(d) and (h), we consolidated the three visits into a single estimation, along with the visiting months, as a control. The results suggest that, overall, the probability that a treated student - receiving Treatment A - would be found attending school during a surprise visit was approximately 8 percentage points higher than the probability for control students, whose mean attendance was approximately 54% during the investigation periods. This estimate is comparable to that provided by Miguel and Kremer (2004) in their de-worming study in Kenya; compared to our study, however, it may have been harder for the de-worming program to achieve an estimate of a similar magnitude, as the initial attendance rate was already higher there than in our area of study.

To further assess the estimates, we carried out a cost-effectiveness analysis, following the method used by Dhaliwal et al. (2013) and Evans and Popova (2016) (see Section S.1 in the supplemental appendix for the details). To simplify the analysis, we considered only the cost (prices) of the solar lanterns, ignoring other factors such as research administration costs, reduced kerosene expenditure, and product maintenance opportunity costs. Assuming that the life of a solar lantern is five years, the minimum length of time for which products function effectively in normal conditions, our intervention raised student participation by 0.59―64 years per 100 USD spent. Referring to Evans and Popova (2016) (Table 3 in p. 268), this increase can be compared with that revealed in Evans et al. (2008)’s study, which involved distributing school uniforms in Kenya.<sup>18</sup>

# **Educational efficiency**

Thus far, this study has demonstrated that while providing solar products increased children’s educational inputs (i.e., hours studied, school-attendance record found on a surprise visit), it did not result in an improvement in their educational achievement (subject test scores and overall GPA). Thus, we are left with the third possibility that learning under solar lighting is not as substantially productive and solar lighting alone is not sufficient to improve children’s learning and schooling performance.

To verify this possibility, in column (a) of Table 7, we exploited the study hours and school attendance (estimated in the analysis of Table 5 and Table 6) as regressors to explain the likelihood of children progressing to the next grade after taking the 2014 examination (see Table S.17 to Table S.19 in the supplemental appendix for the corresponding estimation results on GPA scores). The dependent variable is the same as in Table 2, columns (d)―(f). Surprisingly, the educational inputs - home-study hours and attendance record - have no significant association with children’s progression to the next grade. Furthermore, including the treatment dummies in Table 7, column (b) shows virtually no influence on the estimated relationship between the educational inputs and achievement. Given the significant

> 18To check the treatment heterogeneity on educational inputs, in Table S.16 in the supplemental appendix, we also performed similar exercises to those in Table S.5 for the total study hours from September 2013 to April 2014 and indicators of children’s attendance at our school visits in February, April, and August in 2014. Overall, no noticeable heterogeneity was found.

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