metadata: authors: 0: author: Boulhane,Othmane
1: author: Boxho,Claire Elise
2: author: Kanga,Désiré
3: author: Koussoube,Mousson Estelle Jamel
4: author: Rouanet,Lea Marie
count: WESTERN AND CENTRAL AFRICA,Cote d'Ivoire,Western Africa
docna: 0: docna: Empowering Adolescent Girls through Safe
            Spaces and Accompanying Measures in Côte d’Ivoire
docty: Policy Research Working Paper
theme: Health Systems and Policies,Gender,Human Development and Gender,Access to Education,Reproductive and Maternal Health,Education Financing,Health System Strengthening,Education
lndinstr: 0: lndinstr: Investment Project Financing
lndinstr_key: 1353855
abstracts: cdata!: This study uses a cluster-randomized
            controlled trial to investigate the effects of a large-scale
            women and girls empowerment program on sexual and
            reproductive health and empowerment outcomes in
            C&#xf4;te d&#x2019;Ivoire. The study assesses and
            compares the impact of diverse strategies aimed at equipping
            girls with life skills and sexual and reproductive health
            knowledge, provided through well-established safe spaces, in
            isolation or in combination with livelihood support
            interventions, or with initiatives designed to engage boys
            and men and community and religious leaders. The findings
            show that one year after the end of the interventions, safe
            spaces alone have a moderate impact on girls&#x2019;
            empowerment, while safe spaces combined with
            husbands&#x2019; and future husbands&#x2019; clubs
            are the most impactful. Combining safe spaces with
            livelihood support interventions leads to improvements in
            adolescent girls&#x2019; employment outcomes, as
            expected. Finally, the findings show that engaging leaders
            in the context of safe spaces interventions yields mixed
            results on girls&#x2019; empowerment.
display_title: Empowering Adolescent Girls through
            Safe Spaces and Accompanying Measures in Côte d’Ivoire
listing_relative_url: /research/2024/03/34280293/empowering-adolescent-girls-through-safe-spaces-accompanying-measures-côte-d’ivoire
EnvironmentalCategory: C
topicv3: Early Marriage m1326033 2444,Gender and Skills m1327153 912,Adolescent Health m1327263 1450,Gender and Economic Empowerment m1327622 911,Labor Demand m1583073 4422
publishtoextweb_dt: 2024-03-13T00:00:00Z
dois: 10.1596/1813-9450-10721
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 67
author_keys: 0: author_key: 1848426
1: author_key: 1490498
2: author_key: NA
3: author_key: 1442909
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model_extractions: Policy Research Working Paper 10721 Empowering Adolescent Girls through Safe Spaces and Accompanying Measures in Côte d’Ivoire _Othmane Boulhane Claire Boxho Désiré Kanga Estelle Koussoubé Léa Rouanet_ Africa Region Gender Innovation Lab March 2024
Policy Research Working Paper 10721

# **Abstract**

This paper uses a cluster-randomized controlled trial to examine the effects of a large-scale girls’ empowerment program on sexual and reproductive health and empowerment outcomes in Côte d’Ivoire. The analysis evaluates the impacts of safe spaces—where adolescents and young women receive life skills training and sexual and reproductive health education—implemented either alone or in conjunction with accompanying measures, including livelihood support interventions, husbands’ and future husbands’ clubs and engagement of community and religious leaders. One year after interventions ended, safe spaces alone improve knowledge, attitudes, and SRH behavior but not economic outcomes or decision-making. When combined with husbands’ clubs, safe spaces yield substantially greater impacts across multiple domains including economic outcomes and decision-making. The combination of safe spaces, husbands’ clubs, and leaders’ engagement yields the largest impacts. However, combining safe spaces with livelihood support significantly increases pregnancy, and leaders’ engagement yields mixed results. These findings underscore that adolescent-centered interventions are valuable but insufficient for structural empowerment. Systematic engagement of male household gatekeepers and leaders is critical.

This paper is a product of the Gender Innovation Lab, Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at cboxho@worldbank.org, lrouanet@worldbank.org, mkoussoube@worldbank.org, dkanga@imf.org, and oboulhane@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Empowering Adolescent Girls through Safe Spaces and Accompanying Measures in Côte d’Ivoire<sup>∗</sup>

Othmane Boulhane Claire Boxho Désiré Kanga Estelle Koussoubé Léa Rouanet Originally published in the Policy Research Working Paper Series in _March 2024_ . This version is updated in _May 2026_ .

To obtain the originally published version, please email prwp@worldbank.org.

_Keywords_ : Safe spaces; Adolescent girls; Husbands’ clubs; Income-generating activities; Randomized experiment _JEL codes_ : J12, J13, J16

> ∗Boulhane: World Bank, oboulhane@worldbank.org. Boxho: World Bank, cboxho@worldbank.org. Kanga: International Monetary Fund, dkanga@imf.org. Koussoubé: World Bank, mkoussoube@worldbank.org. Rouanet: World Bank, lrouanet@worldbank.org. This paper greatly benefited from comments by Markus Goldstein, Michael O’Sullivan, Margareta Norris Harrit, Christophe Lemière, Kara Adamon, and Bastien Michel. We also want to thank participants at the Africa Gender Innovation Lab seminar, the CSAE conference 2023, the ICDE conference 2023, the NEUDC conference 2023, the PAA conference 2024, the IFPRI Seminar, the Nantes University Economics Departement, and the Paris Nanterre University EconomiX conference for their valuable insights. Special thanks go to Ioana Botea for her significant contribution during the early stages of this project. This research would not have been possible without the support of the World Bank’s Health, Nutrition and Population Global Practice, the SWEDD task team as well as the SWEDD Project Implementation Unit. We are also thankful to the implementing partners and the data collection firms. This paper is a product of the Gender Innovation Lab, within the Office of the Africa Region Chief Economist. We gratefully acknowledge financial support from Global Affairs Canada under the Gender Innovation and Regional Learning (GIRL) initiative, as well as the World Bank’s Umbrella Facility for Gender Equality (UFGE). The UFGE is a multi-donor trust fund administered by the World Bank to advance gender equality and women’s empowerment through experimentation and knowledge creation to help governments and the private sector focus policy and programs on scalable solutions with sustainable outcomes. The UFGE is supported with generous contributions from Australia, Canada, Denmark, Finland, Germany, Iceland, Ireland, Latvia, the Netherlands, Norway, Spain, Sweden, Switzerland, United Kingdom, United States, the Bill and Melinda Gates Foundation, and the Wellspring Philanthropic Fund. The study was preregistered in the 3ie RIDIE registry: `https://ridie.3ieimpact.org/index.php?r=search/detailView&id=653` . The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank Group and the IMF, their Board of Executive Directors, or the governments they represent. All errors and omissions are our own.
# **1 Introduction**

Gender disparities remain acute, with women facing lower levels of human development compared to men across all geographical regions. Lower-middle income countries experience an exacerbation of these gender gaps, where they pose significant challenges for poverty reduction and economic development(World Bank, 2011; Duflo, 2012; Weny et al., 2017).

Adolescence is a pivotal period when critical investments and behaviors around education, marriage, and fertility are shaped. For this reason, stakeholders across low- and middleincome countries, ranging from non-governmental organizations to governmental agencies, increasingly invest in multi-component girls’ empowerment programs. These programs typically combine life skills training, sexual and reproductive health (SRH) education, and sometimes livelihood support delivered through safe spaces, often alongside activities that engage households and communities. Yet, despite their growing popularity, the evidence on what specific components are necessary to improve girls’ empowerment outcomes and overall well-being remains limited. Most programs bundle multiple interventions, making it difficult to disentangle the contribution of each component and to understand whether investing in girls’ skills, with or without providing them with economic opportunities, is enough or whether changes in household and community environments are also required (see Bergstrom and Ozler, 2021; Temin and Heck, 2020; Haberland et al., 2021; Malhotra and Elnakib, 2021; Cohen et al., 2023, for reviews.).

This paper contributes to filling these gaps by evaluating the impact of a large scale adolescent girls’ empowerment program implemented under the Sahel Women’s Empowerment and Demographic Dividend (SWEDD) project in Côte d’Ivoire, a country which ranks among the countries with the highest gender inequality globally, facing challenges such as high fertility rates, early marriage and childbearing, and limited access to quality education, and employment opportunities for women (Institut National de la Statistique and ICF, 2012, 2021; Institut National de la Statistique, 2022; United Nations Development Programme, 2022). We evaluate a set of interventions targeting out-of-school adolescent girls and young women aged 8–24, including: (i) _safe spaces_ or _girls’ clubs_ .<sup>1</sup> providing SRH education and life skills training; (ii) support for income-generating activities (IGA) for eligible girls, i.e., girls of legal working age; (iii) husbands’ and future husbands’ clubs targeting boys and young men to foster more supportive gender attitudes; and (iv) community and religious leaders’ engagement to promote an enabling environment for girls’ empowerment.

We use a randomized controlled trial, covering 280 rural and urban localities, in the northern part of Côte d’Ivoire<sup>2</sup> . The experimental design unbundles the impact of life skills

> 1 Safe spaces or girls’ clubs are multi-component interventions or platforms used to provide girls mostly with a space where they can feel safe to interact with their peers and a trusted mentor, and where they often receive various training contents, including life skills and sexual and reproductive health knowledge, financial education, micro loans or grants, etc. Under such programs, additional services such as access to health services and community-level engagement interventions often complement the components targeted to girls only.

> 2These localities are in the catchment areas of 60 schools, selected by the project implementation team

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training and SRH education provided through safe spaces from the impact of the other accompanying measures. We randomly assign localities to one of four groups: (i) a safe spaces only; (ii) a safe spaces combined with interventions to improve girls’ economic opportunities; (iii) a safe spaces combined with husbands’ and future husbands’ schools; and (iv) a spillover control group. These groups were further cross-randomized with an intervention to engage community and religious leaders, while 56 localities in the catchment areas of schools that did not receive the in-school intervention serve as a pure control group. We collected data from more than 3,000 out-of-school girls and their households at baseline and at first followup, approximately one year after the interventions ended. Following a pre-analysis plan, we analyze a comprehensive set of outcomes, including marriage and pregnancy, SRH behavior, income-generating activity and empowerment outcomes such as gender attitudes and decision-making power. We also investigate the mechanisms that may explain our findings.

One year after the end of the interventions, we find three main results. First, safe spaces alone improve SRH behavior, SRH knowledge, gender attitudes, and mental health, but do not translate into improved economic outcomes, socio-emotional skills, or decision-making. These findings suggest that equipping girls with knowledge and skills alone is insufficient to overcome binding household and community constraints. Second, combining safe spaces with IGA support increases girls’ SRH knowledge, gender attitudes, economic outcomes (0.18 standard deviations, hereafter SD), and socio-emotional skills (0.25 SD), but also leads to a significant increase in pregnancy rates (5.5 percentage points relative to control). This suggests that the intervention did not sufficiently alter the opportunity cost of childbearing, particularly in contexts where girls can engage in flexible income-generating activities such as agriculture, market stands and retail, that are compatible with early motherhood. Third, combining safe spaces with husbands’ clubs yields the broadest empowerment gains: SRH behavior (0.20 SD), income-generating activities (0.29 SD), socio-emotional skills (0.19 SD), and decision-making both on individual matters (0.20 SD) and within households (0.30 SD). Engaging community and religious leaders further enhanced these effects, particularly on girls’ socio-emotional skills and decision-making. In localities where safe spaces were combined with both leaders’ engagement and husbands’ clubs, we observed the most substantial impacts on multiple domains, with some suggestive evidence of a reduction in current pregnancy (36% relative to the control mean, significant at the 10%), though this may reflect timing rather than sustained fertility change as we find no impact on ever-pregnancy.

However, leader engagement also produced some unexpected results: in communities where leaders were engaged, especially those receiving IGA support or implementing husbands’ clubs, impacts on SRH knowledge were not statistically significant, even though safe spaces alone and safe spaces combined with husbands’ clubs (without leaders) significantly improved SRH knowledge. Qualitative research conducted with leaders targeted by the program reveals that these mixed results are likely due to implementation challenges in the to be part of the evaluation of _in-school_ safe spaces for _in-school_ girls. The results of this evaluation are not reported in this paper.

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leaders’ intervention. The program used a cascade training model prone to information loss, and leaders varied widely in literacy levels and familiarity with gender concepts. Many leaders reported difficulty understanding or remembering the nuanced messages about SRH and gender norms, potentially introducing contradictory or diluted messages that undermined the safe spaces curricula. When leaders were paired with husbands’ clubs, the structured engagement with men may have counterbalanced inconsistent leader messaging, but without this reinforcement, leader engagement appears to have created more noise than signal.

Taken together, these findings suggest that building girls’ knowledge and socio-emotional skills is necessary but not sufficient in contexts where restrictive social norms remain binding. Mobilizing male partners through structured, intensive engagement appears critical to help translate changes in aspirations and attitudes into real shifts in agency and behavior. However, our results also highlight the complexity of multi-stakeholder interventions: engaging additional actors can amplify program effects when well-implemented and when messaging is carefully coordinated, but may dilute or distort program messages when implementation quality varies or when the intervention design does not match available resources and capacity.

This paper contributes to three interrelated strands of the literature on adolescent girls’ empowerment in developing countries.

First, our study expands the understanding of the impact of safe space interventions on girls’ empowerment outcomes. Our findings echo some of the findings of Bandiera et al. (2020), who found significant improvement in girls’ economic and social empowerment (e.g., increase in girls’ probability to be engaged in income-generating activity, improvement in girls’ control over their body—such as increased sexual health knowledge and decreased unwanted sex) following the implementation of community-based girls’ safe spaces in Uganda under the Empowerment and Livelihood for Adolescent Girls (ELA) project. A similar ELA program in Sierra Leone was also found to be effective at improving various domains of girls’ empowerment (Bandiera et al., 2019). However, the multifaceted nature of these programs, which bundled life skills, vocational training, and sometimes community engagement, makes it difficult to identify which components drive observed effects. Our findings suggest that the life skills training and SRH education components of safe spaces, while valuable for building knowledge, attitudes, and SRH behavior, are unlikely to explain the employment gains observed in programs like ELA without accompanying economic or household-level interventions.

Second, our research contributes to the growing, but still limited, body of rigorous causal evidence on engaging men, boys, and communities to amplify girls’ empowerment interventions. Because men and boys often hold greater control over household and community resources, many girls’ empowerment programs now include interventions targeting girls’ environment. These interventions are based on the assumption that promoting progressive social norms and attitudes toward early marriage, childbearing, and broader girls’ empowerment in the community will reinforce the impact of interventions directly targeted to girls.

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However, rigorous evaluations of these interventions remain rare, with emerging evidence pointing towards promising results. For instance, Shah et al. (2022) showed that engaging boys and young men as partners can effectively shift gender attitudes and mitigate intimate partner violence. Similarly, Andrew et al. (2022) found that combining girls’ groups with community engagement reduced school dropout and early marriage in India more effectively than girls’ groups alone. Our results corroborate and extend this evidence by demonstrating that interventions targeting male household gatekeepers, i.e. young husbands and future husbands, can enhance multiple dimensions of girls’ empowerment. However, our results also reveal that the design and implementation of community-wide interventions are critical: community leader engagement can either amplify or dilute program effects depending on message fidelity and coordination with other program components.

Lastly, this paper provides valuable insights into the intricate process of scaling up promising interventions. Bergstrom and Ozler (2021) emphasize the importance of understanding implementation details and contextual factors when assessing the effectiveness of empowerment programs. Interventions that work in controlled pilot settings may lose fidelity when scaled through government systems or across diverse communities. For instance, while ELA programs in Uganda and Sierra Leone showed positive impacts, an evaluation in Tanzania found no significant effects on girls’ empowerment outcomes, likely due to low implementation quality (Buehren et al., 2024). Multi-component programs face particular scaling risks: coordination across partners, message consistency across intervention arms, and adaptation to local contexts all introduce potential sources of variation in program quality. Our mixed findings regarding leader engagement illustrate these challenges concretely. Qualitative research reveals that the intervention design aimed for leaders to act as change agents publicly promoting new norms, but implemented this through broad recruitment, cascade training, and minimal support-an approach better suited to simple information dissemination than to transformative norm change. The resulting heterogeneity in leader capacity and message fidelity helps explain why leaders enhanced some outcomes but not others, and why their effects depended critically on the presence of complementary interventions like husbands’ clubs that provided clearer, more consistent messaging. This underscores that community engagement requires not just good intentions but careful attention to training quality, message consistency, realistic assessment of leader capacity, and sufficient ongoing support—particularly when addressing sensitive topics like SRH and gender norms where miscommunication can undermine program goals.

The remainder of this paper is organized as follows: section 2 presents the context and the interventions. Section 3 presents the research design and section 4 presents the empirical results. Section 5 discusses the results and concludes.

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# **2 Context and Interventions**

## **2.1 Background**

The SWEDD is a regional project launched in 2013 and aiming to accelerate the demographic transition by addressing both supply- and demand-side constraints to family planning and sexual and reproductive health. The project is currently implemented in twelve countries (Benin, Burkina Faso, Cameroon, Chad, Côte d’Ivoire, The Gambia, Guinea, Mali, Mauritania, Niger, Senegal and Togo). The SWEDD is structured into three main components: (i) Generating demand for reproductive, maternal, neonatal, child health, and nutrition products and services; (ii) Improving the supply of these products and qualified personnel; and (iii) Strengthening national capacity and policy dialogue. This study focuses on interventions implemented under the first component in Côte d’Ivoire.

Grounded in both theoretical and empirical evidence, the SWEDD project in Côte d’Ivoire implemented a set of activities targeting adolescent girls and young women aged 8 to 24, who are vulnerable to early marriage, teenage pregnancy, and early school dropout, as well as their communities through the following interventions: (i) Empowering girls through life skills and sexual and reproductive health (SRH) education delivered via safe spaces; (ii) Income-generating activities (IGA) support consisting of providing grants and entrepreneurship training to enhance girls’ economic empowerment; (iii) Offering life skills and SRH education to boys in their communities via husbands and future husbands’ clubs; and (iv) Engaging religious and village leaders to promote girls’ empowerment.

These interventions were designed to address both individual and systemic barriers to girls’ empowerment. While the first two interventions address individual barriers, the latter two interventions aim to change restrictive social norms and create an enabling environment for girls’ empowerment. Below, we describe in detail the four interventions evaluated in this study.

## **2.2 Interventions**

### **2.2.1 Safe Spaces**

As part of the safe spaces intervention, out-of-school girls aged 8 to 24 met under the leadership of a trusted female mentor in a safe space where they received various contents. The curriculum included topics related to life skills (self-awareness, self-esteem, stress management, peer pressure, decision-making and leadership), sexual and reproductive health (contraceptives, human immunodeficiency virus or HIV, sexually transmitted diseases or STDs, menstrual hygiene), gender norms, gender stereotype, nutrition, gender-based violence, and women and children’s rights. The content of the curriculum was adapted to two distinct age groups, younger girls aged 9–12 years, and girls 13 and above. The safe space sessions lasted approximately 2 hours and occurred twice a week for 6 months in a given locality. The implementation of safe spaces across eligible localities spanned over a total of 12 months instead 5
of 18 months because of the COVID-19 restrictions in 2020. Eligible girls participated in the identification of venues for community-based safe spaces, allowing them to ensure a level of security, confidentiality, and privacy. In the regions where the evaluation took place, the mentors in charge of facilitating the sessions were women living in the community, selected and trained for 21 days by the implementing NGO, the International Rescue Committee (IRC). All selected mentors were validated by the beneficiaries to ensure that they identify the woman as a role model and to promote a trusting relationship. To the extent possible, the mentors respected the following two criteria: being between 25 and 45 years old and having completed 9th grade. However, since it was challenging to identify women who met the minimum education requirement and were willing to undertake a volunteer job (stipends provided but no salary), the NGO had to select a few mentors who were not literate. This most likely caused quality issues in the delivery of the curriculum in a few safe spaces.

# **2.2.2 Support for Income-Generating Activities (IGA) Intervention**

The goal of the IGA intervention is to strengthen vocational and income-generating capacities to contribute to the socio-economic empowerment of girls. The intervention targeted beneficiaries of safe spaces who were 16 years old or older at the time of the start of the intervention (i.e., 15 years old or older at baseline). It comprised three different components: (i) an entrepreneurship training of 13 hours running over 3 days; (ii) a one-on-one coaching service that gave personalized advice on the creation of a business; and (iii) a lump-sum cash grant provided to individual girls or groups of girls on the basis of a business plan. The curriculum of the entrepreneurship training was composed of a financial and business skills section (entry cost, business plan, management, costs registry) as well as a socio-emotional skills section (self-esteem, listening and empathy, stress management, and problem solving). According to the program monitoring data, given grants ranged from 25,000 to 1,500,000 CFA francs, with an average amount per girl of 55,900 CFA francs (228 USD purchasing power parity 2019).<sup>3</sup> The high variation in the size of the grant is due to the varying number of business associates (i.e., beneficiaries who associate to work on a business plan) and to the predicted volume of sales of the IGA. The majority of the created IGA were small-scale activities in the food processing sector or in the food and nonfood retail sectors. The IGA intervention, also implemented by the IRC, was delayed due to institutional constraints and the COVID-19 pandemic, which reduced the duration from 12 months initially planned to only 6 months.

# **2.2.3 Husbands’ and Future Husbands’ Clubs**

In addition to safe spaces, husbands’ and future husbands’ clubs, sometimes referred to as husbands’ clubs for fluidity, were implemented to involve men and boys as partners in family health and family planning. The clubs aimed to engage men in discussions on gender

> 3Conversion factor = 245.51. Source: https://data.worldbank.org/indicator/PA.NUS.PPP?locations=CI.

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and sexual and reproductive health, and to promote shifts in gender norms and attitudes, with anticipated spillover effects on other men within the community. Clubs were targeted at out-of-school boys and young men of 12–25 years old with a priority given to the men in the close circle of the target adolescent girls, such as husbands, boyfriends, brothers or other family members. These clubs, implemented by the IRC, were holding sessions once a week during approximately 6 months, from August 2019 to February 2020, on topics related to sexual, maternal, neonatal and child health, decision power in the household, genderbased violence (including early marriage and female genital mutilation), communication skills, parenting skills, and anger management. To select the mentors of the clubs, local NGOs recommended men, and consultations followed with community members and leaders. Mentors then participated in a 5-day training on the curriculum before being deployed in the clubs.

# **2.2.4 Community and Religious Leaders Intervention**

Additionally, in half of the villages that hosted safe spaces, an intervention was introduced to engage community and religious leaders, along with other influential figures, in discussions on gender and family planning. These leaders received training on topics such as girls’ empowerment -including education and health-, gender roles, gender-based violence, birth spacing, and the negative consequences of early pregnancy and child marriage.

These influential figures disseminated messages through various channels: religious leaders conducted sermons during regular services, village chiefs addressed the community through community-wide conversations, and female presidents of women’s associations conducted educational talks with parents. This intervention aimed to sensitize not only the leaders but also the entire community, creating an enabling environment to counter restrictive gender norms.

The intervention was deployed over a 6-month period, with approximately one session per month for each type of activity (sermons, community conversations, and educational talks). The local NGO ARSIP (Alliance des Religieux pour la Santé Intégrale et la Promotion de la personne humaine) trained the leaders using a cascade method, where national trainers were first trained and then trained local leaders in the communities. This training method was chosen to efficiently reach a large number of leaders across diverse areas. We refer to this intervention as the _Leaders_ intervention throughout the paper.

In the appendix, figure 2 reports the timing of each of these interventions, with regards to the timing of the baseline and follow-up data collection. Further implementation details for each intervention are reported in figure 3.

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# **3 Research Design and Data**

## **3.1 Research Design**

In partnership with the government, we conducted a cluster randomized controlled trial to test different approaches to girls’ empowerment in northern Côte d’Ivoire. While the full research design allows to study both the effects of school-based interventions targeting girls in schools, and the effects of community-based interventions, this paper focuses specifically on the effects of the community-based interventions targeted to out-of-school girls.

The school-based component was included in the original design but faced significant implementation challenges, including reduced intervention duration and scheduling conflicts between school administration and the implementing NGO. These challenges resulted in low participation rates and no significant impacts on key outcomes. Complete details and analysis of the school-based intervention are available upon request.

### **3.1.1 Study Setting and Sample Selection**

The study was implemented in 280 localities in the catchment area of 60 middle schools (or _collèges_ ) eligible for the program in the regions of Poro, Tchologo, Bagoué, Folon, and Kabadougou. In collaboration with the Ministry of Education and the Program Implementation Unit, 60 eligible schools were selected from a total of 83 across the five program regions. These schools were chosen based on having the largest populations of girls at the time, in order to meet the project’ s target number of beneficiaries. We then selected 280 localities (villages or neighborhoods of urban localities) in the catchment areas of these schools.<sup>4</sup>

### **3.1.2 Randomization Strategy**

We used a two-stage randomization process. First, we randomized the 60 secondary schools into three groups of equal size: a control group, a group to receive in-school safe spaces, and a group to receive in-school safe spaces and support classes in mathematics and French.<sup>5</sup> The randomization was stratified by the number of localities around the schools and the number of girls eligible to attend the selected schools.

In the second stage, we randomize the 280 localities selected around the schools into treatment and control groups. The 56 localities around the 20 control group schools (figure 1) were automatically considered as a pure control, i.e., with no intervention taking place either in selected schools or in the localities. The remaining 224 localities around treatment schools were randomly assigned to four groups: a group of 56 localities receiving community

> 4Using data from the 2014 General Population Census (Recensement Général de la Population et de l’Habitat), we first selected localities with an estimate of at least 50 eligible girls, i.e., out-of-school girls aged 8 to 24. We then restricted to localities that were close enough to secondary schools that girls residing in these localities could reasonably commute to one of the 60 schools.

> 5Due to delays and other implementation issues, the support classes were not implemented. Both treatment arms were therefore merged into one group of 40 schools receiving in-school safe spaces.

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<!-- Start of picture text --> Northern<br>Céte d'Ivoire<br>|___5regions|<br>School safe spaces Control schools<br>Safe spaces Safe spaces + IGA Husbands’Safe spacesclubs + Control Pure control<br>v<br>14<br>(spillover group)<br>v v Vv Vv v v<br>T1 T1 + Leaders T2 T2 + Leaders T3 T3 + Leaders<br><!-- End of picture text -->
## **3.1.3 Participant Selection**

Toward the end of 2017, in collaboration with the Project Implementation Unit, we conducted a census of 45,883 households across the 280 localities to identify eligible girls. Girls were considered eligible for community safe spaces if they were 8–24 years old and had never been to school or did not go to school during the academic year 2017/2018. Priority was given to orphans, single mothers, pregnant girls and girls considered most vulnerable to early marriage and early pregnancies based on a household vulnerability index.<sup>7</sup> From the eligible population, we sampled a fourth of the total eligible girls who were aged 12–24 to be part of the impact evaluation sample.

# **3.2 Data**

We use two rounds of data collection: first, a baseline survey conducted before the implementation of the interventions between December 2017 and January 2018; and second, a follow-up survey conducted approximately one year after the end of the interventions, between January and March 2021. The follow-up survey was done in-person despite the disruption caused by the COVID-19 pandemic, and followed national health guidelines. Two main questionnaires were used: the household questionnaire and the adolescent girl questionnaire. The household questionnaire, completed by the household’s head or their representative, collected data on the household’s living conditions (e.g., nutrition, assets, and shocks) as well as demographics from every household member (e.g., education, marriage, and pregnancy).

The adolescent girl questionnaire collected information on various domains, including marriage and fertility behaviors, aspirations, socio-emotional skills (collected only at followup), mental health (collected only at follow-up), gender attitudes, gender-based violence (collected only at follow-up), decision-making in the household, income-generating activities, and access to finance. Gender-based violence (experience of emotional, physical, and sexual violence) is measured using questions adapted from the DHS survey. Girls’ mental health is measured using the GHQ-12 (General Health Questionnaire, 12 items), a tool used to detect common mental disorders.<sup>8</sup> The measures of socio-emotional skills used were developed as part of the Effective Socio-emotional Skills to Gain Economic Empowerment (ESTEEM) initiative at the Africa Gender Innovation Lab.<sup>9</sup> At baseline, the total sample size was 3,792 adolescent girls and their respective households. At follow-up, despite an intensive tracking exercise, only a total of 3,007 adolescents girls were successfully interviewed along with 3,680 of their baseline households. This resulted in an average attrition rate of 20% of the total baseline sample of adolescent girls. Tests for differential attrition are presented in table A1 in the appendix. The attrition rate in

> 7In households with more than one eligible girl, only one beneficiary was selected by lottery, unless the number of eligible girls was less than ten in the locality.

> 8Statements used to construct the gender equality, violence, socio-emotional skills and mental health indices are listed in tables A5 and A6 in the appendix.

> 9For more details, see Marsh et al. (2025).

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the control group is 24%, which is significantly higher than in the T1 + Leaders group (safe spaces only with Leaders’ engagement), the T2 + Leaders group (safe spaces with support to IGA, with Leaders’ engagement), and the T3 group (safe spaces with husbands’ clubs), for which the attrition rates are 16%, 15% and 15%, respectively. To examine the robustness of our results to attrition, we use two different bounding approaches, and we also use the inverse probability weighting (IPW) approach to adjust our estimates—results are shown in tables A29 to A35 in the appendix.

# **3.3 Summary Statistics**

## **3.3.1 Baseline Characteristics**

Table 1 presents descriptive statistics and balance tests of key socio-demographic characteristics of adolescent girls and main outcome variables at baseline. Looking at the control group averages, girls’ average age is 19 years old, 62% have ever been married, and 63% have ever been pregnant. Consistent with a sample of out-of-school girls, the schooling level is low, with only 23% of girls having attended school. While 66% of control group girls are engaged in an income-generating activity (IGA), only 18% receive an income from an IGA. Across experimental groups, 58% to 77% of girls already knew about one modern contraceptive at baseline, and 63% to 76% had heard of HIV.

Table 2 presents descriptive statistics and balance tests of key socio-demographic indicators and main outcome variables at the household level. Across treatment groups, 44% to 77% of households live in rural areas. In the control group, around 90% of households are headed by men, and there are approximately 8 individuals per household. Around one-third of household heads are in polygamous unions, and more than two-thirds of them do not have secondary education.

The tables also present the F-test for joint significance of differences between treatment arms. There are some significant imbalances in the likelihood that the adolescent girl has been involved in an IGA at baseline, and in the likelihood that she knows any contraceptive (table 1). At the household level (table 2), there is also an imbalance in the proportion of rural households across treatment groups, with a larger proportion in T2 and T3 + Leaders groups. The estimation strategy outlined in section 3.4 accounts for these imbalances by controlling for the baseline value of these variables.

## **3.3.2 Compliance**

Appendix Table A2 reports the self-reported participation rates of girls in safe spaces, measured at follow-up. Participation in the program was high, with 47% to 65% of girls in treatment localities reporting attending at least one session. This suggests strong demand for the program.<sup>10</sup>

> 10A similar program in Uganda had a substantially lower participation rate of 21% (Bandiera et al., 2020).

11
We also find very limited contamination of the control group—only 2% of the girls reported attending at least one safe space session. In addition, Appendix Table A3 presents the main correlates of program participation. Girls living in rural localities are 8.6 percentage points more likely to participate into the program, while having a polygamous household head is associated with a 3.3 percentage point lower participation rate.

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Table 1: Adolescent girls’ characteristics at baseline

||Control|T1|T1 + Leaders|T2|T2 + Leaders|T3|T3 + Leaders|T4|F-test|
|---|---|---|---|---|---|---|---|---|---|
|Adolescent’s age|18.98|18.81|19.07|19.20|18.73|18.85|18.46|18.93|0.94|
||[0.15]|[0.27]|[0.18]|[0.18]|[0.21]|[0.21]|[0.26]|[0.13]||
|Above 18 years old|0.67|0.67|0.71|0.72|0.66|0.65|0.62|0.66|1.48|
||[0.02]|[0.03]|[0.02]|[0.02]|[0.03]|[0.02]|[0.03]|[0.02]||
|Above 15 years old|0.87|0.84|0.88|0.89|0.84|0.86|0.83|0.86|1.25|
||[0.01]|[0.03]|[0.02]|[0.02]|[0.02]|[0.02]|[0.01]|[0.01]||
|Level of education [0–4]|0.34|0.27|0.32|0.38|0.32|0.36|0.28|0.34|0.27|
||[0.04]|[0.08]|[0.08]|[0.12]|[0.07]|[0.07]|[0.06]|[0.06]||
|Ever schooled|0.23|0.16|0.22|0.23|0.20|0.24|0.20|0.22|0.74|
||[0.02]|[0.03]|[0.03]|[0.06]|[0.03]|[0.04]|[0.04]|[0.03]||
|Ever pregnant<br>13|0.63|0.65|0.62|0.67|0.60|0.62|0.58|0.61|0.83|
||[0.02]|[0.03]|[0.03]|[0.03]|[0.03]|[0.02]|[0.04]|[0.02]||
|Ever married or cohabited|0.62|0.57|0.59|0.63|0.62|0.57|0.54|0.57|1.02|
||[0.02]|[0.04]|[0.04]|[0.04]|[0.03]|[0.03]|[0.05]|[0.04]||
|Engaged in IGA|0.66|0.67|0.65|0.71|0.77|0.77|0.81|0.68|2.37<sup>_∗∗_</sup>|
||[0.03]|[0.04]|[0.05]|[0.05]|[0.06]|[0.05]|[0.04]|[0.04]||
|Remunerated IGA|0.18|0.15|0.14|0.22|0.20|0.18|0.17|0.18|0.49|
||[0.02]|[0.03]|[0.03]|[0.03]|[0.04]|[0.04]|[0.03]|[0.03]||
|Reported profts|0.30|0.28|0.28|0.33|0.38|0.36|0.38|0.31|0.97|
||[0.02]|[0.06]|[0.05]|[0.05]|[0.05]|[0.05]|[0.06]|[0.03]||
|Monthly profts (FCFA)|5514.19|5130.08|4961.36|5634.14|7614.85|6646.75|6140.00|5556.68|1.01|
||[569.51]|[1106.44]|[826.86]|[870.78]|[1142.35]|[1053.19]|[840.23]|[538.89]||
||Control|T1|T1+Leaders|T2|T2+Leaders|T3|T3+Leaders|T4|F-test|
Table 1 continued

|Knows one modern contraception|0.74|0.65|0.77|0.68|0.59|0.63|0.58|0.64|2.31<sup>_∗∗_</sup>|
|---|---|---|---|---|---|---|---|---|---|
||[0.03]|[0.04]|[0.03]|[0.07]|[0.07]|[0.05]|[0.07]|[0.05]||
|Heard of HIV|0.76|0.68|0.75|0.68|0.63|0.65|0.63|0.69|1.37|
||[0.04]|[0.04]|[0.04]|[0.06]|[0.06]|[0.05]|[0.07]|[0.04]||
|Decision-making index|14.27|14.30|15.49|14.11|13.71|13.61|13.46|14.49|0.99|
||[0.54]|[0.67]|[0.57]|[0.91]|[0.53]|[0.60]|[1.04]|[0.51]||
|Domestic violence attitude index|0.72|0.63|0.60|0.67|0.62|0.65|0.68|0.65|1.46|
||[0.03]|[0.03]|[0.04]|[0.05]|[0.06]|[0.06]|[0.06]|[0.03]||
|Self-esteem index|32.27|31.51|32.34|32.09|31.40|32.33|31.80|31.98|1.51|
||[0.29]|[0.25]|[0.28]|[0.28]|[0.29]|[0.51]|[0.44]|[0.26]||
|Gender equality index|1.12|0.79|0.87|0.86|0.97|0.83|0.87|0.90|1.13|
|14|[0.08]|[0.09]|[0.09]|[0.11]|[0.14]|[0.12]|[0.14]|[0.08]||
|N|967|364|279|362|306|399|299|816||

_Note_ : Standard deviations in brackets.<sup>_∗_</sup> _p <_ 0 _._ 10,<sup>_∗∗_</sup> _p <_ 0 _._ 05,<sup>_∗∗∗_</sup> _p <_ 0 _._ 01 This table presents the balance test for key adolescent variables at baseline. The F-test is the joint significance of mean differences across treatment arms. Level of education [0–4] goes from no education (0) to finishing high school (4). IGA indicates income-generating activities, and HIV stands for human immunodeficiency virus.
Table 2: Household-level characteristics at baseline

||Control|T1|T1 + Leaders|T2|T2 + Leaders|T3|T3 + Leaders|T4|F-test|
|---|---|---|---|---|---|---|---|---|---|
|Rural|0.48|0.67|0.44|0.68|0.60|0.54|0.77|0.46|2.12<sup>_∗∗_</sup>|
||[0.09]|[0.12]|[0.11]|[0.12]|[0.11]|[0.14]|[0.10]|[0.09]||
|Household size|8.12|7.55|7.88|8.07|7.69|8.15|8.59|7.71|1.24|
||[0.27]|[0.29]|[0.41]|[0.35]|[0.43]|[0.46]|[0.35]|[0.23]||
|Asset Index [0–8]|4.22|4.04|4.05|4.11|4.16|4.19|4.35|4.16|0.68|
||[0.07]|[0.10]|[0.16]|[0.10]|[0.11]|[0.12]|[0.15]|[0.06]||
|Head is female|0.10|0.17|0.17|0.08|0.09|0.09|0.10|0.10|1.66|
||[0.01]|[0.03]|[0.04]|[0.02]|[0.02]|[0.02]|[0.03]|[0.02]||
|Head is polygamous|0.35|0.36|0.41|0.33|0.41|0.34|0.38|0.35|0.53|
||[0.03]|[0.03]|[0.04]|[0.04]|[0.04]|[0.04]|[0.03]|[0.02]||
|Head has no education<br>15|0.74|0.80|0.74|0.74|0.74|0.72|0.75|0.71|0.65|
||[0.02]|[0.05]|[0.04]|[0.04]|[0.03]|[0.03]|[0.05]|[0.03]||
|At least one member in agri labor|0.70|0.77|0.76|0.82|0.76|0.68|0.83|0.74|1.61|
||[0.07]|[0.08]|[0.07]|[0.06]|[0.08]|[0.09]|[0.06]|[0.05]||
|At least one member in non-agri labor|0.68|0.56|0.61|0.50|0.62|0.63|0.58|0.68|1.47|
||[0.05]|[0.08]|[0.06]|[0.07]|[0.06]|[0.07]|[0.06]|[0.04]||
|N|967|364|279|362|306|399|299|816||

_Note_ : Standard deviations in brackets.<sup>_∗_</sup> _p <_ 0 _._ 10,<sup>_∗∗_</sup> _p <_ 0 _._ 05,<sup>_∗∗∗_</sup> _p <_ 0 _._ 01.

This table presents the balance test for key household variables at baseline. The F-test is the joint significance of mean differences across treatment arms.
# **3.4 Empirical Strategy**

To assess the impacts of the safe spaces and accompanying interventions, we estimate intention-to-treat (ITT) effects, considering the original assignment of adolescent girls to offered interventions, regardless of whether they participated or not. We use an ANCOVA specification for our main analysis whenever the baseline value of the outcome variable is available. Our estimated model is as follows: where _Yijt_ is the outcome for individual i in the locality _j_ at time t, with t = 0 being the baseline and t = 1 being the follow-up. T1 _ij_ , T1Leaders _ij_ , T2 _ij_ , T2Leaders _ij_ , T3 _ij_ , T3Leaders _ij_ , and T4 _ij_ are binary indicators of the assignment status for each individual, following indicator descriptions in section 3.1. _Xij_ 0 is a vector of control variables measured at baseline, including unbalanced variables between the control and the treatment groups, as well as age and the education of the adolescent girl. We also include randomization strata fixed effects ( _S_ ) and the standard errors _εij_ are clustered at the locality level.

To address multiple hypothesis testing concerns and maximize statistical power, we combined multiple variables from the same domains into thirteen indices, following Anderson (2008). These indices, described in table A4, are grouped into three categories: (i) primary outcomes—SRH behavior, economic outcomes, which are the main outcomes targeted by the program at short term; (ii) mechanisms outcomes—SRH knowledge and attitudes, gender attitudes, aspirations, socio-emotional skills (SES), which capture changes expected to mediate effects on primary outcomes; and (iii) secondary outcomes—marriage and pregnancy, violence, decision-making on individual matters, decision-making within the couple, finance, nutrition, and mental health, which are broader girls empowerment and well-being outcomes potentially affected by the interventions and, for some, may require more time to adjust.<sup>11</sup> Each index is weighted following a generalized least squares (GLS) weighting procedure that accounts for the correlation between items included in the index. Each index is also normalized according to the control group mean and standard deviation. Where necessary, we reverse the sign of individual items so that higher scores consistently indicate better outcomes. We also report false discovery rate (FDR)-adjusted q-values for these indices in Appendix Tables A17, A18 and A19.

We conduct two sets of robustness checks. First, we use a double LASSO procedure following Belloni et al. (2014) to select control variables in a data-driven way, reducing the

> 11This study follows to the extent possible the pre-analysis plan for the multi-country randomized controlled trial or RCT evaluating the impacts of safe spaces across five countries in the Sahel, with necessary adaptations due to the specificity of the sample in Côte d’Ivoire (e.g., older adolescents than in other countries of the regional study). The pre-analysis plan is available on the 3ie RIDIE registry page : `https://ridie.3ieimpact.org/index.php?r=search/detailView&id=981.`

16
risk of overfitting and omitted variable bias (see tables A20 to A22 in the Appendix). Second, we test the robustness of our results to potential differential attrition across treatment arms (see table A23 to A35 ). To do so, we implement several complementary approaches. We first apply trimming procedures equivalent to Lee bounds, which estimate upper and lower bounds of the treatment effects by removing observations from the tails of the outcome distribution in groups with higher attrition. We then use imputation methods that replace missing outcomes among attritors with values drawn from different percentiles of the observed distribution. Finally, we estimate treatment effects using Inverse Probability Weighting (IPW), which accounts for differences in the probability of remaining in the sample.

Beyond average treatment effects, we explore whether impacts vary by participants’ characteristics. In particular, we examine heterogeneous effects based on baseline marital status using the following specification: where M _i_ is a dummy variable indicating if the individual i has ever been married at the baseline. While we pre-specified both marital status and age as dimensions for heterogeneity analysis in our pre-analysis plan, we focus only on marital status in this paper due to sample composition. Only 13% of respondents were under age 15 at baseline, limiting our ability to detect age-based heterogeneity with sufficient statistical power.

Examining heterogeneity by marital status is particularly relevant for policy and program design. Unmarried girls might be more receptive to interventions as their decisions may be less influenced by partners or prior life choices. Conversely, married girls may face different constraints and have distinct needs that could affect program impact. Understanding these differences can inform more effective targeting and adaptation of similar interventions in the future.

# **4 Results**

This section presents results organized by type of outcome (primary, mechanism, and secondary) and analysis (main vs heterogeneity) and by type of intervention. All results reported below are robust to multiple hypothesis testing using false discovery rate (FDR) adjustments – (Appendix Tables A17 A19), to alternative control variable selection using double LASSO (Appendix Tables A20–A22), and to differential attrition using inverse probability weighting, trimming, and imputation approaches (Appendix TablesA23–A35). Effects significant at the 10% level occasionally lose significance after FDR adjustment. Our core findings remain the 17
same across all robustness checks.

# **4.1 Impacts on Primary Outcomes**

Table 3 reports treatment effects on our primary outcomes: SRH behavior (for girls aged 15+) and economic outcomes. Results for the underlying individual outcomes are shown in Tables A7 and A8. We present results by treatment arm to highlight how each program component contributes to girls’ empowerment outcomes.

**Safe spaces alone (T1).** One year after the interventions ended, safe spaces alone significantly improved SRH behavior by 0.20 SD (p<0.01), driven primarily by reductions in high-risk sexual behaviors. Specifically, safe spaces alone reduced transactional sex by 2.6 percentage points (p<0.05), an 87% decline relative to the 3% control mean (Table A7). However, T1 had no impact on economic outcomes, suggesting that building girls’ knowledge and skills alone is insufficient to overcome structural constraints on economic participation.

**Safe spaces with IGA support (T2).** Combining safe spaces with entrepreneurship training and cash grants substantially improved economic outcomes by 0.18 SD (p<0.05). These effects operated primarily through profitability: girls in T2 were 11 percentage points more likely to report profits (p<0.05) and earned higher profits on average (Table A8). However, T2 did not improve SRH behavior, and the effect was marginally significantly smaller than T1 (p=0.097). While this suggests that IGA support did not reinforce safe spaces’ impact on SRH outcomes, the mechanisms underlying this pattern remain unclear.

**Safe spaces with husbands’ clubs (T3).** Combining safe spaces with husbands’ clubs yielded significant improvements in both primary outcomes. SRH behavior improved by 0.20 SD (p<0.05), including a 6.4 percentage point increase in contraceptive use (p<0.10), representing a 41% rise relative to control. T3 also improved economic outcomes by 0.29 SD (p<0.01), driven by increased engagement in any income-generating activity (13.9 percentage points, p<0.01) and a shift toward non-agricultural activities (15.1 percentage points, p<0.01). Statistical tests showed no significant difference between T2 and T3 effects on economic outcomes (p=0.255), suggesting that engaging male household gatekeepers can be as effective as providing direct livelihood support to improve girls’ economic participation.

**Leader engagement added to each intervention.** Adding religious and community leaders to safe spaces alone (T1+Leaders) eliminated the positive effect on SRH behavior and did not generate any economic gains. When leaders are added to T2 (T2+Leaders), the economic impact was maintained and slightly strengthened (0.24 SD, p<0.01), but SRH behavior still showed no impact. In contrast, combining leaders with both safe spaces and husbands’ clubs (T3+Leaders) sustained significant effects on both SRH behavior (0.14 SD, p<0.05) and economic outcomes (0.27 SD, p<0.05). Overall, leaders’ engagement seems to reinforce program impacts only when combined with complementary community engagement through husbands’ clubs. When introduced without this structured engagement of male household gatekeepers, leader involvement diluted the effects observed in other treatments.

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Table 3: Impact on primary outcomes

|||(1)<br>SRH<br>behavior<br>(15yo+)|(2)<br>Economic<br>outcomes|
|---|---|---|---|
|T1|(safe spaces)|0.202***|0.051|
|||(0.076)|(0.092)|
|T1|+ Leaders|0.132|0.022|
|||(0.093)|(0.113)|
|T2|(safe spaces + IGA)|0.049|0.179**|
|||(0.084)|(0.090)|
|T2|+ Leaders|-0.011<br>(0.112)|0.240***<br>(0.089)|
|T3|(safe spaces + husbands’ clubs)|0.197**<br>(0.096)|0.293***<br>(0.081)|
|T3|+ Leaders|0.141**|0.271**|
|||(0.071)|(0.118)|
|T4|(control spillover)|0.079|0.074|
|||(0.066)|(0.071)|
|T1|= T1 + L|.481|.819|
|T2|= T2 + L|.625|.55|
|T3|= T3 + L|.579|.862|
|T1|= T2|.0965|.235|
|T2|= T3|.174|.255|
|T1|= T3|.965|.0189|
|T1|+ L = T2 + L|.276|.0844|
|T2|+ L = T3 + L|.188|.814|
|T1|+ L = T3 + L|.921|.102|
|N||2,855|3,003|
|Co|ntrol mean|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; SRH = sexual and reproductive health; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

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# **4.2 Impacts on Mechanism Outcomes**

To understand mechanisms driving observed impacts on primary outcomes, we examine four pre-specified intermediate outcomes: SRH knowledge, gender attitudes, aspirations, and socio-emotional skills. Results are presented in Table 4.

**Safe spaces alone (T1).** Safe spaces alone significantly improved SRH knowledge (0.31 SD, p<0.01) and gender attitudes (0.21 SD, p<0.05). Examining specific SRH knowledge components (Table A9), T1 increased maternal health care attitudes by 0.23 SD (p<0.01). However, safe spaces alone showed no significant impact on socio-emotional skills or the overall aspirations index.

**Safe spaces with IGA support (T2).** T2 significantly improved SRH knowledge (0.31 SD, p<0.01), gender attitudes (0.16 SD, p<0.05), and socio-emotional skills (0.25 SD, p<0.01). Examining components, T2 increased the reported ideal age for women to marry by 0.77 years (p<0.05) (Table A10). Girls in T2 also aspired to have 0.32 (p<0.05) fewer children than girls in the control group (Table A11), suggesting that economic opportunities can shift fertility preferences even without dramatically altering broader aspirations.

**Safe spaces with husbands’ clubs (T3).** T3 significantly improved SRH knowledge (0.35 SD, p<0.01), gender attitudes (0.22 SD, p<0.01), and socio-emotional skills (0.19 SD, p<0.05). The improvements in gender attitudes were particularly notable, with significant effects on both the overall gender equality index and conformity to traditional gender roles (Table A10). Similar to T2, girls in T3 aspired to have 0.22 fewer children (p<0.10) (Table A11), although the overall aspirations index did not move significantly.

**Leader engagement added to each intervention.** Adding leaders consistently diluted the program’s impact on SRH knowledge. For instance, T1+Leaders showed a marginally significant effect (0.21 SD, p<0.10), smaller than the highly significant effect (0.31 SD, p<0.01) observed with safe spaces alone. Similarly, T2+Leaders and T3+Leaders showed no significant effects despite significant impacts in T2 and T3. The impacts on gender attitudes follow a similar pattern: T1+Leaders and T2+Leaders showed no significant effects, while T3+Leaders maintained a significant impact (0.20 SD, p<0.01). Qualitative research revealed that the leaders’ training was delivered through a cascade model with minimal follow-up support, which meant that they often struggled to remember and accurately convey nuanced content about SRH and gender norms. This potentially introduced contradictory or diluted messages that undermined what girls were learning in the safe spaces. However, leader engagement did enhance socio-emotional skills. T1+Leaders significantly improved SES (0.25 SD, p<0.05), an effect significantly larger than T1 (p=0.046). T2+Leaders maintained the significant SES impact (0.30 SD, p<0.01). Most notably, T3+Leaders produced the largest improvement in socio-emotional skills across all treatment arms (0.46 SD, p<0.01), significantly exceeding most other arms.

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Table 4: Impact on mechanism outcomes

||(1)<br>SRH<br>knowledge<br>(15 yo+)|(2)<br>Gender<br>attitudes|(3)<br>Aspirations|(4)<br>SES|
|---|---|---|---|---|
|T1 (safe spaces)|0.307**|0.208**|-0.183|-0.022|
||(0.121)|(0.092)|(0.134)|(0.113)|
|T1 + Leaders|0.207*|0.082|-0.161|0.247**|
||(0.115)|(0.105)|(0.120)|(0.113)|
|T2 (safe spaces + IGA)|0.312***<br>(0.119)|0.160**<br>(0.076)|0.127<br>(0.108)|0.248***<br>(0.090)|
|T2 + Leaders|0.183|0.071|-0.036|0.301***|
||(0.117)|(0.102)|(0.098)|(0.099)|
|T3 (safe spaces + husbands’ clubs)|0.348***<br>(0.120)|0.220***<br>(0.076)|0.012<br>(0.098)|0.191**<br>(0.092)|
|T3 + Leaders|0.226|0.204***|-0.005|0.459***|
||(0.147)|(0.069)|(0.158)|(0.105)|
|T4 (control spillover)|0.008|0.042|-0.029|0.120|
||(0.110)|(0.071)|(0.089)|(0.094)|
|T1 = T1 + L|.408|.273|.888|.0465|
|T2 = T2 + L|.3|.397|.189|.62|
|T3 = T3 + L|.402|.838|.922|.0199|
|T1 = T2|.97|.627|.0503|.0273|
|T2 = T3|.77|.464|.358|.569|
|T1 = T3|.735|.906|.195|.0838|
|T1 + L = T2 + L|.842|.933|.366|.667|
|T2 + L = T3 + L|.77|.192|.852|.188|
|T1 + L = T3 + L|.898|.254|.375|.0998|
|N|2,953|3,003|2,991|3,003|
|Control mean|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; SRH= sexual and reproductive health; yo = years old; SES = socio-emotional skills. The table presents estimated impacts of our 6 interventions’ combinations and the control spillove relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

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# **4.3 Impacts on Secondary Outcomes**

Beyond primary and mechanism outcomes, we examine secondary outcomes that capture broader dimensions of girls’ empowerment and well-being, and for some, may require more time to adjust: marriage and pregnancy, violence, decision-making (individual and couple), financial inclusion, nutrition, and mental health. Table 6 presents effects on the summary indices.

**Safe spaces alone (T1).** Safe spaces alone significantly improved mental health (0.28 SD, p<0.01) but showed no significant effects on marriage and pregnancy, violence, decisionmaking, or financial inclusion. However, unexpectedly, T1 significantly worsened nutrition outcomes (–0.40 SD, p<0.05).

**Safe spaces with IGA support (T2).** T2 improved mental health (0.27 SD, p<0.05) and, like T1, worsened nutrition (–0.36 SD, p<0.05). This combination had no significant impact on marriage and pregnancy, violence, finance, or decision-making.

**Safe spaces with husbands’ clubs (T3).** T3 significantly improved decision-making on both individual matters (0.20 SD, p<0.10) and within couples (0.30 SD, p<0.05). However, T3 also showed the largest negative impact on nutrition (–0.68 SD, p<0.01) and no significant effects on mental health, violence, finance, or the marriage-and-pregnancy index.

**Leader engagement added to each intervention.** Adding leaders produced notably different effects across treatment arms. In T1+Leaders, the positive mental health effect observed in T1 disappeared, while T1+Leaders significantly improved decision-making on both individual matters (0.25 SD, p<0.10) and within couples (0.41 SD, p<0.01). T2+Leaders eliminated the mental health benefit from T2 and significantly increased ever-pregnancy by 5.4 percentage points (p<0.01), a 7% increase relative to the control mean (Table A13). This suggests that IGA support combined with leader engagement did not sufficiently alter the opportunity cost of childbearing in a context where girls engaged in flexible incomegenerating activities, such as agriculture, market stands, and retail, that were compatible with early motherhood. However, T2+Leaders did improve financial inclusion (0.15 SD, p<0.10), an outcome not observed in T2 alone. T3+Leaders yielded the most substantial impacts on secondary outcomes. Decision-making on individual matters increased by 0.40 SD (p<0.01), and mental health improved by 0.27 SD (p<0.05). We also find suggestive evidence that T3+Leaders reduced current pregnancy by 3.9 percentage points (p<0.10), a 36% reduction relative to the control mean, and reduced ever being married by 4.6 percentage points (p<0.10) (Table A13). It is worth noting that the pregnancy effect may reflect timing rather than sustained fertility change given that ever-pregnancy remained unaffected. —– This full package safe spaces, husbands’ clubs, and leader engagement—– appears most effective at expanding girls’ agency and decision-making. The nutrition decline observed in T3 was also no longer significant in T3+Leaders, though the reason for this difference is unclear.

Overall, secondary outcomes showed limited short-run impacts. The nutrition findings, i.e., significant declines in dietary diversity across T1, T2, and T3, were particularly unex22
pected. This may reflect shifts away from traditional dietary practices, miscommunication about nutrition messages in program delivery, or reallocation of household resources. We flag this for future research but note that it does not seem to reflect deteriorating household well-being, as mental health improved in T1 and T2.

Table 5: Impact on secondary outcomes

||(1)<br>Marriage and<br>pregnancy|(2)<br>Violence<br>(15 yo+)|(3)<br>Decision-<br>making<br>(individual)|(4)<br>Decision-<br>making<br>(couples)|(5)<br>Finance|(6)<br>Nutrition|(7)<br>Mental<br>health|
|---|---|---|---|---|---|---|---|
|T1 (safe spaces)|0.006|0.051|0.069|0.111|0.026|-0.403**|0.278***|
||(0.061)|(0.090)|(0.117)|(0.144)|(0.125)|(0.161)|(0.096)|
|T1 + Leaders|-0.019|-0.029|0.251*|0.405***|0.028|-0.239*|-0.002|
||(0.072)|(0.113)|(0.135)|(0.145)|(0.099)|(0.144)|(0.107)|
|T2 (safe spaces + IGA)|-0.054|-0.015|0.159|0.170|0.053|-0.357**|0.268**|
||(0.059)|(0.082)|(0.128)|(0.142)|(0.095)|(0.155)|(0.104)|
|T2 + Leaders|-0.015|0.085|0.002|0.204|0.148|-0.152|-0.003|
||(0.070)|(0.074)|(0.115)|(0.150)|(0.092)|(0.154)|(0.112)|
|T3 (safe spaces + husbands’ clubs)|-0.036|0.142|0.199*|0.297**|-0.045|-0.679***|0.108|
||(0.055)|(0.090)|(0.102)|(0.126)|(0.119)|(0.203)|(0.134)|
|T3 + Leaders|0.078|0.019|0.395***|0.407**|0.188|-0.048|0.268**|
||(0.060)|(0.091)|(0.127)|(0.168)|(0.115)|(0.137)|(0.114)|
|T4 (control spillover)|0.008|0.049|0.081|0.224*|-0.125*|-0.247**|0.039|
||(0.053)|(0.087)|(0.106)|(0.121)|(0.073)|(0.125)|(0.092)|
|T1 = T1 + L|.765|.516|.184|.0626|.989|.389|.0132|
|T2 = T2 + L|.645|.206|.279|.848|.363|.27|.0309|
|T3 = T3 + L|.11|.247|.154|.551|.112|.003|.293|
|T1 = T2|.419|.486|.538|.737|.84|.809|.927|
|T2 = T3|.804|.105|.771|.431|.452|.154|.256|
|T1 = T3|.573|.369|.297|.251|.637|.22|.227|
|T1 + L = T2 + L|.973|.297|.0928|.245|.278|.633|.998|
|T2 + L = T3 + L|.258|.479|.00697|.292|.758|.551|.0409|
|T1 + L = T3 + L|.256|.703|.359|.99|.22|.259|.042|
|N|2,995|2,931|2,919|1,734|2,995|3,003|3,003|
|Control mean|0|0|0|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. IGA = income-generating activity; yo = years old. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

23
# **4.4 Heterogeneity by Baseline Marital Status**

Tables 6, 7, and 8 examine whether program effects varied by baseline marital status ("married" is defined as reporting a civil or informal union at baseline).<sup>12</sup> While we pre-specified both marital status and age as dimensions for heterogeneity analysis, only 13% of respondents were under age 15 at baseline, limiting statistical power for age-based analysis. We focus on the most substantively important patterns. The results show a clear pattern: SRH outcomes generally benefited unmarried girls more, while economic outcomes benefited married and unmarried girls equally when interventions include either IGA support or husbands’ clubs.

**SRH behavior and knowledge.** Impacts on SRH behavior concentrated primarily among unmarried girls. In T1, T1+Leaders, and T3+Leaders, only unmarried girls showed significant improvements (0.26–0.31 SD, p<0.05 or better), though the difference between married and unmarried girls was not statistically significant. T3 was the exception, showing marginally significant positive effects for both married and unmarried girls. SRH knowledge follows a similar pattern: T1 and T1+Leaders primarily benefited unmarried girls (0.43 SD and 0.29 SD, p<0.01 and p<0.10), while T2, T3, a with or without leader engagement, improved knowledge for both married and unmarried girls.

**Economic outcomes.** Safe spaces alone (T1) benefited only unmarried girls economically (0.21 SD, p<0.05), with married girls showing a significant negative interaction (–0.25 SD, p<0.05). This pattern changed when interventions included either IGA support (T2, T2+Leaders) or husbands’ clubs (T3, T3+Leaders)—– both married and unmarried girls experienced significant improvements with no differences between groups. This suggests that economic resources or engagement with male household gatekeepers may help married girls overcome the constraints that limited the effectiveness of safe spaces when implemented alone.

**Gender attitudes and socio-emotional skills.** Gender attitudes improved more for unmarried girls in several arms (T1, T3, T3+Leaders), with T3+Leaders showing a marginally negative interaction for married girls (–0.25 SD, p<0.10). For SES, T2 produced larger gains among unmarried girls (0.43 SD, p<0.01) with a significant negative interaction for married girls (–0.28 SD, p<0.05), while T2+Leaders, T3, and T3+Leaders benefited both groups similarly.

**Secondary outcomes.** Most secondary outcomes, including decision-making on individual matters, nutrition, and mental health, did not exhibit meaningful differences by marital status. One exception was the violence index in T3+Leaders, where married girls show a significantly larger improvement (interaction: 0.34 SD, p<0.05), though the overall effect for married girls remained statistically indistinguishable from zero. These heterogeneity results suggest that unmarried girls benefited more from informationbased components for SRH outcomes, likely because they were at an earlier life stage (17.8 12At baseline, between 57% (T3 + Leaders) and 67% (control) of the non-attrited sample were married; the share is balanced across treatment arms (Table 1).

24
years on average vs 20.5 years for married girls at baseline) where information can more easily influence life decisions, and they faced fewer constraints from existing marriages. For married girls, gains emerged primarily when interventions directly engaged their environment, particularly through husbands’ clubs, or provided tangible economic resources. However, given reduced statistical power and multiple testing, these findings should be interpreted as suggestive rather than definitive.

Table 6: Impact on primary outcomes by marital status at baseline

||(1)|(2)|
|---|---|---|
||SRH||
||behavior<br>(15 yo+)|Economic<br>outcomes|
|T1 (safe spaces)|0.310***<br>|0.208**<br>|
||(0.114)|(0.101)|
|T1 x Married|-0.170|-0.251**|
||(0.145)|(0.118)|
|T1 + Leaders|0.267**|0.138|
||(0.123)|(0.133)|
|T1 + Leaders x Married|-0.210|-0.173|
||(0.167)|(0.152)|
|T2 (safe spaces + IGA)|-0.038|0.182|
||(0.115)|(0.112)|
|T2 x Married|0.140<br>|0.008<br>|
||(0.126)|(0.124)|
|T2 + Leaders|-0.121|0.326***|
||(0.216)|(0.111)|
|T2 + Leaders x Married|0.171|-0.128|
||(0.241)|(0.097)|
|T3 (safe spaces + husbands’ clubs)|0.242*|0.367***|
||(0.132)|(0.097)|
|T3 x Married|-0.067|-0.109|
||(0.128)|(0.123)|
|T3 + Leaders|0.261***|0.341**|
||(0.096)|(0.160)|
|T3 + Leaders x Married|-0.197|-0.101|
||(0.150)|(0.183)|
|T4 (control spillover)|0.156|0.159*|
||(0.104)|(0.092)|
|T4 (control spillover) x Married|-0.121|-0.129|
||(0.121)|(0.100)|
|T1 + T1 x Mar = 0|.147|.707|
|(T1 + L) + (T1 + L) x Mar = 0|.643|.796|
|T2 + T2 x Mar = 0|.276|.0711|
|(T2 + L) + (T2 + L) x Mar = 0|.683|.0355|
|T3 + T3 x Mar = 0|.0884|.0139|
|(T3 + L) + (T3 + L) x Mar = 0|.55|.0845|
|N|2,852|2,999|
|Control mean|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; Mar = in union at baseline; SRH = sexual and reproductive health; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations relative to the pure control group, for the unmarried then the married sample. All regressions control for the baseline value of the outcome variable, an indicator for being married at baseline, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

25
Table 7: Impact on mechanism outcomes by marital status at baseline

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||SRH<br>knowledge<br>(15 yo+)|Gender<br>attitudes|Aspirations|SES|
|T1 (safe spaces)|0.431***|0.246**|-0.174|-0.117|
||(0.162)|(0.122)|(0.110)|(0.157)|
|T1 x Married|-0.211|-0.064|-0.029|0.157|
||(0.169)|(0.126)|(0.188)|(0.141)|
|T1 + Leaders|0.290*|0.144|-0.166|0.416***|
||(0.171)|(0.136)|(0.139)|(0.156)|
|T1 + Leaders x Married|-0.139|-0.104|0.004|-0.283|
||(0.158)|(0.173)|(0.158)|(0.180)|
|T2 (safe spaces + IGA)|0.191|0.203*|0.077|0.425***|
||(0.166)|(0.119)|(0.128)|(0.120)|
|T2 x Married|0.184|-0.065|0.067|-0.280**|
||(0.127)|(0.148)|(0.111)|(0.113)|
|T2 + Leaders|0.154|0.126|0.055|0.361**|
||(0.175)|(0.137)|(0.121)|(0.147)|
|T2 + Leaders x Married|0.049|-0.080|-0.146|-0.096|
||(0.150)|(0.161)|(0.136)|(0.148)|
|T3 (safe spaces + husbands’ clubs)|0.320**|0.287***|0.051|0.296**|
||(0.154)|(0.086)|(0.128)|(0.144)|
|T3 x Married|0.050|-0.107|-0.073|-0.175|
||(0.114)|(0.093)|(0.113)|(0.132)|
|T3 + Leaders|0.298*|0.347***|-0.107|0.497***|
||(0.156)|(0.096)|(0.165)|(0.132)|
|T3 + Leaders x Married|-0.125|-0.245*|0.167|-0.067|
||(0.190)|(0.125)|(0.175)|(0.152)|
|T4 (control spillover)|0.044|0.139*|-0.045|0.176|
||(0.147)|(0.080)|(0.108)|(0.120)|
|T4 (control spillover) x Married|-0.061|-0.163|0.014|-0.099|
||(0.119)|(0.116)|(0.109)|(0.111)|
|T1 + T1 x Mar = 0|.107|.0755|.29|.718|
|(T1 + L) + (T1 + L) x Mar = 0|.19|.761|.265|.318|
|T2 + T2 x Mar = 0|.000851|.143|.215|.133|
|(T2 + L) + (T2 + L) x Mar = 0|.0722|.705|.427|.0139|
|T3 + T3 x Mar = 0|.00187|.0481|.826|.184|
|(T3 + L) + (T3 + L) x Mar = 0|.363|.246|.752|.000904|
|N|2,949|2,999|2,990|2,999|
|Control mean|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; mar = married; yo = years old; SRH = sexual and reproductive health. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group, for the unmarried then the married sample. All regressions control for the baseline value of the outcome variable, an indicator for being married at baseline, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

26
Table 8: Impact on secondary outcomes by marital status at baseline

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
||Violence<br>(15 yo+)|Decision-<br>making<br>(individual)|Finance|Nutrition|Mental<br>health|
|T1 (safe spaces)|-0.050|-0.028|0.038|-0.412**|0.302**|
||(0.102)|(0.167)|(0.155)|(0.181)|(0.124)|
|T1 x Married|0.162|0.151|-0.014|0.021|-0.035|
||(0.121)|(0.163)|(0.153)|(0.152)|(0.125)|
|T1 + Leaders|0.131|0.153|0.174|-0.161|-0.131|
||(0.120)|(0.153)|(0.126)|(0.160)|(0.150)|
|T1 + Leaders x Married|-0.261|0.148|-0.226|-0.110|0.218|
||(0.163)|(0.182)|(0.145)|(0.143)|(0.162)|
|T2 (safe spaces + IGA)|-0.029|0.206|0.034|-0.344**|0.260**|
||(0.112)|(0.160)|(0.097)|(0.169)|(0.128)|
|T2 x Married|0.020|-0.076|0.026|-0.017|0.014|
||(0.140)|(0.144)|(0.114)|(0.159)|(0.127)|
|T2 + Leaders|-0.027|0.121|0.032|-0.088|0.011|
||(0.111)|(0.149)|(0.097)|(0.206)|(0.148)|
|T2 + Leaders x Married|0.168|-0.185|0.185|-0.100|-0.018|
||(0.149)|(0.142)|(0.129)|(0.221)|(0.161)|
|T3 (safe spaces + husbands’ clubs)|0.090|0.208|0.113|-0.626***|0.097|
||(0.098)|(0.130)|(0.188)|(0.209)|(0.151)|
|T3 x Married|0.079|-0.019|-0.260|-0.083|0.020|
||(0.120)|(0.125)|(0.170)|(0.127)|(0.115)|
|T3 + Leaders|-0.182|0.389**|0.251*|0.061|0.295*|
||(0.130)|(0.156)|(0.142)|(0.154)|(0.176)|
|T3 + Leaders x Married|0.341**|0.003|-0.107|-0.187|-0.042|
||(0.138)|(0.164)|(0.171)|(0.147)|(0.175)|
|T4 (control spillover)|-0.048|0.095|-0.087|-0.277**|0.063|
||(0.101)|(0.144)|(0.086)|(0.135)|(0.112)|
|T4 (control spillover) x Married|0.157|-0.035|-0.063|0.056|-0.034|
||(0.109)|(0.129)|(0.092)|(0.113)|(0.120)|
|T1 + T1 x Mar = 0|.299|.312|.865|.0267|.0123|
|(T1 + L) + (T1 + L) x Mar = 0|.369|.0718|.655|.085|.455|
|T2 + T2 x Mar = 0|.927|.343|.602|.0407|.0204|
|(T2 + L) + (T2 + L) x Mar = 0|.147|.599|.0648|.285|.954|
|T3 + T3 x Mar = 0|.128|.0911|.154|.00106|.409|
|(T3 + L) + (T3 + L) x Mar = 0|.103|.00857|.319|.418|.0256|
|N|2,935|2,923|2,999|3,007|3,007|
|Control mean|0|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; mar = married; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group, for the unmarried then the married sample. All regressions control for the baseline value of the outcome variable, stratification fixed effects, an indicator for being married at baseline, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

27
# **5 Discussion**

This study demonstrates that comprehensive, multi-sectoral approaches are most effective for empowering adolescent girls in low-resource settings. Using a cluster randomized controlled trial in northern Côte d’Ivoire, we evaluated safe spaces combined with various accompanying measures: livelihood support, husbands’ clubs, and community leaders’ engagement. One year after the interventions ended, we find that safe spaces alone improved girls’ SRH behavior and knowledge, mental health, and gender attitudes, but not decision-making or economic outcomes. When combined with husbands’ clubs, safe spaces yielded substantially greater impacts across multiple domains. In localities where safe spaces were combined with both leaders’ engagement and husbands’ clubs, we observed the most substantial impacts on girls’ empowerment outcomes, including a 36% reduction in pregnancy relative to control, though this effect is only marginally significant (p<0.10).

Two unexpected findings stand out, however. First, combining safe spaces with livelihood support increased the probability of ever being pregnant by 5.4 percentage points, significant at the 1% level, suggesting the intervention may not have sufficiently altered the opportunity cost of childbearing. The types of income-generating activities girls pursued—predominantly agriculture, market stands, and retail—are flexible and compatible with childbearing responsibilities. Second, community and religious leaders’ engagement yielded mixed results. While leaders amplified impacts when combined with husbands’ clubs, they muted SRH knowledge gains when paired with other components. This pattern likely stems from the cascade training method used for leaders, which is prone to information loss and may have introduced contradictory messaging about gender roles and family planning. This underscores that community engagement requires careful attention to training quality, message fidelity, and alignment across stakeholders.

Indeed, implementation quality proved crucial for explaining our results. Implementation challenges included shortage of qualified mentors, resistance from some community leaders due to entrenched gender norms, and COVID-19-related delays that reduced implementation from 18 to 12 months. While the IGA intervention met numerical targets, sustainability challenges highlighted the need for stronger ongoing support mechanisms. These factors likely attenuated program impacts.

Our findings both confirm and extend previous research on adolescent empowerment programs. Consistent with prior evaluations of safe spaces programs, we find improvements in reproductive health knowledge and attitudes. However, our experimental design allows us to demonstrate that life skills and SRH training alone do not explain improvements in economic outcomes —–vocational training and cash grants appear critical for economic empowerment. Regarding male engagement, our results align with recent evidence (e.g., Shah et al. (2022)), while adding important nuance about implementation: safe spaces yield limited structural change alone but become transformative when paired with systematic male engagement through husbands’ clubs. In addition, our findings on leaders’ engagement illustrate scaling 28
challenges, specifically, that interventions can lose fidelity when implemented through cascade training without adequate quality control.

These findings have important implications for program design and policy. Three key lessons emerge. First, adolescent-centered interventions like safe spaces are valuable but insufficient for structural empowerment. Addressing the enabling environment through systematic male engagement and community engagement is critical. Second, the modality of community engagement matters critically. Leaders’ engagement yielded positive impacts only when paired with husbands’ clubs; implementing leaders’ training in isolation risks diluted messaging. When engaging leaders, programs should match ambitious goals with adequate training, ongoing support, and careful attention to message fidelity. Third, multi-sectoral approaches addressing multiple barriers simultaneously appear most effective, though they require substantially more resources and careful coordination. Policymakers must balance potential impact against implementation costs and complexity.

These resource constraints can be substantial. Under the program evaluated in this paper, community safe spaces absorbed the largest share of resources (USD 1.94 million) but were the least costly per participant at about USD 122 per girl. The other components vary considerably in cost: IGA support required around USD 460 per girl, husbands’ clubs USD 190 per man, and leaders’ engagement only USD 6 per girl in treated localities. These figures illustrate a trade-off: safe spaces provide broad but lighter-touch outreach and can serve as an entry point, a platform for broader girls’ programming, while add-on interventions offer more intensive engagement yielding stronger outcomes. However, it is worth noting that the leaders’ engagement intervention was least costly per girl but produced the most inconsistent results. This suggests that cost-effectiveness depends critically on whether intervention design matches implementation capacity.

This study has several limitations. We measure outcomes only one year post-intervention; longer-term effects remain unknown. A 20% attrition rate may affect our results. We cannot fully isolate all mechanisms of change, such as whether husbands’ clubs work primarily through shifting male attitudes, improving couple communication, or reducing household resistance to girls’ activities. Our findings from northern Côte d’Ivoire may not generalize to contexts with different gender norms, economic structures, or baseline female empowerment levels.

In summary, this study provides rigorous evidence that multi-sectoral approaches to adolescent girls’ empowerment—combining direct support to girls with systematic engagement of their male partners and communities—are most effective at addressing multiple barriers faced by adolescent girls in low-income countries. However, successful implementation requires careful attention to message fidelity across intervention components, adequate resources for quality delivery, and recognition that some intervention combinations may produce unintended consequences.

29
# **References**

- Anderson, M. L. (2008): “Multiple inference and gender differences in the effects of early intervention: A reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects,” <u>Journal</u> of the American statistical Association, 103, 1481–1495.

- Andrew, A., S. Krutikova, G. Smarrelli, and H. Verma (2022): “Gender norms, violence and adolescent girls’ trajectories: evidence from a field experiment in India,” Working Paper, IFS 22/41.

- Bandiera, O., N. Buehren, R. Burgess, M. Goldstein, S. Gulesci, I. Rasul, and M. Sulaiman (2020): “Women’s empowerment in action: evidence from a randomized control trial in Africa,” American Economic <u>Journal:</u> Applied Economics, 12, 210–59.

- Bandiera, O., N. Buehren, M. P. Goldstein, I. Rasul, and A. Smurra (2019): “The Economic Lives of Young Women in the Time of Ebola : Lessons from an Empowerment Program,” Policy Research Working Paper Series 8760, The World Bank.

- Belloni, A., V. Chernozhukov, and C. Hansen (2014): “High-dimensional methods and inference on structural and treatment effects,” <u>Journal</u> of Economic Perspectives, 28, 29–50.

- Bergstrom, K. A. and B. Ozler (2021): “Improving the Well-Being of Adolescent Girls in Developing Countries,” Policy Research Working Paper Series 9827, The World Bank.

- Buehren, N., M. Goldstein, S. Gulesci, I. Salcher, M. Sulaiman, and V. Yam (2024): “What We Can Learn When Impacts Fail to Replicate: Lessons From an Empowerment Programme for Young Women in Tanzania,” The <u>Journal</u> of Development <u>Studies,</u> 1–11.

- Cohen, I., M. Abubakar, and D. Perlman (2023): “Pathways to Choice: A Bundled Intervention against Child Marriage,” .

- Duflo, E. (2012): “Women empowerment and economic development,” <u>Journal</u> of Economic Literature, 50, 1051–79.

- Haberland, N., T. de Hoop, S. Desai, S. Engebretsen, and T. Ngo (2021): “Adolescent girls’ and young women’s economic empowerment programs: Emerging insights from a review of reviews,” Tech. rep.

- Institut National de la Statistique (2022): “Rapport d’enquête du SIGI Côte d’Ivoire,” Tech. rep.

- Institut National de la Statistique and ICF (2012): “Enquête Démographique et de Santé et à Indicateurs Multiples de Côte d’Ivoire 2011-2012,” Tech. rep., INS/Côte d’Ivoire and ICF.

30
- ——— (2021): “Enquête Démographique et de Santé de Côte d’Ivoire,” Report, INS/Côte

- d’Ivoire and ICF.

- Malhotra, A. and S. Elnakib (2021): “20 years of the evidence base on what works to prevent child marriage: A systematic review,” <u>Journal</u> of Adolescent Health, 68, 847–862.

- Marsh, V., C. Delavallade, S. Das, L. Rouanet, T. Koroknay-Palicz, and D. McDaniel (2025): “Assessing Workplace Social, Emotional, and Behavioral Skills in Africa: The ESTEEM Framework,” Policy Research Working Paper 11128, World Bank, Washington, DC.

- Shah, M., J. Seager, J. Montalvao, and M. Goldstein (2022): “Two Sides of Gender: Sex, Power, and Adolescence,” Working Paper, World Bank, Washington, DC.

- Temin, M. and C. J. Heck (2020): “Close to home: Evidence on the impact of communitybased girl groups,” <u>Global</u> Health: <u>Science</u> and Practice, 8, 300–324.

- United Nations Development Programme (2022): “Human Development Report 2021-22,” Tech. rep.

- Weny, K., R. Snow, and S. Zhang (2017): “The demographic dividend atlas for Africa: Tracking the potential for a demographic dividend,” Tech. rep., United Nations Population Fund.

- World Bank (2011): <u>World</u> development report 2012: <u>Gender</u> equality and development, The World Bank.

31
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**Attrition and Take-up Tables**

Table A1: Attrition

|||Attriter<br>midline survey|
|---|---|---|
|T1|(safe spaces)|0.021|
|||(0.041)|
|T1|+ Leaders|-0.063*|
|||(0.035)|
|T2|(safe spaces + IGA)|-0.063<br>(0.041)|
|T2|+ Leaders|-0.091***<br>(0.030)|
|T3|(safe spaces + husbands’ clubs)|-0.098**<br>(0.042)|
|T3|+ Leaders|-0.016|
|||(0.043)|
|T4|(control spillover)|0.002<br>(0.031)|
|T1|= T1 + L|.0621|
|T2|= T2 + L|.496|
|T3|= T3 + L|.128|
|T1|= T2|.0927|
|T2|= T3|.496|
|T1|= T3|.0166|
|T1|+ L = T2 + L|.427|
|T2|+ L = T3 + L|.0964|
|T1|+ L = T3 + L|.328|
|N||3,785|
|Co|ntrol mean|.238|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, OLS regression with standard errors in parentheses clustered at the locality level. IGA = income-generating activity; OLS = ordinary least squares. The dependent variable for column (1) is a dummy for attrited individuals at the follow-up survey. The p-values of the difference tests between the treatments are in the second part of the table. This regression controls stratification fixed effects.

34
Table A2: Attendance per treatment arm (self-reported take-up)

|||(1)<br>Attended at least<br>one safe space session|
|---|---|---|
|T1|(safe spaces)|0.496<br>(0.500)|
|T1|+ Leaders|0.474|
|||(0.500)|
|T2|(safe spaces + IGA)|0.652<br>(0.477)|
|T2|+ Leaders|0.494<br>(0.500)|
|T3|(safe spaces + husbands’ clubs)|0.476<br>(0.500)|
|T3|+ Leaders|0.605<br>(0.486)|
|T4|(control spillover)|0.026<br>(0.159)|
|Co|ntrol|0.018<br>(0.131)|
|N||2,999|

_Note:_ Standard deviations in parentheses. IGA = income-generating activity.

35
Table A3: Determinants of attendance (self-reported take-up)

||(1)<br>Attended at least|
|---|---|
||one safe space session|
|T1 (safe spaces)|0.456***<br>(0.065)|
|T1 + Leaders|0.466***<br>|
||(0.062)|
|T2 (safe spaces + IGA)|0.615***<br>|
||(0.069)|
|T2 + Leaders|0.479***<br>|
||(0.054)|
|T3 (safe spaces + husbands’ clubs)|0.449***|
||(0.074)|
|T3 + Leaders|0.560***|
||(0.058)|
|Rural|0.086**|
||(0.039)|
|Household size|0.002|
||(0.002)|
|Housedhold head is female|-0.029|
||(0.025)|
|Household head is polygamous|-0.033**|
||(0.015)|
|Household head had no formal education|-0.005|
||(0.017)|
|Household head is Muslim|-0.014<br>|
||(0.024)|
|Adolescent age|0.003<br>|
||(0.003)|
|Adolescent has been married/lived with a husband/partner|-0.008<br>|
||(0.021)|
|Adolescent has gone to school|0.014|
||(0.019)|
|Index decision-making: individual issues (categories 1–6)|-0.000<br>(0.002)|
|Ado has been engaged in any IGA (last 30 days)|0.003|
||(0.019)|
|T1 = T1 + L|.913|
|T2 = T2 + L|.12|
|T3 = T3 + L|.216|
|T1 = T2|.088|
|T2 = T3|.0944|
|T1 = T3|.938|
|T1 + L = T2 + L|.867|
|T2 + L = T3 + L|.307|
|T1 + L = T3 + L|.256|
|N|2,999|
|Control mean|.018|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, OLS regression with standard errors in parentheses clustered at the locality level. IGA = income-generating activity; OLS = ordinary least squares. The dependent variable for column (1) is a dummy for attending at least one safe space session. When the baseline value is missing, it is imputed and a dummy indicating whether the variable is imputed or noted is added as control. This regression controls stratification fixed effects.

36
# **Variables and Indices Composition**

Table A4: Indices composition

|Index|Variables|
|---|---|
|SRH behavior (15 yo+)|Ever had sex [yes = 1] (15 yo+) (Reserve)<br>Had transactional sex in the last 6 months [yes = 1] (15 yo+) (Reserve)<br>Was sexually active in the last 12 months [yes = 1] (15 yo+) (Reserve)<br>Used a condom in last sexual intercourse [yes = 1] (15 yo+)<br>Ever used a contraception to avoid pregnancy [yes = 1] (15 yo+)<br>|
||Engaged in any IGA (last 6 months) [yes = 1]<br>Total profts cash (last 30 days) (IHS)|
|IGA|Received income from IGA (last 30 days) [yes = 1]<br>Number of IGA adolescent has been engaged in (last 6 months)<br>Number of IGA adolescent took the initiative (last 6 months)<br>Worked in a nonagricultural IGA (last 6 months)[yes = 1]|
|SRH knowledge & attitude|Knows of at least one modern contraception method [yes = 1]<br>Has ever heard of HIV/AIDS [yes = 1] (15 yo+)<br>Agrees using a condom can reduce HIV transmission risk [yes = 1] (15 yo+)<br>Attitude index on maternal health care (15 yo+)<br>|
||Index gender equality (std)<br>Index gender equality based on conformity to traditional gender role beliefs (std)<br>Ideal age for a woman to marry|
|Gender attitudes|Ideal age for a man to marry<br>Finds at least one disadvantage for a girl to marry before 18 [yes=1]<br>Expected education for adolescent’s female children<br>Gap between the ideal level of education for her daughter(s) and son(s)|
|Aspirations|Adolescent’s ideal number of children<br>Occupation desired by adolescent is high or intermediate status [yes = 1]<br>Revenue adolescent wishes to make from desired occupation (IHS)|
|SES|Self esteem index<br>General efcacy index<br>Self-awareness index<br>Problem-solving index<br>Perseverance index<br>Index on ability to infuence others<br>Creativity index|
|Marriage and pregnancy|Adolescent ever been married [yes = 1] (Reserve)<br>Adolescent currently pregnant [yes = 1] (Reserve)<br>Adolescent ever been pregnant [yes = 1] (Reserve)|
||Experienced at least one type of emotional violence [yes = 1] (Reserve)|
|Violence (15 yo+)|Experienced at least one type of physical violence [yes = 1] (15 yo+) (Reserve)<br>Experienced at least one type of sexual violence [yes = 1] (15 yo+) (Reserve)|
|Decision-making individual|Decision-making index on individual issues (std)|
|Decision-making couples (married)|Decision-making index on couples issues (if married at baseline and midline) (std)|
|Finances|Borrowed money in the last 12 months [yes = 1]<br>Saved money in the last 12 months [yes = 1]|
|Nutrition|Adolescent’s dietary diversity score [0–1]<br>|
|Mental health|Overall, adolescent feels happy or very happy [yes = 1]<br>Mental health index|

_Note:_ AIDS = acquired immunodeficiency syndrome; HIV = human immunodeficiency virus; IGA = income-generating activity; IHS = inverse hyperbolic sine; SES = socio-emotional skills; SRH = sexual and reproductive health; std = standard deviation; yo = years old.

37
Table A5: Statements on gender equality and gender-based violence

|Index|Items|
|---|---|
|Gender equality|1. Who should have the highest level of education in the family?<br>2. Who should earn money for the family?<br>3. Who should be responsible for washing, cleaning and cooking?<br>4. If there is no water pump or tap, who should go fetch water?<br>5. Who should be in charge of feeding, and washing the kids?<br>6. Who should be in charge of caring for sick people?<br>7. Who should help the children with their homework?|
|Decision-making (individual)|To what extent do you make your own decision when it comes to<br>1. The money you earn?<br>2. Your studies?<br>3. Your work?<br>4. Your healthcare?<br>5. The tasks you do in a given day?<br>6. Your whereabouts?|
|Decision-making (couples)|To what extent do you make your own decision when it comes to<br>1. Family planning?<br>2. Your pregnancies?<br>3. The way the household’s money is spent?<br>4. The main household purchases?<br>5. The visits you pay to your family?|
|Physical violence|1. Has anyone hurt you physically, punched, shoved, slapped, hit you in the last 12 months?<br>2. Has anyone kicked you, dragged you to the ground, tried to strangle you,<br>burned you, threatened you with a knife, or pulled a gun on you in the last 12 months?|
|Sexual violence|1. Has anyone ever physically forced you to have sex when you didn’t want to in the last 12 months?<br>2. Has anyone forced you to do other sexual practices that you didn’t want to do in the last 12 months?<br>3. Has anyone touched you in a sexual way, I mean your breasts, your buttocks, or your private parts,<br>without your permission, touching without permission includes pinching, grabbing, rubbing, or fondling against your will,<br>either directly or through your clothing in the last 12 months?|
|Emotional violence|1. Has anyone said or done something to humiliate you in front of other people in the last 12 months?<br>2. Has anyone threatened to hurt or harm you or anyone close to you in the last 12 months?<br>3. Has anyone insulted or belittled you in the last 12 months?|

38
Table A6: Statements on socio-emotional skills and on mental health

|Index|Items<br>|
|---|---|
|Problem-solving skills|1. When I am faced/confronted with a problem, I can usually fnd several solutions.<br>2. If I am in trouble, I can usually think of a solution<br>3. I solve most problems if I put in the necessary efort<br>4. Thanks to my skillful and creative thinking, I know how to handle unforeseen situations<br>5. I can always solve difcult problems if I try hard enough<br>6. When I have a decision to make, I take the time to try to predict the positive and negative consequences of each possible option before I act<br>7. When I have a problem to solve, one of the frst things I do is get as many facts about the problem as possible<br>8. When I am trying to solve a problem, I think of as many options as possible until I can no longer come up with any more ideas<br>9. I am able to come up with new and diferent ideas<br>10. I like to think of new ways of doing things<br>11. I come up with new ways to do things<br>12. I am an original thinker<br>13. I plan tasks carefully|
||1. I fnish what I begin<br>2. Setbacks do not discourage me|
|Perseverance skills|3. I am diligent<br>4. If someone is against me, I can fnd ways to get what I want<br>5. It is easy for me to stick to my aims and achieve my goals<br>6. I am confdent that I could deal conveniently with unexpected events|
||1. My behavior often puzzles me (reverse negatively coded items)<br>2. I understand my own behaviors<br>3. I am aware of my thoughts<br>4. I monitor my thinking to ensure it is accurate<br>5. I analyze my behavior after I make mistakes|
|Self-awareness skills|6. I know the skills I have that other people do not have<br>7. I assess my strengths and weaknesses in new situations<br>8. I criticize my own abilities<br>9. I review how I am thinking when I make a mistake<br>10. I have a clear sense of who I am|
||11. I understand other people’s thoughts, feelings, and actions better than my own (reverse negatively coded items)|
|Emotional regulation skills|1. I can remain calm when I am facing difculties because I can rely on my abilities to cope|
||1. I can communicate my ideas in a way that will convince people to agree with me<br>2. People like to follow my ideas<br>3. When I ask for help, I receive it|
|Ability to infuence|4. I am good at getting people to help me when I need it<br>5. I am good at examining social situations to determine how to present myself well<br>6. I observe social situations carefully before deciding how to present an idea to others<br>7. I am able to adjust my behavior to make a good impression|
||1. Have you been able to focus on what you are doing ?<br>2. Have you been sleep-deprived because of a problem?<br>3. Have you felt able to make decisions?<br>4. Have you felt stressed?<br>5. Have you lost self-confdence?|
|Mental health|6. Did you feel that you had a useful role in life?<br>7. Did you feel that you could not overcome difculties?<br>8. Have you been able to enjoy your normal daily activities?<br>9. Have you been able to cope with your own problems?<br>10. Have you been feeling unhappy and depressed?<br>11. Have you considered yourself as a useless person?<br>12. Have you been reasonably happy, overall?|

39
# **Results on Primary Outcomes**

Table A7: Impact on SRH behavior (15yo+)

||Transactional<br>sex|Had intercourse<br>last 12m|Used condom<br>last<br>intercourse|Uses<br>contraception<br>to delay<br>pregnancy|
|---|---|---|---|---|
|T1 (safe spaces)|-0.026**<br>(0.011)|0.018<br>(0.016)|-0.004<br>(0.029)|0.041<br>(0.037)|
|T1 + Leaders|-0.010|0.007|-0.013|0.039|
||(0.015)|(0.026)|(0.029)|(0.037)|
|T2 (safe spaces + IGA)|0.010|-0.015|0.028|-0.016|
||(0.017)|(0.019)|(0.025)|(0.029)|
|T2 + Leaders|0.036|-0.029|0.044|0.053**|
||(0.027)|(0.021)|(0.037)|(0.026)|
|T3 (safe spaces + husbands’ clubs)|-0.006|0.032**|0.040|0.064*|
||(0.015)|(0.016)|(0.036)|(0.037)|
|T3 + Leaders|-0.005|0.002|0.043*|0.036|
||(0.014)|(0.022)|(0.025)|(0.034)|
|T4 (control spillover)|0.001|0.002|0.023|-0.008|
||(0.013)|(0.013)|(0.025)|(0.030)|
|T1 = T1 + L|.13|.69|.797|.954|
|T2 = T2 + L|.34|.569|.688|.0293|
|T3 = T3 + L|.938|.203|.955|.536|
|T1 = T2|.0153|.133|.305|.166|
|T2 = T3|.393|.0212|.741|.0461|
|T1 = T3|.122|.449|.26|.636|
|T1 + L = T2 + L|.073|.225|.185|.71|
|T2 + L = T3 + L|.105|.249|.975|.643|
|T1 + L = T3 + L|.728|.866|.0821|.946|
|N|2,200|2,327|2,138|2,706|
|Control mean|.03|.923|.093|.155|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; SRH = sexual and reproductive health; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

40
Table A8: Impact on economic outcomes

||Engaged in IGA<br>(last 6 months)|Reported<br>profts|Monthly<br>profts|Engaged in<br>non-Ag IGA<br>(last 6 months)|Number of<br>IGAs|Number of<br>own<br>initiative<br>IGAs|
|---|---|---|---|---|---|---|
|T1 (safe spaces)|0.093*|0.014|0.126|-0.036|0.137*|0.013|
||(0.053)|(0.056)|(0.546)|(0.038)|(0.079)|(0.055)|
|T1 + Leaders|0.044|0.041|0.347|-0.017|0.105|-0.016|
||(0.064)|(0.048)|(0.459)|(0.047)|(0.100)|(0.059)|
|T2 (safe spaces + IGA)|0.096*|0.109**|1.086**|0.013|0.230**|0.144**|
||(0.056)|(0.053)|(0.527)|(0.039)|(0.098)|(0.057)|
|T2 + Leaders|0.105*|0.113***|1.038**|0.034|0.229**|0.156***|
||(0.053)|(0.042)|(0.418)|(0.044)|(0.094)|(0.055)|
|T3 (safe spaces + husbands’ clubs)|0.139***|0.041|0.406|0.151***|0.210**|0.198***|
||(0.049)|(0.043)|(0.443)|(0.049)|(0.084)|(0.065)|
|T3 + Leaders|0.189***|0.085|0.858|0.050|0.257***|0.178**|
||(0.061)|(0.057)|(0.570)|(0.050)|(0.081)|(0.070)|
|T4 (control spillover)|0.050|0.013|0.121|0.029|0.097|0.041|
||(0.047)|(0.032)|(0.331)|(0.034)|(0.074)|(0.051)|
|T1 = T1 + L|.468|.69|.739|.718|.758|.654|
|T2 = T2 + L|.881|.951|.938|.684|.996|.846|
|T3 = T3 + L|.421|.51|.509|.124|.623|.811|
|T1 = T2|.964|.19|.178|.308|.38|.0562|
|T2 = T3|.444|.285|.289|.0178|.856|.447|
|T1 = T3|.419|.674|.661|.00129|.448|.0177|
|T1 + L = T2 + L|.393|.225|.222|.387|.296|.0101|
|T2 + L = T3 + L|.203|.681|.785|.797|.785|.781|
|T1 + L = T3 + L|.0575|.541|.465|.308|.175|.0164|
|N|3,003|3,003|3,003|3,003|3,003|3,003|
|Control mean|.529|.235|2.38|.266|.652|.371|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; nonag = nonagricultural. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.
# **Results on Mechanisms and Secondary Outcomes**

## Table A9: Impact on SRH knowledge (15yo+)

||Knows<br>modern contraception<br>method|Heard of<br>HIV|Knows<br>condom<br>reduces HIV<br>risks|Maternal<br>care<br>attitude|Knows<br>modern<br>MH products|Declares<br>advantages<br>of modern<br>MH producs|Agrees that<br>girls should<br>attend school<br>on their period|
|---|---|---|---|---|---|---|---|
|T1 (safe spaces)|0.089**|0.079|0.090|0.225***|0.100|0.074|0.056|
||(0.042)|(0.053)|(0.056)|(0.085)|(0.061)|(0.074)|(0.037)|
|T1 + Leaders|0.046|0.088*|0.060|0.149*|0.067|0.097|-0.010|
||(0.042)|(0.045)|(0.064)|(0.088)|(0.053)|(0.066)|(0.048)|
|T2 (safe spaces + IGA)|0.061|0.069|0.163***|0.287***|0.157***|0.158***|0.027|
||(0.037)|(0.043)|(0.057)|(0.088)|(0.049)|(0.049)|(0.034)|
|T2 + Leaders|0.054|0.082*|0.078|0.089|0.035|0.084|-0.048|
||(0.042)|(0.044)|(0.053)|(0.078)|(0.058)|(0.052)|(0.050)|
|T3 (safe spaces + husbands’ clubs)|0.117***|0.094**|0.064|0.239***|0.160***|0.169***|0.095***|
||(0.036)|(0.044)|(0.057)|(0.082)|(0.046)|(0.043)|(0.032)|
|T3 + Leaders|0.077*|0.054|0.117|0.109|0.051|0.007|0.092**|
||(0.040)|(0.062)|(0.074)|(0.100)|(0.068)|(0.074)|(0.044)|
|T4 (control spillover)|0.015|0.002|0.018|-0.053|0.041|-0.002|0.021|
||(0.037)|(0.045)|(0.054)|(0.083)|(0.052)|(0.049)|(0.030)|
|T1 = T1 + L|.356|.879|.679|.393|.623|.782|.222|
|T2 = T2 + L|.859|.792|.195|.0282|.0469|.158|.158|
|T3 = T3 + L|.273|.519|.519|.203|.107|.021|.943|
|T1 = T2|.511|.855|.286|.513|.374|.25|.491|
|T2 = T3|.115|.598|.161|.609|.96|.805|.0679|
|T1 = T3|.49|.784|.694|.876|.333|.177|.334|
|T1 + L = T2 + L|.869|.897|.8|.494|.607|.849|.539|
|T2 + L = T3 + L|.587|.654|.618|.838|.831|.302|.0206|
|T1 + L = T3 + L|.479|.592|.513|.711|.824|.295|.0782|
|N|2,953|2,931|2,094|2,931|2,871|2,871|2,995|
|Control mean|.831|.785|.529|3.35|.639|.463|.811|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

42
Table A10: Impact on gender attitudes

||Gender<br>equality<br>index|Gender<br>equality<br>(conformity<br>to roles)|Ideal age<br>for a woman<br>to marry|Ideal age<br>for a man<br>to marry|Gap of<br>ideal age<br>to marry<br>women-men|Expected<br>education for<br>ado’s girls|Gap of<br>ideal<br>education<br>girls-boys|
|---|---|---|---|---|---|---|---|
|T1 (safe spaces)|0.269|0.260|-0.054|-0.982|0.697*|0.030|0.011|
||(0.238)|(0.246)|(0.487)|(0.609)|(0.407)|(0.085)|(0.073)|
|T1 + Leaders|0.006|-0.134|0.487|0.242|-0.168|0.029|0.057|
||(0.174)|(0.194)|(0.538)|(0.664)|(0.406)|(0.066)|(0.072)|
|T2 (safe spaces + IGA)|0.045|0.106|0.774**|0.574|-0.446|0.018|0.139**|
||(0.138)|(0.162)|(0.350)|(0.499)|(0.380)|(0.073)|(0.060)|
|T2 + Leaders|0.111|0.146|0.441|-0.169|0.500|-0.072|-0.003|
||(0.169)|(0.191)|(0.353)|(0.532)|(0.392)|(0.096)|(0.065)|
|T3 (safe spaces + husbands’ clubs)|0.313*|0.389**|0.365|-0.027|0.108|0.170**|-0.026|
||(0.174)|(0.170)|(0.354)|(0.546)|(0.486)|(0.071)|(0.051)|
|T3 + Leaders|0.179|0.163|1.353**|0.939|0.055|0.150*|-0.023|
||(0.194)|(0.176)|(0.525)|(0.640)|(0.319)|(0.077)|(0.052)|
|T4 (control spillover)|-0.042|0.063|0.390|0.057|0.067|0.021|0.048|
||(0.152)|(0.166)|(0.431)|(0.551)|(0.350)|(0.068)|(0.046)|
|T1 = T1 + L|.291|.135|.363|.0633|.0658|.991|.618|
|T2 = T2 + L|.689|.844|.279|.0855|.0287|.388|.054|
|T3 = T3 + L|.536|.236|.0474|.108|.911|.806|.956|
|T1 = T2|.329|.538|.0527|.00281|.0163|.895|.111|
|T2 = T3|.112|.112|.195|.176|.272|.0549|.00914|
|T1 = T3|.863|.618|.325|.0836|.279|.127|.613|
|T1 + L = T2 + L|.582|.208|.925|.484|.126|.294|.479|
|T2 + L = T3 + L|.745|.932|.0654|.0583|.251|.037|.76|
|T1 + L = T3 + L|.416|.155|.184|.329|.586|.119|.283|
|N|2,990|2,990|2,995|2,995|1,734|2,940|2,973|
|Control mean|1.03|1.22|18|22.9|-4.91|3.19|-1.04|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

43
Table A11: Impact on aspirations

||Desired number<br>children|Occupation desired<br>High or<br>intermediate|Desired<br>remuneration|
|---|---|---|---|
|T1 (safe spaces)|0.124|-0.079|-0.250|
||(0.131)|(0.060)|(0.387)|
|T1 + Leaders|-0.139|-0.144*|-0.260|
||(0.145)|(0.087)|(0.186)|
|T2 (safe spaces + IGA)|-0.317**|0.030|-0.097|
||(0.141)|(0.047)|(0.199)|
|T2 + Leaders|-0.137|-0.090|-0.040|
||(0.126)|(0.061)|(0.165)|
|T3 (safe spaces + husbands’ clubs)|-0.220*|-0.104|0.202|
||(0.124)|(0.066)|(0.159)|
|T3 + Leaders|-0.291*|-0.066|-0.200|
||(0.166)|(0.082)|(0.298)|
|T4 (control spillover)|0.030|-0.030|0.008|
||(0.109)|(0.050)|(0.203)|
|T1 = T1 + L|.118|.497|.981|
|T2 = T2 + L|.264|.0645|.792|
|T3 = T3 + L|.697|.694|.194|
|T1 = T2|.00916|.104|.717|
|T2 = T3|.548|.0554|.151|
|T1 = T3|.0288|.748|.257|
|T1 + L = T2 + L|.991|.57|.286|
|T2 + L = T3 + L|.39|.795|.604|
|T1 + L = T3 + L|.446|.46|.85|
|N|2,946|2,965|2,993|
|Control mean|5.51|.812|11.6|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

44
Table A12: Impact on SES

||Self-<br>Esteem|General-<br>Efcacy|Self-<br>awarness|Problem<br>solving|Perseverance|Infuence|Creativity|
|---|---|---|---|---|---|---|---|
|T1 (safe spaces)|-0.003|-0.449|0.431|-0.285|-0.253|-0.282|-0.089|
||(0.243)|(0.583)|(0.532)|(0.857)|(0.358)|(0.488)|(0.280)|
|T1 + Leaders|0.621**|1.477**|1.440**|1.743**|0.729*|0.567|0.550*|
||(0.257)|(0.609)|(0.587)|(0.850)|(0.406)|(0.416)|(0.295)|
|T2 (safe spaces + IGA)|0.697***|1.033*|1.290***|1.723**|0.374|1.031**|0.668***|
||(0.230)|(0.619)|(0.476)|(0.743)|(0.327)|(0.429)|(0.211)|
|T2 + Leaders|0.687**|2.272***|1.000**|2.209***|0.942***|1.277***|0.613**|
||(0.300)|(0.587)|(0.492)|(0.734)|(0.347)|(0.489)|(0.262)|
|T3 (safe spaces + husbands’ clubs)|0.451**|0.975*|1.020**|1.307*|0.425|0.689|0.523**|
||(0.220)|(0.547)|(0.447)|(0.770)|(0.289)|(0.422)|(0.230)|
|T3 + Leaders|1.141***|2.419***|1.869***|3.218***|1.493***|1.498***|1.067***|
||(0.260)|(0.631)|(0.479)|(0.896)|(0.393)|(0.438)|(0.295)|
|T4 (control spillover)|0.290|0.658|0.601|0.834|0.416|0.270|0.200|
||(0.226)|(0.533)|(0.387)|(0.770)|(0.329)|(0.394)|(0.251)|
|T1 = T1 + L|.026|.00551|.164|.038|.0403|.0936|.0604|
|T2 = T2 + L|.974|.0806|.62|.541|.157|.647|.83|
|T3 = T3 + L|.0122|.037|.138|.047|.01|.097|.0721|
|T1 = T2|.00998|.0433|.173|.0307|.14|.0177|.00688|
|T2 = T3|.315|.932|.631|.615|.886|.47|.526|
|T1 = T3|.0896|.0353|.345|.095|.0861|.0666|.0377|
|T1 + L = T2 + L|.844|.26|.532|.603|.646|.18|.847|
|T2 + L = T3 + L|.178|.836|.145|.27|.222|.681|.16|
|T1 + L = T3 + L|.0833|.213|.528|.152|.126|.0535|.148|
|N|2,995|2,995|3,003|3,003|3,003|3,003|2,979|
|Control mean|7.06|16.6|20.3|24.3|11.7|12.3|7.41|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

45
Table A13: Impact on marriage and pregnancy

||Currently<br>Pregnant|Ever<br>Pregnant|Ever<br>Married or Cohabited|
|---|---|---|---|
|T1 (safe spaces)|-0.004|0.018|-0.003|
||(0.018)|(0.032)|(0.039)|
|T1 + Leaders|-0.001|-0.017|0.018|
||(0.019)|(0.041)|(0.027)|
|T2 (safe spaces + IGA)|0.030|0.022|-0.029|
||(0.027)|(0.024)|(0.026)|
|T2 + Leaders|-0.010|0.054***|-0.014|
||(0.025)|(0.020)|(0.029)|
|T3 (safe spaces + husbands’ clubs)|-0.001|0.028|0.001|
||(0.020)|(0.027)|(0.028)|
|T3 + Leaders|-0.039*|-0.005|-0.046*|
||(0.020)|(0.030)|(0.027)|
|T4 (control spillover)|0.001|-0.002|-0.005|
||(0.014)|(0.025)|(0.029)|
|T1 = T1 + L|.92|.436|.59|
|T2 = T2 + L|.232|.191|.62|
|T3 = T3 + L|.124|.347|.122|
|T1 = T2|.254|.898|.518|
|T2 = T3|.313|.85|.308|
|T1 = T3|.925|.797|.904|
|T1 + L = T2 + L|.751|.083|.312|
|T2 + L = T3 + L|.307|.0409|.311|
|T1 + L = T3 + L|.127|.803|.0326|
|N|2,846|2,900|2,991|
|Control mean|.109|.799|.803|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

46
Table A14: Impact on finance

|||Took a<br>loan|Saved<br>money|
|---|---|---|---|
|T1|(safe spaces)|-0.014|0.051|
|||(0.030)|(0.063)|
|T1|+ Leaders|-0.032|0.089*|
|||(0.024)|(0.052)|
|T2|(safe spaces + IGA)|-0.025|0.097|
|||(0.024)|(0.066)|
|T2|+ Leaders|-0.021|0.166***|
|||(0.026)|(0.048)|
|T3|(safe spaces + husbands’ clubs)|-0.040|0.050|
|||(0.027)|(0.064)|
|T3|+ Leaders|0.010|0.133**|
|||(0.031)|(0.056)|
|T4|(control spillover)|-0.032*|-0.034|
|||(0.019)|(0.041)|
|T1|= T1 + L|.567|.575|
|T2|= T2 + L|.889|.315|
|T3|= T3 + L|.148|.251|
|T1|= T2|.741|.562|
|T2|= T3|.599|.56|
|T1|= T3|.447|.989|
|T1|+ L = T2 + L|.692|.176|
|T2|+ L = T3 + L|.363|.593|
|T1|+ L = T3 + L|.203|.495|
|N||2,995|2,995|
|Co|ntrol mean|.097|.346|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

47
Table A15: Impact on violence (15yo+)

|||At least one<br>Emotional<br>violence|At least one<br>Physical<br>violence|At least one<br>Sexual<br>violence|
|---|---|---|---|---|
|T1|(safe spaces)|-0.001|-0.025|0.002|
|||(0.068)|(0.016)|(0.023)|
|T1|+ Leaders|0.028|-0.021|0.020|
|||(0.065)|(0.016)|(0.027)|
|T2|(safe spaces + IGA)|-0.003|0.007|0.001|
|||(0.045)|(0.020)|(0.019)|
|T2|+ Leaders|-0.032|-0.026*|0.003|
|||(0.040)|(0.014)|(0.021)|
|T3|(safe spaces + husbands’ clubs)|-0.046|-0.019|-0.023|
|||(0.055)|(0.016)|(0.017)|
|T3|+ Leaders|0.008|-0.009|-0.004|
|||(0.065)|(0.017)|(0.018)|
|T4|(control spillover)|-0.023|-0.008|-0.003|
|||(0.045)|(0.016)|(0.021)|
|T1|= T1 + L|.737|.797|.546|
|T2|= T2 + L|.489|.0734|.947|
|T3|= T3 + L|.467|.59|.263|
|T1|= T2|.968|.122|.987|
|T2|= T3|.466|.199|.18|
|T1|= T3|.538|.727|.266|
|T1|+ L = T2 + L|.324|.654|.519|
|T2|+ L = T3 + L|.513|.308|.751|
|T1|+ L = T3 + L|.803|.516|.37|
|N||2,924|2,931|2,931|
|Co|ntrol mean|.231|.057|.046|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

48
Table A16: Impact on mental health and nutrition

||Self-reported<br>happiness|Mental Health<br>Index|Women’s Dietay<br>Diversity score<br>(0-1)|Minimum Dietary<br>Diversity<br>(yes=1)|
|---|---|---|---|---|
|T1 (safe spaces)|0.096***|0.490*|-0.059**|-0.114**|
||(0.036)|(0.287)|(0.024)|(0.049)|
|T1 + Leaders|-0.023|0.149|-0.035*|-0.066|
||(0.043)|(0.285)|(0.020)|(0.054)|
|T2 (safe spaces + IGA)|0.072*|0.611**|-0.048**|-0.130**|
||(0.037)|(0.271)|(0.023)|(0.051)|
|T2 + Leaders|0.071|-0.490*|-0.019|-0.066|
||(0.047)|(0.288)|(0.021)|(0.058)|
|T3 (safe spaces + husbands’ clubs)|0.042|0.160|-0.090***|-0.246***|
||(0.048)|(0.305)|(0.026)|(0.082)|
|T3 + Leaders|0.125***|0.249|0.000|-0.060|
||(0.044)|(0.301)|(0.019)|(0.053)|
|T4 (control spillover)|0.029|-0.037|-0.032*|-0.097**|
||(0.033)|(0.241)|(0.017)|(0.048)|
|T1 = T1 + L|.00947|.283|.388|.451|
|T2 = T2 + L|.99|.000985|.279|.337|
|T3 = T3 + L|.135|.809|.00091|.0343|
|T1 = T2|.536|.718|.679|.785|
|T2 = T3|.539|.184|.155|.188|
|T1 = T3|.298|.349|.312|.116|
|T1 + L = T2 + L|.0883|.06|.515|.993|
|T2 + L = T3 + L|.308|.0375|.405|.932|
|T1 + L = T3 + L|.00486|.771|.121|.923|
|N|3,003|3,003|2,995|3,003|
|Control mean|.696|13.4|.405|.811|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p- values of the difference tests between the treatments are in the second part of the table. All regressions control for the baseline value of the outcome variable, stratification fixed effects, and the following baseline variables: adolescent girl’s age, education level, an indicator for being engaged in an IGA, knowledge of modern contraception, household is rural, household head is female, and at least one household member has an agricultural activity. When the baseline value of the outcome variable is missing, it is imputed and a dummy indicating whether the variable is imputed or not is added as control.

49
# **Multiple Hypothesis Testing—Q-Values**

Table A17: Impact on primary outcomes—with false discovery rate adjusted q-values

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
||SR|H Behav|ior||IGA||
||Beta|pval|qval|Beta|pval|qval|
|T1 (safe spaces)|0.204|0.008|0.051|0.051|0.579|0.661|
|T1 + Leaders|0.136|0.146|0.247|0.023|0.836|0.805|
|T2 (safe spaces + IGA)|0.050|0.555|0.661|0.180|0.046|0.126|
|T2 + Leaders|-0.016|0.889|0.805|0.240|0.007|0.050|
|T3 (safe spaces + husbands’ clubs)|0.197|0.041|0.117|0.293|0.000|0.017|
|T3 + Leaders|0.141|0.049|0.127|0.271|0.022|0.082|
|T4 (Control Spillover)|0.078|0.245|0.354|0.074|0.293|0.393|

_Note:_ The coefficients and the p-values in this table (beta and pval) are obtained from the regressions in table 3 and they denote the impact of our treatments. The q-values (qval) are False Discovery Rate adjusted p-values and are estimated using the procedure described in Anderson 2008.

Table A18: Impact on mechanism outcomes—with false discovery rate adjusted q-values

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Know|ledge in|SRH|Gen|der attit|udes|As|piration|s||SES||
||Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|
|T1 (safe spaces)|0.308|0.012|0.060|0.209|0.022|0.082|-0.183|0.174|0.293|-0.023|0.842|0.805|
|T1 + Leaders|0.208|0.071|0.160|0.084|0.429|0.567|-0.161|0.182|0.300|0.246|0.031|0.101|
|T2 (safe spaces + IGA)|0.312|0.009|0.055|0.162|0.034|0.105|0.128|0.236|0.354|0.248|0.006|0.050|
|T2 + Leaders|0.183|0.119|0.217|0.070|0.494|0.610|-0.037|0.709|0.768|0.302|0.003|0.047|
|T3 (safe spaces + husbands’ clubs)|0.348|0.004|0.047|0.218|0.005|0.048|0.011|0.907|0.805|0.191|0.039|0.115|
|T3 + Leaders|0.225|0.127|0.224|0.203|0.004|0.047|-0.006|0.972|0.805|0.459|0.000|0.002|
|T4 (Control Spillover)|0.008|0.943|0.805|0.042|0.553|0.661|-0.029|0.744|0.786|0.120|0.205|0.332|

_Note:_ The coefficients and the p-values in this table (beta and pval) are obtained from the regressions in table 4 and they denote the impact of our treatments. The q-values (qval) are False Discovery Rate adjusted p-values and are estimated using the procedure described in Anderson 2008.
Table A19: Impact on secondary outcomes—with false discovery rate adjusted q-values

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|(13)|(14)|(15)|(16)|(17)|(18)|(19)|(20)|(21)|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Marriag|e and pr|egnancy|Viole|nce (15|yo+)|Decisio|n-makin|g (indiv)|Decisio|n-making|(couples)||Finance||N|utritio|n|Me|ntal heal|th|
|5|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|Beta|pval|qval|
|T1 (safe spaces)<br>1|-0.004|0.960|0.805|0.051|0.567|0.661|0.068|0.563|0.661|0.115|0.426|0.567|0.028|0.826|0.805|-0.400|0.015|0.071|0.277|0.004|0.047|
|T1 + Leaders|-0.006|0.939|0.805|-0.028|0.808|0.805|0.250|0.064|0.152|0.408|0.005|0.049|0.030|0.762|0.786|-0.235|0.105|0.209|-0.003|0.975|0.805|
|T2 (safe spaces + IGA)|0.005|0.931|0.805|-0.014|0.861|0.805|0.158|0.214|0.342|0.168|0.237|0.354|0.055|0.566|0.661|-0.354|0.024|0.086|0.267|0.011|0.060|
|T2 + Leaders|-0.054|0.339|0.458|0.085|0.250|0.354|0.002|0.989|0.805|0.205|0.175|0.293|0.148|0.109|0.209|-0.153|0.321|0.434|-0.002|0.984|0.805|
|T3 (safe spaces + husbands’ clubs)|-0.035|0.597|0.678|0.141|0.117|0.217|0.200|0.051|0.127|0.294|0.021|0.082|-0.046|0.698|0.768|-0.682|0.001|0.028|0.109|0.417|0.567|
|T3 + Leaders|0.055|0.351|0.461|0.019|0.834|0.805|0.396|0.002|0.047|0.406|0.016|0.073|0.186|0.108|0.209|-0.051|0.710|0.768|0.269|0.019|0.081|
|T4 (Control Spillover)|0.007|0.908|0.805|0.049|0.574|0.661|0.081|0.443|0.567|0.223|0.067|0.155|-0.125|0.089|0.181|-0.247|0.051|0.127|0.039|0.673|0.751|

_Note:_ The coefficients and the p-values in this table (beta and pval) are obtained from the regressions in table 6 and they denote the impact of our treatments. The q-values (qval) are False Discovery Rate adjusted p-values and are estimated using the procedure described in Anderson 2008.
# **LASSO Specification Tables**

Table A20: Impact on primary outcomes—with double-LASSO selected controls

|||(1)<br>SRH<br>behavior<br>(15yo+)|(2)<br>Economic<br>outcomes|
|---|---|---|---|
|T1|(safe spaces)|0.216***|0.119|
|||(0.080)|(0.104)|
|T1|+ Leaders|0.162*|0.062|
|||(0.091)|(0.137)|
|T2|(safe spaces + IGA)|0.017|0.155*|
|||(0.077)|(0.087)|
|T2|+ Leaders|-0.012|0.276***|
|||(0.113)|(0.088)|
|T3|(safe spaces + husbands’ clubs)|0.203**|0.333***|
|||(0.095)|(0.083)|
|T3|+ Leaders|0.117|0.251**|
|||(0.076)|(0.126)|
|T4|(control spillover)|0.092|0.058|
|||(0.071)|(0.076)|
|T1|= T1 + L|.582|.701|
|T2|= T2 + L|.806|.201|
|T3|= T3 + L|.384|.523|
|T1|= T2|.0206|.741|
|T2|= T3|.0649|.0518|
|T1|= T3|.894|.0466|
|T1|+ L = T2 + L|.17|.124|
|T2|+ L = T3 + L|.272|.847|
|T1|+ L = T3 + L|.64|.26|
|N||2,855|3,003|
|Co|ntrol mean|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; SRH = sexual and reproductive health; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for stratification fixed effects and the double-LASSOselected variables within a set of baseline values that include the outcome variable at baseline, the adolescent individual characteristics and her household’s. When the baseline value is missing, it is imputed and if it is selected by the double-LASSO procedure a dummy indicating whether the variable is imputed or not is added as control.

52
Table A21: Impact on mechanism outcomes—with double-LASSO selected controls

||(1)<br>SRH<br>knowledge<br>(15 yo+)|(2)<br>Gender<br>attitudes|(3)<br>Aspirations|(4)<br>SES|
|---|---|---|---|---|
|T1 (safe spaces)|0.265**|0.242***|-0.119|-0.011|
||(0.118)|(0.093)|(0.101)|(0.111)|
|T1 + Leaders|0.155|0.087|-0.140|0.259**|
||(0.104)|(0.115)|(0.123)|(0.113)|
|T2 (safe spaces + IGA)|0.257**|0.172**|0.049|0.226**|
||(0.110)|(0.077)|(0.105)|(0.094)|
|T2 + Leaders|0.058|0.063|-0.078|0.301***|
||(0.119)|(0.104)|(0.092)|(0.098)|
|T3 (safe spaces + husbands’ clubs)|0.433***<br>(0.098)|0.206***<br>(0.077)|-0.030<br>(0.113)|0.181**<br>(0.092)|
|T3 + Leaders|0.176|0.155**|0.014|0.443***|
||(0.158)|(0.077)|(0.149)|(0.108)|
|T4 (control spillover)|-0.015|0.053|-0.041|0.108|
||(0.115)|(0.074)|(0.095)|(0.098)|
|T1 = T1 + L|.308|.208|.882|.0433|
|T2 = T2 + L|.0925|.299|.287|.486|
|T3 = T3 + L|.0806|.509|.796|.0222|
|T1 = T2|.947|.448|.179|.0481|
|T2 = T3|.0697|.649|.557|.659|
|T1 = T3|.0973|.704|.5|.0981|
|T1 + L = T2 + L|.388|.857|.647|.733|
|T2 + L = T3 + L|.465|.378|.555|.235|
|T1 + L = T3 + L|.891|.549|.381|.162|
|N|3,002|3,003|2,995|3,003|
|Control mean|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; SES = socio-emotional skills; SRH= sexual and reproductive health; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for stratification fixed effects and the double-LASSO-selected variables within a set of baseline values that include the outcome variable at baseline, the adolescent individual characteristics and her household’s. When the baseline value is missing, it is imputed and if it is selected by the double-LASSO procedure a dummy indicating whether the variable is imputed or not is added as control.

53
Table A22: Impact on secondary outcomes—with double-LASSO selected controls

||(1)<br>Marriage and<br>pregnancy|(2)<br>Violence<br>(15 yo+)|(3)<br>Decision-<br>making<br>(individual)|(4)<br>Decision-<br>making<br>(couples)|(5)<br>Finance|(6)<br>Nutrition|(7)<br>Mental<br>health|
|---|---|---|---|---|---|---|---|
|T1 (safe spaces)|-0.044|0.057|0.045|0.094|0.007|-0.449***|0.241***|
||(0.059)|(0.092)|(0.118)|(0.144)|(0.119)|(0.158)|(0.090)|
|T1 + Leaders|-0.011|-0.040|0.247**|0.378***|0.041|-0.226|-0.006|
||(0.069)|(0.112)|(0.117)|(0.123)|(0.103)|(0.144)|(0.115)|
|T2 (safe spaces + IGA)|-0.091*|-0.014|0.122|0.131|0.067|-0.389**|0.243**|
||(0.055)|(0.083)|(0.122)|(0.142)|(0.087)|(0.154)|(0.109)|
|T2 + Leaders|-0.005|0.082|0.005|0.160|0.161*|-0.171|-0.032|
||(0.068)|(0.074)|(0.117)|(0.145)|(0.090)|(0.151)|(0.114)|
|T3 (safe spaces + husbands’ clubs)|-0.007|0.129|0.207**|0.278**|-0.019|-0.679***|0.077|
||(0.053)|(0.090)|(0.102)|(0.130)|(0.115)|(0.202)|(0.133)|
|T3 + Leaders|0.043|0.028|0.321***|0.276|0.133|-0.094|0.244**|
||(0.060)|(0.092)|(0.123)|(0.171)|(0.122)|(0.125)|(0.108)|
|T4 (control spillover)|0.014|0.061|0.094|0.198|-0.108|-0.218*|0.082|
||(0.056)|(0.090)|(0.110)|(0.126)|(0.076)|(0.117)|(0.104)|
|T1 = T1 + L|.688|.414|.105|.0399|.803|.22|.032|
|T2 = T2 + L|.281|.22|.418|.868|.339|.23|.0343|
|T3 = T3 + L|.481|.326|.393|.992|.308|.00454|.25|
|T1 = T2|.524|.458|.592|.831|.63|.752|.988|
|T2 = T3|.212|.131|.528|.365|.481|.2|.254|
|T1 = T3|.606|.476|.2|.256|.859|.303|.213|
|T1 + L = T2 + L|.946|.245|.077|.163|.289|.756|.846|
|T2 + L = T3 + L|.559|.544|.0274|.548|.83|.631|.0319|
|T1 + L = T3 + L|.52|.575|.595|.544|.515|.389|.0533|
|N|2,995|2,931|2,919|1,734|3,003|3,003|3,003|
|Control mean|0|0|0|0|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. IGA = income-generating activity; yo = years old. The table presents estimated impacts of our 6 interventions’ combinations and the control spillover relative to the pure control group. The p-values of the difference tests between the treatments are in the second part of the table. All regressions control for stratification fixed effects and the double-LASSO-selected variables within a set of baseline values that include the outcome variable at baseline, the adolescent individual characteristics and her household’s. When the baseline value is missing, it is imputed and if it is selected by the double-LASSO procedure a dummy indicating whether the variable is imputed or not is added as control.

54
# **Attrition Robustness—Bounds**

Table A23: Robustness of impact on SRH behavior index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|0.20***<br>(0.08)|0.22***<br>(0.08)|0.13*<br>(0.07)|0.19**<br>(0.08)|0.20***<br>(0.08)|0.20***<br>(0.08)|0.21***<br>(0.08)|
|T1+Leaders|0.13|0.29***|-0.13*|0.04|0.14|0.14|0.14|
||(0.09)|(0.09)|(0.08)|(0.09)|(0.09)|(0.09)|(0.09)|
|T2 (Safe Spaces + IGA)|0.05|0.22***|-0.13|0.01|0.05|0.05|0.04|
||(0.08)|(0.06)|(0.09)|(0.09)|(0.08)|(0.08)|(0.08)|
|T2+Leaders|-0.02|0.29***|-0.31***|-0.09|-0.02|-0.01|-0.02|
||(0.11)|(0.08)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|
|T3 (Safe Spaces + Husbands Clubs)|0.20**|0.39***|-0.04|0.07|0.16*|0.20**|0.20**|
||(0.10)|(0.08)|(0.09)|(0.09)|(0.09)|(0.09)|(0.10)|
|T3+Leaders|0.14**|0.20***|0.03|0.13*|0.14**|0.14**|0.15**|
||(0.07)|(0.07)|(0.06)|(0.07)|(0.07)|(0.07)|(0.07)|
|T4 (control spillover)|0.08|0.09|0.07|0.07|0.08|0.08|0.08|
||(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|
|N|2855|2854|2854|2856|2856|2856|2855|
|Control Mean|0|0|0|.003|0|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

55
Table A24: Robustness of impact on economic outcomes index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimming|treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|0.05|0.07|0.01|0.04|0.04|0.05|0.06|
||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T1+Leaders|0.02|0.15|-0.20**|-0.05|-0.01|0.03|0.03|
||(0.11)|(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2 (Safe Spaces + IGA)|0.18**|0.25***|0.05|0.13|0.15*|0.19**|0.18*|
||(0.09)|(0.09)|(0.10)|(0.09)|(0.09)|(0.09)|(0.09)|
|T2+Leaders|0.24***|0.41***|0.02|0.16*|0.20**|0.23***|0.24***|
||(0.09)|(0.10)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T3 (Safe Spaces + Husbands Clubs)|0.29***<br>(0.08)|0.47***<br>(0.09)|0.09<br>(0.08)|0.19**<br>(0.08)|0.23***<br>(0.08)|0.28***<br>(0.08)|0.30***<br>(0.08)|
|T3+Leaders|0.27**|0.31***|0.21*|0.25**|0.26**|0.27**|0.27**|
||(0.12)|(0.11)|(0.11)|(0.12)|(0.12)|(0.12)|(0.12)|
|T4 (control spillover)|0.07|0.08|0.07|0.07|0.07|0.07|0.07|
||(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|
|N|3003|3002|3002|3004|3004|3004|3003|
|Control Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

56
Table A25: Robustness of impact on SRH knowledge index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimming|treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.31**|0.36***|0.30**|0.30**|0.30**|0.30**|0.31***|
|||(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T1|+Leaders|0.21*|0.45***|0.10|0.17|0.17|0.19*|0.21*|
|||(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|(0.12)|
|T2|(Safe Spaces + IGA)|0.31***|0.48***|0.27**|0.29**|0.29**|0.29**|0.30**|
|||(0.12)|(0.10)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T2|+Leaders|0.18|0.45***|0.10|0.14|0.14|0.16|0.18|
|||(0.12)|(0.09)|(0.12)|(0.11)|(0.11)|(0.11)|(0.12)|
|T3|(Safe Spaces + Husbands Clubs)|0.35***<br>(0.12)|0.56***<br>(0.11)|0.26**<br>(0.11)|0.30***<br>(0.11)|0.30***<br>(0.11)|0.32***<br>(0.11)|0.34***<br>(0.12)|
|T3|+Leaders|0.23<br>(0.15)|0.31**<br>(0.14)|0.20<br>(0.15)|0.22<br>(0.15)|0.22<br>(0.15)|0.22<br>(0.15)|0.23<br>(0.14)|
|T4|(control spillover)|0.01|0.01|0.01|0.01|0.01|0.01|0.01|
|||(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|N||2953|2952|2952|2954|2954|2954|2953|
|Con|trol Mean|0|0|0|.001|.001|.001|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

57
Table A26: Robustness of impact on Gender attitudes index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimming|treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.21**<br>(0.09)|0.26***<br>(0.09)|0.15*<br>(0.09)|0.20**<br>(0.09)|0.20**<br>(0.09)|0.21**<br>(0.09)|0.21**<br>(0.09)|
|T1|+Leaders|0.08<br>(0.11)|0.28***<br>(0.08)|-0.08<br>(0.10)|0.04<br>(0.10)|0.06<br>(0.10)|0.08<br>(0.10)|0.08<br>(0.11)|
|T2|(Safe Spaces + IGA)|0.16**<br>(0.08)|0.29***<br>(0.07)|0.05<br>(0.08)|0.12*<br>(0.08)|0.14*<br>(0.08)|0.16**<br>(0.07)|0.16**<br>(0.08)|
|T2|+Leaders|0.07<br>(0.10)|0.35***<br>(0.08)|-0.12<br>(0.09)|0.02<br>(0.10)|0.04<br>(0.10)|0.06<br>(0.10)|0.08<br>(0.10)|
|T3|(Safe Spaces + Husbands Clubs)|0.22***<br>(0.08)|0.42***<br>(0.08)|0.04<br>(0.07)|0.15*<br>(0.08)|0.18**<br>(0.08)|0.20***<br>(0.07)|0.23***<br>(0.08)|
|T3|+Leaders|0.20***<br>(0.07)|0.29***<br>(0.07)|0.15**<br>(0.07)|0.19***<br>(0.07)|0.20***<br>(0.07)|0.20***<br>(0.07)|0.21***<br>(0.07)|
|T4|(control spillover)|0.04<br>(0.07)|0.05<br>(0.07)|0.04<br>(0.07)|0.04<br>(0.07)|0.04<br>(0.07)|0.04<br>(0.07)|0.05<br>(0.07)|
|N||3003|3002|3002|3004|3004|3004|3003|
|Con|trol Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

58
Table A27: Robustness of impact on Aspirations index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|-0.18|-0.11|-0.22*|-0.19|-0.19|-0.18|-0.18|
||(0.13)|(0.11)|(0.13)|(0.13)|(0.13)|(0.13)|(0.13)|
|T1+Leaders|-0.16|0.09|-0.32***|-0.20*|-0.18|-0.16|-0.16|
||(0.12)|(0.09)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T2 (Safe Spaces + IGA)|0.13|0.29***|0.04|0.10|0.11|0.12|0.12|
||(0.11)|(0.09)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2+Leaders|-0.04|0.23***|-0.20*|-0.09|-0.07|-0.04|-0.04|
||(0.10)|(0.08)|(0.11)|(0.10)|(0.10)|(0.10)|(0.10)|
|T3 (Safe Spaces + Husbands Clubs)|0.01|0.23**|-0.14|-0.06|-0.02|-0.00|0.02|
||(0.10)|(0.10)|(0.09)|(0.09)|(0.09)|(0.10)|(0.10)|
|T3+Leaders|-0.00|0.10|-0.06|-0.02|-0.01|-0.01|-0.01|
||(0.16)|(0.11)|(0.15)|(0.16)|(0.16)|(0.16)|(0.16)|
|T4 (control spillover)|-0.03|-0.02|-0.03|-0.03|-0.03|-0.03|-0.03|
||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|N|2991|2990|2990|2992|2992|2992|2991|
|Control Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

59
Table A28: Robustness of impact on SES index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|-0.02|0.03|-0.06|-0.03|-0.03|-0.02|-0.02|
|||(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.12)|
|T1|+Leaders|0.25**|0.49***|0.08|0.19*|0.22*|0.24**|0.25**|
|||(0.11)|(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2|(Safe Spaces + IGA)|0.25***<br>(0.09)|0.40***<br>(0.08)|0.15*<br>(0.09)|0.21**<br>(0.09)|0.23**<br>(0.09)|0.24***<br>(0.09)|0.26***<br>(0.09)|
|T2|+Leaders|0.30***<br>(0.10)|0.53***<br>(0.09)|0.13<br>(0.10)|0.24**<br>(0.10)|0.26***<br>(0.10)|0.28***<br>(0.10)|0.30***<br>(0.10)|
|T3|(Safe Spaces + Husbands Clubs)|0.19**<br>(0.09)|0.38***<br>(0.08)|0.03<br>(0.09)|0.11<br>(0.09)|0.15*<br>(0.09)|0.18**<br>(0.09)|0.20**<br>(0.09)|
|T3|+Leaders|0.46***<br>(0.10)|0.56***<br>(0.10)|0.40***<br>(0.11)|0.44***<br>(0.10)|0.45***<br>(0.10)|0.45***<br>(0.10)|0.46***<br>(0.10)|
|T4|(control spillover)|0.12|0.13|0.12|0.12|0.12|0.12|0.12|
|||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|N||3003|3002|3002|3004|3004|3004|3003|
|Con|trol Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

60
Table A29: Robustness of impact on marriage and pregnancy index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|-0.01|0.00|-0.04|-0.02|-0.01|0.00|-0.01|
||(0.08)|(0.08)|(0.09)|(0.08)|(0.08)|(0.08)|(0.08)|
|T1+Leaders|-0.01|0.07|-0.19***|-0.08|-0.03|0.02|-0.01|
||(0.08)|(0.08)|(0.06)|(0.07)|(0.08)|(0.08)|(0.08)|
|T2 (Safe Spaces + IGA)|0.00|0.04|-0.12**|-0.05|0.02|0.02|0.00|
||(0.06)|(0.06)|(0.05)|(0.06)|(0.06)|(0.06)|(0.06)|
|T2+Leaders|-0.05|0.03|-0.28***|-0.13**|-0.07|-0.01|-0.06|
||(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|
|T3 (Safe Spaces + Husbands Clubs)|-0.03|0.02|-0.23***|-0.14**|-0.06|0.01|-0.04|
||(0.07)|(0.07)|(0.06)|(0.07)|(0.07)|(0.06)|(0.07)|
|T3+Leaders|0.06|0.08|0.01|0.04|0.05|0.07|0.06|
||(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|
|T4 (control spillover)|0.01|0.01|0.01|0.00|0.01|0.01|-0.00|
||(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.06)|(0.07)|
|N|2995|2994|2994|2996|2996|2996|2995|
|Control Mean|0|0|0|.003|.001|-.001|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

61
Table A30: Robustness of impact on violence index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimming|treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.05|0.13|0.04|0.05|0.05|0.05|0.04|
|||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T1|+Leaders|-0.03|0.28***|-0.10|-0.05|-0.05|-0.05|-0.03|
|||(0.11)|(0.08)|(0.12)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2|(Safe Spaces + IGA)|-0.02|0.22***|-0.05|-0.03|-0.03|-0.03|-0.02|
|||(0.08)|(0.07)|(0.08)|(0.08)|(0.08)|(0.08)|(0.08)|
|T2|+Leaders|0.08|0.36***|0.03|0.06|0.06|0.06|0.08|
|||(0.07)|(0.06)|(0.08)|(0.07)|(0.07)|(0.07)|(0.07)|
|T3|(Safe Spaces + Husbands Clubs)|0.14<br>(0.09)|0.40***<br>(0.06)|0.09<br>(0.10)|0.11<br>(0.09)|0.11<br>(0.09)|0.11<br>(0.09)|0.14<br>(0.09)|
|T3|+Leaders|0.02|0.14*|0.00|0.01|0.01|0.01|0.01|
|||(0.09)|(0.08)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T4|(control spillover)|0.05|0.06|0.05|0.05|0.05|0.05|0.04|
|||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|N||2931|2930|2930|2932|2932|2932|2931|
|Con|trol Mean|0|0|0|.001|.001|.001|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

62
Table A31: Robustness of impact on decision-making index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.07|0.11|0.03|0.06|0.06|0.07|0.07|
|||(0.12)|(0.11)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|T1|+Leaders|0.25*|0.46***|0.05|0.18|0.21|0.24*|0.25*|
|||(0.13)|(0.15)|(0.13)|(0.13)|(0.13)|(0.13)|(0.13)|
|T2|(Safe Spaces + IGA)|0.16|0.28***|0.03|0.11|0.14|0.16|0.16|
|||(0.13)|(0.11)|(0.13)|(0.13)|(0.13)|(0.13)|(0.13)|
|T2|+Leaders|0.00|0.20*|-0.23**|-0.08|-0.04|0.01|0.00|
|||(0.11)|(0.12)|(0.10)|(0.11)|(0.11)|(0.11)|(0.12)|
|T3|(Safe Spaces + Husbands Clubs)|0.20*|0.39***|-0.01|0.09|0.15|0.20**|0.20**|
|||(0.10)|(0.10)|(0.11)|(0.10)|(0.10)|(0.10)|(0.10)|
|T3|+Leaders|0.40***<br>(0.13)|0.45***<br>(0.14)|0.34***<br>(0.12)|0.37***<br>(0.13)|0.38***<br>(0.13)|0.39***<br>(0.13)|0.40***<br>(0.13)|
|T4|(control spillover)|0.08|0.08|0.08|0.08|0.08|0.08|0.09|
|||(0.11)|(0.11)|(0.10)|(0.11)|(0.11)|(0.11)|(0.11)|
|N||2919|2918|2918|2920|2920|2920|2919|
|Con|trol Mean|0|0|0|.003|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

63
Table A32: Robustness of impact on decision-making (couple matters) index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimming|treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.11|0.19|0.02|0.08|0.10|0.10|0.12|
|||(0.14)|(0.15)|(0.13)|(0.14)|(0.14)|(0.14)|(0.14)|
|T1|+Leaders|0.41***|0.72***|0.09|0.28**|0.34**|0.38***|0.40***|
|||(0.15)|(0.14)|(0.12)|(0.14)|(0.14)|(0.14)|(0.15)|
|T2|(Safe Spaces + IGA)|0.17<br>(0.14)|0.39***<br>(0.12)|-0.07<br>(0.13)|0.09<br>(0.14)|0.13<br>(0.14)|0.17<br>(0.14)|0.17<br>(0.14)|
|T2|+Leaders|0.20|0.50***|-0.18|0.11|0.16|0.21|0.20|
|||(0.15)|(0.15)|(0.12)|(0.15)|(0.15)|(0.15)|(0.15)|
|T3|(Safe Spaces + Husbands Clubs)|0.30**<br>(0.13)|0.66***<br>(0.11)|-0.13<br>(0.12)|0.11<br>(0.13)|0.21<br>(0.12)|0.30**<br>(0.12)|0.30**<br>(0.13)|
|T3|+Leaders|0.41**|0.55***|0.26|0.36**|0.39**|0.41**|0.40**|
|||(0.17)|(0.20)|(0.16)|(0.17)|(0.17)|(0.17)|(0.17)|
|T4|(control spillover)|0.22*|0.23*|0.22*|0.22*|0.22*|0.22*|0.23*|
|||(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|(0.12)|
|N||1734|1733|1733|1735|1735|1735|1734|
|Con|trol Mean|0|0|0|.005|.002|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

64
Table A33: Robustness of impact on finance index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.03|0.04|-0.04|0.01|0.02|0.03|0.03|
|||(0.12)|(0.13)|(0.11)|(0.13)|(0.12)|(0.12)|(0.13)|
|T1|+Leaders|0.03|0.11|-0.17**|-0.04|0.01|0.05|0.03|
|||(0.10)|(0.10)|(0.08)|(0.10)|(0.10)|(0.10)|(0.10)|
|T2|(Safe Spaces + IGA)|0.05|0.10|-0.13|0.00|0.04|0.07|0.05|
|||(0.09)|(0.10)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|T2|+Leaders|0.15|0.26**|-0.09|0.06|0.12|0.12|0.14|
|||(0.09)|(0.10)|(0.07)|(0.09)|(0.09)|(0.09)|(0.09)|
|T3|(Safe Spaces + Husbands Clubs)|-0.05|0.04|-0.25***|-0.15|-0.08|-0.01|-0.04|
|||(0.12)|(0.12)|(0.08)|(0.12)|(0.12)|(0.12)|(0.12)|
|T3|+Leaders|0.19|0.21*|0.08|0.15|0.18|0.19*|0.19*|
|||(0.12)|(0.12)|(0.09)|(0.12)|(0.11)|(0.12)|(0.11)|
|T4|(control spillover)|-0.13*|-0.12*|-0.13*|-0.13*|-0.13*|-0.12*|-0.12*|
|||(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|(0.07)|
|N||2995|2994|2994|2996|2996|2996|2995|
|Con|trol Mean|0|0|0|.003|.001|-.001|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

65
Table A34: Robustness of impact on nutrition index to differential attrition

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|
||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1 (Safe Spaces)|-0.40**|-0.36**|-0.43***|-0.41**|-0.41**|-0.40**|-0.40**|
||(0.16)|(0.16)|(0.16)|(0.16)|(0.16)|(0.16)|(0.16)|
|T1+Leaders|-0.24*|-0.01|-0.39***|-0.27*|-0.26*|-0.24*|-0.24|
||(0.14)|(0.12)|(0.14)|(0.14)|(0.14)|(0.14)|(0.14)|
|T2 (Safe Spaces + IGA)|-0.36**|-0.22|-0.47***|-0.38**|-0.38**|-0.35**|-0.35**|
||(0.16)|(0.14)|(0.14)|(0.15)|(0.15)|(0.15)|(0.15)|
|T2+Leaders|-0.15|0.14|-0.32*|-0.20|-0.20|-0.15|-0.15|
||(0.15)|(0.14)|(0.16)|(0.15)|(0.15)|(0.15)|(0.15)|
|T3 (Safe Spaces + Husbands Clubs)|-0.68***<br>(0.20)|-0.48***<br>(0.16)|-0.89***<br>(0.18)|-0.74***<br>(0.20)|-0.69***<br>(0.20)|-0.67***<br>(0.20)|-0.68***<br>(0.20)|
|T3+Leaders|-0.05|0.02|-0.09|-0.06|-0.06|-0.05|-0.05|
||(0.14)|(0.13)|(0.14)|(0.14)|(0.14)|(0.14)|(0.14)|
|T4 (control spillover)|-0.25**|-0.24*|-0.25**|-0.25**|-0.25**|-0.25**|-0.25**|
||(0.13)|(0.13)|(0.13)|(0.13)|(0.13)|(0.13)|(0.12)|
|N|3003|3002|3002|3004|3004|3004|3003|
|Control Mean|0|0|0|.001|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

66
Table A35: Robustness of impact on mental health index to differential attrition

|||(1)|(2)|(3)|(4)|(5)|(6)|(7)|
|---|---|---|---|---|---|---|---|---|
|||Main|Trimmin|g treated|Im|puting cont|rol|IPW|
|||spec.|Bottom<br>UB|Top<br>LB|95th pc.|75th pc.|50th pc.||
|T1|(Safe Spaces)|0.28***<br>(0.10)|0.33***<br>(0.09)|0.25***<br>(0.09)|0.27***<br>(0.10)|0.27***<br>(0.10)|0.27***<br>(0.10)|0.28***<br>(0.10)|
|T1|+Leaders|-0.00|0.23**|-0.16|-0.04|-0.03|-0.02|-0.00|
|||(0.11)|(0.09)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|T2|(Safe Spaces + IGA)|0.27**|0.43***|0.17*|0.23**|0.24**|0.25**|0.27**|
|||(0.10)|(0.10)|(0.10)|(0.10)|(0.10)|(0.10)|(0.10)|
|T2|+Leaders|-0.00|0.26***|-0.19*|-0.06|-0.03|-0.01|0.00|
|||(0.11)|(0.09)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|T3|(Safe Spaces + Husbands Clubs)|0.11|0.36***|-0.05|0.04|0.06|0.08|0.11|
|||(0.13)|(0.10)|(0.12)|(0.13)|(0.13)|(0.13)|(0.13)|
|T3|+Leaders|0.27**|0.37***|0.22**|0.25**|0.26**|0.26**|0.27**|
|||(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|(0.11)|
|T4|(control spillover)|0.04|0.05|0.04|0.04|0.04|0.04|0.04|
|||(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|(0.09)|
|N||3003|3002|3002|3004|3004|3004|3003|
|Con|trol Mean|0|0|0|.002|.001|0|0|

_Note:_ *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1, standard errors in parentheses clustered at the locality level. Column (1) replicates the main results presented in tables 3, 4 and 5. Columns (2)-(3) present results equivalent to Lee bounds: we re-run the estimations after dropping _K_ observations from the top/bottom of the distribution in the treatment group to calculate the lower/upper bound, where _K_ is the difference between the number of attriters in the treatment groups and the control group. Columns (4)-(6) present similar results, but instead of dropping _K_ observations in the treatment group, we impute the outcomes of _K_ attriters in the control group using the 5th, 25th and 50th percentiles of the observed distribution of the treatment group. Column (7) presents the Inverse Probability Weighting (IPW) estimates.

67