financial constraints that beneficiary households faced in accessing health services. The expansion in health‐seeking behavior was observed in both rural and urban households.

B.2.3 Education Services In contrast with the program impacts on access to health services, CfW participation had no systematic positive impact on access to education (Table 9). Indeed, student absenteeism appears to have risen among treatment households. The average number of school days missed in the four weeks previous to the survey increased by nearly 51 percent (0.2 days). Also, expenditure data show that there were declines of about 27 percent in household spending on girls and boys schooling in urban areas (see Table 6, columns 9‐10). However, at least in the short run, treated households did not report lower school enrollments among children, only lower school attendance rates.<sup>28</sup> At the same time, there was no expansion in children’s labor market participation. One possible explanation for the rise in school absenteeism is that, because of the substantial increase in labor market participation among adult household members, school‐going children may have been skipping school to help with household chores or to take care of younger siblings. While there was no observed increase in the time children spent on household chores, the IE captured a relatively narrow set of data on time use and the distribution of household responsibilities among members.

# **_B.3 Impacts on Savings and Investment_**

Part of the income gains from CfW participation were clearly being used for welfare‐enhancing consumption (food, household supplies, and consumer durables), especially among rural households (see above). However, the longer‐term poverty reduction potential of this instrument is directly linked to the extent to which CfW income is used to enhance the productive potential and overall resilience of targeted households. It is on this dimension that some of the most interesting program impacts emerge, despite the fact that the CfW program’s emphasis was on temporary employment rather than on boosting the productive capacity of poor households.

First, there were positive impacts on savings. Among treated households, participation in informal savings groups ( _osusu_ ) increased by 16 percent (4 percentage points; Table 10, columns 2). However, there were no discernable impacts on the likelihood of having a formal savings account. Furthermore, the result was driven primarily by the impact in rural areas, as there was no statistically significant change observed in urban areas. The total monetary value of reported savings also rose substantially among rural households (by about 25 percent).

Various types of investments were examined, and a pattern emerges of increased investment in homes and businesses among treated households (Table 10, columns 6‐9). Investments by treated households in home improvements rose by 33 percent.<sup>29</sup> There was also a 39 percent expansion in investments in existing businesses in rural areas. These findings validate the argument that PW programs may promote resilience against future shocks.

> 28 Higher absenteeism may signal higher drop‐out rates in the medium term given that the endline survey was conducted in July– August and the new school year starts in September. 29 This is consistent with findings from an unconditional cash transfer program in Kenya where treatment households increased their ownership of metal roofs appreciably (Haushofer and Shapiro 2013).

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