Yit is the outcome of interest for individual i and time t. Treati is an indicator which is equal to 1 for treated individuals and 0 otherwise. Postt is an indicator equal to 1 for midline observations and 0 for baseline. Xit is a vector of controls at baseline (t=0), including individual characteristics (education, age, current pregnancy, marital, parental, and orphan status) and household characteristics (sex of household head and household size). β1 is the coefficient of interest that defines the “impact” of the program on individuals in the treatment group. The model also includes dummy variables for the communities where the program was implemented (and where the trainees resided) as well as the program track (business skills or job skills) to which the respondent was assigned. Finally, in order to control for household wealth, we compute an index based on household asset ownership at baseline using multiple component analysis, similar to the method described in Filmer and Pritchett (2001). After constructing the index, which includes thirteen household assets and six indicators of housing conditions, we control for the quintile of household’s overall asset position in all regressions. We augment this basic specification with an individual fixed effects model and find that the results are almost identical. For binary dependent variables, we estimate both linear probability models and probit models analogous to the one given in equation (1), again finding that the results are nearly identical across all outcomes. We cluster the standard errors by classroom in all models, and to account for the interaction effect for variables such as (PosttxTreati) we additionally follow Ai and Norton (2003) to correct the standard error for interaction terms in probit models.

# 3.4. Baseline characteristics

Table 2 presents baseline balance tests for survey respondents from the treatment and control groups.<sup>15</sup> In addition to confirming the success of the randomization, as judged by the very few significant differences between the two groups, the table provides a vivid profile of the average EPAG participant. The study population has an average age of 23 years, with 55% falling between 20 and 24 years. The majority have never been married, while 29% are cohabiting with a partner and only 5% are married. The majority of the study population has started or completed high school, which is consistent with the program’s target group of young women with basic literacy and numeracy, and with the program’s goal not to encourage girls to drop out of school. Thirty-eight percent of the sample was already engaged in at least one income-generating activity (IGA) at baseline. This is consistent with the national figures from the 2007 DHS survey, which found labor force participation rates of 34% for women aged 15-19 and 49% for women ages 20-24. It is also consistent with the Liberian 2010 Labor Force Survey, which found labor force participation rates of 25% for women aged 15-19 and 47% for women aged 20-24.For the purposes of this study, to be consistent with program objectives and the Liberian context, our definition of income-generating activity encompasses the full range of activities through which people earn money, including paid employment, either formal or informal, and self-employment in small business or through petty trade. The most common types of IGAs reported at baseline were petty trade, including

> 15 The balance tests are run on the same sample as will be used in the impact analysis in Section 4, that is, the subset of individuals for whom we have a panel. Balance tests run on the full sample of baseline survey respondents, regardless of whether they also participated in the midline survey, confirm the same findings. A report summarizing the balance tests on the full sample, including comparisons to nationally representative data, is available upon request from the authors.

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