1 in Mombasa. When comparing baseline characteristics between those who dropped out and those who continued (not reported in the paper), it became clear that those who dropped out were more willing to work in the next six months, were more active in searching for jobs, and were more likely to have attended school according to the baseline survey data. This suggests a negative selection in the sample (an upward bias in the estimated impacts). Although the direction of the bias is not known, baseline characteristics suggest it might be negative as those who did not continue in the sample might have refused to participate in the survey because they had found jobs and/or had better options.

Ipsos recorded that those who did not take part in the endline surveys fell into three categories: (i) those who could not be reached as their contact numbers were wrong or their phones were out of service; (ii) those who could not be reached because of sickness or death or because they were out of town and or out of the country; and (iii) those who refused to participate in the surveys. A large portion of attrition from endline 1 and 2 was due to people refusing to participate in the survey and was not random (41 percent and 50 percent respectively for the two endline surveys).<sup>7</sup> Mobility may explain some of the attrition if we assume that those who were not reached (because their numbers were wrong or their phones were off) were out of the country or in a different region/province where their phones did not work.

7Among the 478 who did not participate in endline1, 41 percent refused, 46 percent had a phone that was out of service, and 13 percent could not be reached because of sickness, death, or travel. The main reasons for the attrition from endline2 were refusals (50 percent), wrong contacts (36 percent), and other reasons (14 percent).

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