The fact that women face a range of disadvantages in this setting is starkly quantified in our baseline data: respondents are on average 18 years old, yet 60% are in relationships, 28% are married (with a third of marriages being polygamous). While their age at marriage is close to 16, the average age at marriage of their husbands is almost double, at 31. Despite their young ages, nearly half have children. For those in relationships, 46% report being subject to intimate partner violence. These traits of early marriage, childbearing and exposure to violence all have obvious long term consequences on women’s ability to acquire human capital and lead financially independent lives [e.g. Jayachandran 2015].

Our analysis is based on a 2 _×_ 2 factorial design, where one dimension is the quasi-random assignment of the severity of Ebola-related disruption to villages, and the other dimension is the random assignment of villages to ELA treatment or control. We use retrospective data collected from village leaders at the tail end of the crisis to construct an index of village level disruption, proxying the loss in economic opportunity and health service provision that each village experienced. We make precise the four identifying assumptions for the factorial design and provide supportive evidence for each. On the assumption of the quasi-random assignment of disruption, we document how our disruption index is largely uncorrelated to contemporaneous village characteristics, and uncorrelated to past measures of health related behaviors, knowledge and state capacity. This is in line with existing work using spatiotemporal models to simulate the spread of Ebola and measure the local intensity of the shock. This body of work also suggests the geographic incidence of the outbreak is largely uncorrelated to economic, social or political characteristics of locations [Backer and Wallinga 2016, Maffioli 2017, Fluckinger _et al._ 2018].

Our monitoring data confirms there was an extensive roll out of the ELA program despite the circumstances: (i) 70% of clubs opened on time (by September 2014); (ii) the majority of clubs provided life skills training; (iii) vocational skills training took off after travel quarantines were lifted in January 2015. Moreover, there is high demand from women for accessing ELA clubs: 71% of survey respondents in treated villages _ever_ participated in an ELA club meeting or activity (versus 4% in control villages). In terms of trainings received: (i) 82% participated in life skills; (ii) 25% received financial literacy training; (iii) 34% participated in vocational skills training; (iv) 13% received a microfinance loan from BRAC. The overall pattern of participation in activities is in line with what was reported in terms of club openings and training offered.

We conduct our analysis separately for young girls (aged 12-17 at baseline), and older girls (aged 18-25 at baseline) because (i) these cohorts differ in the economic activities they were engaged in at baseline: the majority of the younger cohort are engaged full time in schooling pre-crisis, while the majority of the older cohort are engaged in income generation; (ii) the policy responses to 3