groups of socioemotional outcomes. All point estimates are close to zero, with the exception of Neuroticism for the poverty treatment, with a coefficient of 0.186 standard deviations (statistically significant at the 1% level). Nevertheless, the coefficients for the impact on “family indices” for both treatments are close to zero (-0.005 and -0.099 standard deviations for the merit- and poverty-based treatment, respectively), and neither coefficient is statistically significant.

- The broad pattern of the table suggests that the program did not produce effects socioemotional skills, despite the observed impact on school progression and, merit sample, on cognitive outcomes. We cannot rule out competing hypotheses

- such as low marginal exposure to schooling (i.e., the treatment groups increased their attainment by only about four months, on average). We note,

- that this amount of additional schooling was sufficient to produce improved cognitive among the recipients of merit-based scholarships.

- **Labor outcomes**

- Table 6 presents the effects of the program on current labor status (coded as one if the is “currently working”, and zero otherwise); the respondent’s age

- they started working (which captures child labor); whether the recipient participated work-related training that lasted for at least one week (formal or informal, the cognitive demands of the respondent’s main work activity;

- two measures of income: yearly earnings and the daily reservation wage using an inverse hyperbolic sine).

- There is a positive impact on the probability of working for recipients of scholarships (3.4 percentage points, statistically significant, at the

- the point estimate for the poverty arm is lower (1.2 percentage points),

- statistically significant. These effects are from a high baseline level of report to be currently working (the means of both control groups are

# **6.4 Labor outcomes**

Table 6 presents the effects of the program on current labor status (coded as one if the respondent is “currently working”, and zero otherwise); the respondent’s age when they started working (which captures child labor); whether the recipient participated in work-related training that lasted for at least one week (formal or informal, a zero-or-one variable); the cognitive demands of the respondent’s main work activity; and two measures of income: yearly earnings and the daily reservation wage (both transformed using an inverse hyperbolic sine).

There is a positive impact on the probability of working for recipients of the merit-based scholarships (3.4 percentage points, statistically significant, at the 10% level); the point estimate for the poverty arm is lower (1.2 percentage points), and not statistically significant. These effects are from a high baseline level of people who report to be currently working (the means of both control groups are around 92%).<sup>25</sup>

> 25 Of those, approximately 84% report agriculture, fishery, or forestry as their main field of work. Approximately 90% report to engage in agriculture, fishery, or forestry among their overall labor activities. We follow the International Standard Classification of Occupations (ISCO); these

The broad pattern of the table suggests that the program did not produce effects on socioemotional skills, despite the observed impact on school progression and, for the merit sample, on cognitive outcomes. We cannot rule out competing hypotheses such as low marginal exposure to schooling (i.e., the treatment groups increased their educational attainment by only about four months, on average). We note, however, that this amount of additional schooling was sufficient to produce improved cognitive performance among the recipients of merit-based scholarships.

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