had completed primary education but had not completed secondary education. Only 1 percent of the sample did not complete primary school. The majority of those with a tertiary education<sup>10</sup> (either partial or completed) were in the field of information technology and business management (accounting and finance). The sample for the baseline survey had an average of 14 years of schooling, meaning that the program’s targeting could be improved to reach the most vulnerable youths between 16 and 29 years old.

Only about 12 percent of those in the sample were attending school before the program, which validates one of the program’s eligibility conditions (being out of school). Most of those who reported being in school were attending tertiary schools, either a government polytechnic or teacher training school or a private college or university. The main reason that respondents gave for having to withdraw from post‐secondary schools was a lack of financial resources.

Gender disparities were evident at both the lower level and the highest level of education in Nairobi. While little gender disparity was observed among those for whom secondary school was the highest level of education achieved, there was a higher prevalence of females among those who had only achieved a primary education and who had not completed secondary school and a higher prevalence of males among those who had completed tertiary education, reflecting the gender, education and city stratification.

Before the intervention, about 30 percent of the sample reported having participated in a work‐ related or skills training program that lasted at least 30 hours in the previous year, with the most common fields being business management (17 percent of respondents), medical and health services (11 percent), IT (10 percent), and arts or humanities (7 percent). In the majority of cases, this training lasted from between six months and two and more years. The probability of having participated in a training program in the previous year had increased to 50 percent in the endline survey.

The probability of being employed was quite high in the baseline survey, about 0.78 in Nairobi and 0.70 in Mombasa, as was the number of hours worked (about 30 hours a week). The probability of being in wage employment, in other words, working for somebody outside of the family, was about double the probability of self‐employment in both Nairobi and Mombasa. Urban youth unemployment rose by the time of the endline survey **,** with a drop in the current employment probability to 0.67 overall and a drop from six to four average hours worked per day. Similarly, the probability of finding a salaried job in the previous four weeks had decreased by the endline survey. The probability of having a written contract also fell from 0.25 to 0.20, while the probability of having a job with social security and a formal pension was also high (13 months after program completion it was 0.27).

While these statistics suggest that labor market participation and activities declined overall between 2012 and 2014, we interpret these differences as mainly due to noise in the data collection and to the different design of the two surveys.<sup>11</sup> The average employment statistics for youths in the treatment groups were better than those for the control group in the endline survey. Current employment was higher among treatment groups than the control group in the endline data in both

> 10 It has to be noted that some of those attending college-level schools may not have completed secondary school if they were at a youth polytechnic **.**

> 11 There are no representative data on labor force participation by urban youths over the same period to compare with these survey findings.

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