Targeting Youth Entrepreneurs: Does the composition of targeting committee matter?

This intervention builds on and targets Youth Agricultural Innovation Groups (YAIGs) in Oromia region, which were part of the SAfA (Foundations Alliance for Africa) project implemented by the Hanns R. Neumann Stiftung (HRNS). The SAfA project aimed to enhance the livelihood prospects of young people in Ethiopia through an integrated and multi-sectoral approach. The target population for this intervention are YAIG leaders and YAIG members in two (Bedele and Gechi) districts in Oromia region.
Intervention: Identification of potential youth entrepreneurs and ranking by YAIG leaders
The main intervention in this study is to identify youth with relatively high entrepreneurial potential and test the performance of alternative community-based targeting methods. The CBT will be conducted by YAIG leaders in each YAIG, composed of chairman, secretary, cashier, auditor, and facilitator. We task YAIG leaders to rank about 20 YAIG members in their respective YAIG, from the one with the highest entrepreneurial potential (first) to the one with least entrepreneurial potential (last) based on a set of predefined criteria, which are handed to the committee by the researchers (see the experimental design selection below). YAIG leaders will be informed that the NGO conducting the YAIG-level survey aims to identify a small group of youth to support them with seed capital to start or expand a business or support livelihood activities. The transfer of the seed capital follows a two-stage process. First, beneficiary YAIG will be randomly selected. Next, within each selected YAIG, the NGO we are working with will transfer to the seed capital to the four highest-ranked youth members as determined by the committee members. If a YAIG is selected, we aim to award a 20,000 Birr seed capital to each of the four youth members with the highest potential within each YAIG.
We randomly assign the recruited YAIGs to two experimental arms: (i) conventional targeting (YAIG leaders select beneficiaries) and (ii) gender-balanced targeting (gender-balanced committee selects beneficiaries). This allows us to create an otherwise comparable group of youth and their YAIG. Prior to the ranking exercise, we administer a series of questions that aim to elicit YAIG leaders’ objective functions in allocating the seed capital transfers.

Research Objectives and Research Questions
This research project aims to address three broad research questions. The first question and objective relate to whether increasing women’s representation in targeting committees increase their voice and influence in collective decisions. This builds on previous evidence on the potential of increasing women’s representation in committees and leadership roles (Karpowitz et al., 2012; Clayton et al., 2025; Karpowitz et al., 2014; Leon et al., 2019; Kahsay et al., 2021). While some studies show that women leaders improve the provision of public goods (Chattopadhyay and Duflo, 2004; Agarwal, 2009a,b; Coleman and Mwangi, 2013; Leisher et al., 2016; Kahsay et al., 2021), others find the opposite (Gajwani and Zhang, 2015; Deininger et al., 2015; Ban and Rao, 2008; Bardhan et al., 2010). It also links to a broader literature on women decision making in politics (e.g., O'Brien and Rickne, 2016; Bagues and Campa, 2021) and company boards (e.g., Ferrari et al., 2022). Second, we investigate whether this ultimately leads to improved access to transfer for women and marginalized youth. Finally, we also aim to investigate whether women’s representation reduces elite capture of the transfer. Similarly, we also explore whether targeting priorities of the committee change because of the increase in women’s representation. For this purpose, we elicited YAIG leaders’ preferences and priorities in identifying and targeting youth with highest entrepreneurial potential. More specifically, we aim to address the following research questions:
1) Can increasing women’s representation improve their influence in collective and targeting decisions?
2) Do women’s representation in targeting committee increase women’s and girl’s access to transfer in targeted transfers?
3) Do women’s representation in targeting committees reduce elite-capture of transfers?

2026-08-01

2026-11-30

1. Women’s access to seed capital: proxied by the gender of selected youth members
2. Elite capture: proxied by the link between the committee and selected youth members ( (selecting oneself, family member, relative, friend, etc.)
3. Women and girls voice and influence in collective decisions
4. Cooperation among committee members
5. Targeting effectiveness: proxied by the comparison of selected youth members and average group member in terms of ability (education, business experience).

1. Women’s access to seed capital and gender composition and related characteristics of youth selected to receive seed capital. One of our immediate outcomes relate to women’s or girls’ access to the seed capital. We are mostly interested in understanding whether changing the composition of the committee matters for the ultimate composition of beneficiaries. Specifically, we aim to explore if including more women in the targeting committee increase the share of women and girls benefiting from the seed capital. We are also interested in uncovering youth characteristics selected to receive seed capital under the conventional and gender-balanced arms. This includes simple comparison of the attributes of the youth selected to receive transfer in each group. For this purpose, we aim to compare observable characteristics of beneficiary youth in both groups in terms of their gender, education, socioemotional skills, business experience and potential as well as their household characteristics.
2. Elite capture: we measure elite capture in terms of inclusion of the committee members as well as their acquaintances, relatives and friends in the beneficiary list. For this purpose, we aim to construct binary indicator variables assuming a value of 1 if one or more of the committee members are selected to benefit from the transfer or not. Similarly, we aim to characterize the relationship between those selected to benefit from the transfer and the committee members and identify potential tendencies of favoritism.
3. Women’s influence in collective decisions: we aim to elicit perceived influence associated with each member of the committee. At the end of the interview, we ask each member separately about who was influencing much of the collective decisions (Karpowitz et al., 2012; Karpowitz et al., 2024). Ultimately, this helps us to capture women’s influence in collective decisions.
4. Cooperation among committee members: We measure cooperation among committee members through a public-good experiment, particularly in terms of their contributions to public good. At the beginning of the experiment, we provide YAIG leaders with two envelopes: one labeled as a “private account” and the other as a “group account”, along with 200 Birr. We then asked each leader how much to contribute to the “group account” and how much to keep in his/her “private account”. The total contributions invested in the group account are doubled by the experimenter and subsequently distributed equally among group members, irrespective of individual contributions. Thus, individual earnings from the game would be determined by their own decisions and the decisions of two other leaders. Cooperation is a continuous variable which is measured as the amount each participant contributes to the public good from the initial endowment.
5. Targeting effectiveness: proxied by the comparison of selected youth members and average group member in terms of ability (education, business experience)

1. Concordance with data-driven and peer targeting
2. Decision-making processes: consensus-based, voting or a combination of both
3. YAIG-level performance indicators
4. Targeting priorities and preferences

This section describes the experimental design of the leader-based targeting of potential entrepreneurs. The target group for this experiment are YAIG leaders assuming various roles within their youth groups. Thus, the key actors and target of our interventions are the four YAIG leaders recruited from each YAIG. As described earlier, the survey brings together four YAIG leaders assuming the following roles in their YAIG: (i) Chairperson, (ii) Secretary, (iii) Casher, (iv) Auditor, and (v) facilitator. In some cases when these leaders are not available or missing, we replace them by those who previously assumed these roles or other active members of the YAIG. We note that these members are commonly involved in some important decisions related to identification of beneficiaries for similar programs and interventions, both in Ethiopia and other parts of Africa. The intervention follows YAIG level clustered randomization in which the 185 YAIGs are randomly assigned into a control and treatment arm (see also Figure 1). The random assignment is stratified by kebele as we have multiple YAIGs in each kebele.

Infert Figure 1 Here (Figure 1. Random assignment of YAIG treatment and control arms)


(1) Conventional composition of YAIG leaders (C): YAIG leaders in this group are instructed to create a committee composed of their usual officers and then conduct the targeting process following the introductions. They are informed that their ranks and selection will have consequences. If their YAIG is lucky and identified to be in the group randomly selected for the seed capital (transfer), we will provide the top four candidates with a seed capital of 20,000 Birr each. All YAIG members ranked below will not receive any transfer. YAIG leaders are asked to rank all youth from the one with highest entrepreneurial potential to the one with the least entrepreneurial potential. They are given the following five criteria for ranking the youth with entrepreneurial potential within their YAIG. Specifically, the YAIG leaders are asked to prioritize and rank the YAIG members based on the following criteria:
(i) Youth who may have potential entrepreneurial qualities to succeed in business compared to other peers in the same group.
(ii) Youth who has or may have business ideas or are in the process of starting a business.
(iii) Youth who have know or experience running a business
(iv) Youth who have the potential to turn a seed capital into in a profitable business with high potential returns.
(2) Gender-balanced YAIG leader composition (T): Another group of YAIG leaders are asked to ensure gender-balance of the committee and strictly satisfy that at least half (two) of the committee members should be female. This is motivated by our interest to understand the implications of bringing women and girls in major decision-making roles. Previous studies show that women’s inclusion in deliberation and committee-based decision improve their voice and associated outcomes (Karpowitz et al., 2012; Clayton et al., 2025; Karpowitz et al., 2014; Kahsay et al., 2021). Except for the composition of the committee, YAIG leaders in this group are asked to accomplish identical tasks and they are required to rank YAIG members based on the five pre-determined targeting criteria described above.

Not available

The randomization is done at the YAIG level using the list of YAIGs available to us. The YAIGs were created and established by another project. The 185 YAIG are then randomly assigned into the two groups, with stratification at kebele level.

Youth Agricultural Innovation Group (YAIG)

Yes

185 YAIG and about 740 YAIG leaders (and associated YAIG members).

C (Control : conventional committee): 93 YAIGs
T (Gender-balanced committee): 92 YAIGs

185 YAIG and about 740 YAIG leaders (and associated YAIG members). C (Control : conventional committee): 93 YAIGs T (Gender-balanced committee): 92 YAIGs

185 YAIG and about 740 YAIG leaders (and associated YAIG members).
C (Control : conventional committee): 93 YAIGs
T (Gender-balanced committee): 92 YAIGs

We compute the number of YAIGs needed for the primary outcomes described above, assuming fixed number of youth members in each YAIG. The nature of the outcomes we examine involve analyses at different levels: YAIG leader, individual and YAIG levels. In the full sample of YAIG members, we have on average 24 members in each YAIG, and we anticipate being able to trace about 85-87 percent of them, about 20 YAIG members. Our power calculations aim to achieve the standard and widely adopted 80 percent power at a significance level of 5 percent. Given that we have multiple primary outcomes, we computed the number of clusters and associated sample size needed for each outcome separately. For each outcome, we assemble mean and standard deviations from our administrative data and previous studies in similar settings. To evaluate the impact of increasing women’s representation on women’s access to the transfer, we compute statistical power and sample size needed to detect a reasonable impact on women or girl’s access to the transfers (whether a woman youth receives a transfer). About a third of the YAIG members in our samples are female. As shown in Table 1, to detect a 10-percentage point increase in women’s access to the transfer because of women’s representation, we need 76 YAIGs in each arm. Similarly, detecting an 8 percent difference in elite capture (by self-selecting YAIG leaders into the beneficiary list for the seed capital) requires at least 65 YAIGs in each arm. Based on these calculations, we randomly allocate 93 of the total 185 YAIGs into the control group and the remaining arm to the gender-balanced arm. We stratify the random assignment of YAIGs across woredas and kebeles.