To the contrary, the differential attrition rates between the control group and the T1 group were slightly smaller for females than for males (Table 4). We found that the life skill training component had had no medium‐term effects on the labor supply and earnings outcomes of youths assigned to the T1 group (not reported in the tables). It may have had some short‐term effects that had faded away during the 23 months between the participants’ completed the life skills training and when they responded to the second endline survey.

# _Labor Market Supply and Earnings_

Table 10 panel A presents ITT and ATT effects on several employment outcome variables for the male, female, and Mombasa sub‐samples, describing labor market participation, labor market earnings, and the quality of jobs. The outcome indicators include measures of whether respondents have been working in the previous seven days, in the past month, whether they worked for pay,<sup>15</sup> whether they worked as a wage worker (for somebody not in their family) or were self‐employed, the average number of hours they worked per week, whether they worked for at least 20 hours per week, whether they had a written contract, whether they received social security benefits, the number of months they have been working (tenure), and finally their monthly earnings from wage employment and self‐employment. The ATT effects were estimated using both “being placed in an internship” and “program graduation” as indicators of compliance in the first stage regression. All of our ITT and ATT estimates are robust, with the ATT estimates being of a larger magnitude as would be expected as they are locally defined on a smaller group.

The ATT and ITT effects of the KYEP program were significant and comparable to those for similar programs in other developing countries (for example, Colombia’s _Jovenes en accion_ and the Dominican Republic’s _Joventud y Empleo)_ . Our ITT estimates show that the full program increased current employment by 6.5 percentage points for all males originally assigned to the program about 14 months after they had completed the program, by 10.8 points for those placed in internships (ATT estimates), and by 14.2 percentage points among males who actually completed the program compared to those in the control group. Given that 69 percent of males in the control group reported in the endline survey having been employed in the previous seven days and 64 percent in the previous month, the ITT estimates were equivalent to a 9.5 percent increase in employment the previous week and a 10.8 percent increase in employment the previous month, while the ATT estimates were equivalent to 15.6 and 17.8 percent increases respectively. Our estimates of wage employment were slightly higher and also significant, translating into an extra three hours worked per week more than the 23 average hours worked per week by the control group. In addition, we found no significant impact on tenure, suggesting that being out of the labor force (in training) for three months did not dramatically change the length of job tenure for male participants compared with control males.

Those effects were mainly driven by the higher probability of wage employment among male program participants rather than self‐employment, which is consistent with the program’s positive effect on the probability of having a written contract. It was also consistent with the program’s design, which aimed to foster wage employment and to encourage employers to retain interns rather than to support small‐scale entrepreneurship. The program designers anticipated that a certain number of youths would want to start new businesses of their own, so they decided to offer 15This variable was equal to one if the respondent reported having worked in the previous seven days and also reported having received a salary from that job.

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