not take into account the fact that recipients are, on average, poorer than non-recipients.

The remaining columns of Table 2 estimate CSP program effects with different RD specifications. In the “basic” specification, with school fixed effects and a quartic in the school dropoutrisk score, we estimate that children who were offered scholarships are 24 percentage points more likely to be attending school on the day of the unannounced school visit and 19 percentage points more likely to be enrolled in school, as reported in the household survey.<sup>13</sup> This specification also suggests that recipients spent 5.6 more hours in school in the last week (without conditioning on school enrollment); spent US $10.4 more on schooling; and had completed 0.24 more years of schooling than non-recipients at the time of the survey.<sup>14</sup> It is also possible to include school-specific quartics in the dropout-risk score, rather than a quartic which is restricted to be constant across schools. Those results are reported in the third column of the table. The impact of the CSP program is very similar to that found in the more parsimonious specification. Finally, we run regressions with a sample limited to households whose score places them within 10 ranks of the cut-off, as is often done in RD specifications (Imbens and Lemieux 2008; Lee and Lemieux 2009). This reduces the sample size by approximately two-thirds, but the results from this 13 An important potential concern with these estimates of program effects is any impact that scholarships might have had on _non-recipients_ . If the CSP scholarship program discouraged non-recipients from attending school, perhaps because classrooms became more crowded, the program effects we estimate could be some combination of higher school attendance among recipients and lower school attendance among non-recipients. This would be a violation of the Stable-Unit-Treatment-Value-Assumption (SUTVA)—see Imbens and Wooldridge (2009) for a discussion. We find no evidence that this is the case. Recall that, in “large” schools, the CSP offered 20 more scholarships than in “small” schools. Controlling for a polynomial in school size, “large” schools therefore had a larger influx of CSP recipients than small schools. However, in a regression of the attendance of non-recipient girls on a quartic in school size and an indicator for “large” schools the coefficient on this indicator variable is very small, and nowhere near conventional levels of significance (coefficient : -0.003, with a standard error of 0.022). We also ran a regression of attendance of girls who were turned down for scholarships on the number of CSP recipients, divided by the number of students who attended 7<sup>th</sup> grade in the year before the program. Schools in which this ratio is high are therefore those in which crowded classrooms are most likely to be an issue. The coefficient on the ratio is -0.014 (with a standard error of 0.089). (Both regressions also include a quartic in the dropout score and school fixed effects.) We conclude there is no evidence that children who did not receive scholarships decreased their enrollment in response to the program.

14 This number is consistent with the impact on school enrollment: The estimates of program effects on school enrollment suggest that approximately one out of every five CSP recipients would not have been in school in the absence of the program; with on-time grade progression we would therefore expect that every fifth CSP recipient would have completed one more year of schooling than comparable non-recipients. Table 2 shows that this is approximately the case.

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