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Public Disclosure Authorized
Policy Research Working Paper 9552
Public Disclosure Authorized
Business Training and Mentoring
Experimental Evidence from Women-Owned
Microenterprises in Ethiopia
M. Mehrab Bakhtiar
Public Disclosure Authorized
Gautam Bastian
Markus Goldstein
Public Disclosure Authorized
Africa Region
Gender Innovation Lab
February 2021Policy Research Working Paper 9552
Abstract
Recent research shows that microenterprises in develop- business training received customized mentoring from
ing countries are constrained by their managerial capacity, these “trained mentors.” Pooled results using three rounds
especially in the areas of marketing, record keeping, finan- of post-training surveys carried out over three years show
cial planning, and stock control. In a stratified randomized that business training causes profit and sales to improve by
controlled trial, experienced businesswomen in Ethiopia 0.21 standard deviation, while business practices improve
were given a formal business training that addressed these by 0.13 standard deviation. The overall impact of mentor-
constraints. A second-stage mentoring component in which ing is muted—strong impacts are observed on the adoption
a random selection of female mentees within the social of business practices among mentees, but there is no statis-
and business network of the trainees from the first-stage tically significant impact on profits.
This paper is a product of the Office of the Gender Innovation Lab. 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 mgoldstein@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 TeamBusiness Training and Mentoring:
Experimental Evidence from Women-Owned
Microenterprises in Ethiopia
M. Mehrab Bakhtiar∗ Gautam Bastian
IFPRI Independent Researcher
Markus Goldstein
World Bank
JEL: D22, L26, M53, C93, J24
Keywords: Entrepreneurship, Business training, Mentorship, Impact Evaluation, Field
Experiments, Gender
∗
Contact: M.Bakhtiar@cgiar.org; gautamb@gmail.com; mgoldstein@worldbank.org. We thank
the Umbrella Facility for Gender Equality for financial support and seminar participants at the
Pacific Conference for Development Economics (PACDEV), 2017; Centre for the Study of African
Economies (CSAE) Conference, 2018; Annual Bank Conference on Africa (ABCA), Stanford Uni-
versity, 2018 for their helpful comments. Eliana Carranza was closely involved with the Impact
Evaluation design and provided insightful feedback throughout the duration of the research project.
Adiam Hailemichael, Nikita Arora, Tigist Ketema, Ombeline Gras and Brittany Hill provided ex-
cellent research assistance as well as field and administrative support. Vanessa Adams and Hebret
Abahoy - from ACDI/VOCA, the implementing partner in this project - were superbly collaborative.
We are indebted to David Mckenzie, Salman Alibahi, Joao Montalvao, Kenneth Leonard, Rachael
Pierotti and Michael O’Sullivan for their invaluable feedback. The views presented in this paper are
the authors’ own and do not represent the World Bank and its member countries.1 Introduction
Ownership of, and employment in, microenterprises account for a large fraction of the labor
market in the developing world. In many countries, microenterprises underperform other
forms of businesses in terms of productivity and profitability. One possible explanation
for the dismal outcomes of microenterprises is that microenterprise owners lack managerial
capital, which is the skill-set required to run a business (Bloom and Van Reenen, 2007; Bruhn,
Karlan, and Schoar, 2010; McKenzie and Woodruff, 2016). Policymakers have attempted to
address this constraint that small businesses face by scaling up business training programs
all over the developing world. While an emerging body of literature finds that business
training can improve management practices, the measured impact of standard versions of
this training on business profit or operational scale appears to be modest, at best (McKenzie
and Woodruff, 2016; Quinn and Woodruff, 2019).
McKenzie and Woodruff (2016), however, argue that the relationship between ‘better’ man-
agement/business practices1 - particularly, in the areas of marketing, record keeping, financial
planning and stock control - and performance is causal and that the lack of an observable
effect in the impact evaluations of most business training programs is because firms do not
change business practices enough rather than because these practices do not matter.2 More-
over, in a critical review of the literature, McKenzie and Woodruff (2014) find that many
of the business training evaluations measure impacts only within a year of training. They
argue that such short-term evaluations are problematic because it may take longer than a
year for adopted business practices to translate into an impact on business outcomes. Thus,
several recent studies had an extended period of follow-up after training interventions were
completed (Bruhn, Karlan, and Schoar, 2018; Higuchi, Mhede, and Sonobe, 2019; Karlan,
Knight, and Udry, 2015; David McKenzie Susana Puerto, 2017; Valdivia, 2015). However,
these studies show mixed impacts of business training programs on business performance.
1
The study uses 26 questions that measure business practices in the areas of marketing (e.g., Does the
firm advertise? Does it attempt to attract customers with a special offer? Does it ask customers what other
products they would like it to sell?), record keeping (e.g. Does the firm record every sale and purchase? Has
it worked out the cost of each item it sells? Does it have a written budget?), financial planning (e.g. Does
it have a sales target for the next year? Does it have a balance sheet and profit and loss statement?), and
buying and stock control (e.g. Does it frequently run out of stock? Does it attempt to negotiate discounts
with suppliers?). These are intended to be universal best practices, in the sense that most firms should
benefit from using them. They are closely based on the goals of business training programs like the ILO’s
Improve Your Business (IYB) program.
2
Importantly, McKenzie and Woodruff (2016) show that the (modest) effects observed in several business
training programs on profits/sales are remarkably consistent with the predicted effects given the observed
changes in business practices.
1To address this gap in the literature, we evaluate the impact of a well-designed and intensive
business training curriculum on business practices and performance over an extended period.
The business training program targeted high-potential women entrepreneurs in five regions
of Ethiopia and was carried out as a randomized controlled trial. Pooled results using 3
rounds of post-training surveys, carried out over 3 years show that business training causes
profits and sales to improve significantly. This effect appears to be driven by the adoption
of several of the ‘better’ business practices identified by McKenzie and Woodruff (2016) that
were covered extensively in the business training program.
Given the extent of micro-entrepreneurial activities in developing countries, it is, however,
important to identify low-cost programs that can lead towards the adoption of these business
practices with the aim of subsequently improving business performance. Standard business
training programs, like the one mentioned above, are expensive - business training programs
can cost hundreds of dollars per student and collectively, several billion dollars have been
spent behind business training all over the world involving millions of trainees (Blattman and
Ralston, 2015).3 This problem could be potentially addressed by a mentoring intervention
involving trained mentors: once more experienced business people are given formal business
training, they can be connected with smaller firm owners from their networks to pass on what
they had learned in the training program as well as provide customized mentorship. This is
a promising low-cost approach to business training programs that organically disseminates
relevant market information and advice on business practices and knowledge to new and
fledgling businesses.
To understand the impact of mentoring, business women (mentors) who completed the busi-
ness training were assigned to provide mentoring to a random subset of smaller firm owners
(mentees) within their social and business networks that they had nominated when applying
for the business training. We find that mentees, randomly assigned to receive mentoring,
exhibit strong effects on business practices. Profits, however, were not significantly affected.
However, we show that, despite lacking statistical significance, the effect of mentorship on
profit is remarkably consistent with the predicted effect given the observed changes in busi-
ness practices.
This study is similar to the impact evaluation of a training and a mentoring intervention
by Brooks, Donovan, and Johnson (2018), where they directly compare the impact of one-
to-one mentorship to a traditional business training. They find that in the short term,
one-to-one mentoring results in higher business profits as a result of a transmission of local
3
For example, the International Labor Organization’s Start and Improve Your Business program has
trained more than 4 million people in 100 countries since 1977.
2market information, such as low-cost suppliers. However, the effect appears to fade in
the longer term. Our study departs from Brooks, Donovan, and Johnson (2018) in two
important ways. First, we evaluate whether firms that receive formal business training,
adopt ‘better’ businesses practices. Here we focus on marketing, stock-keeping, record-
keeping, and financial planning business practices that McKenzie and Woodruff (2016) have
identified as essential inputs for improving business performance. We specifically examine
whether changed practices translate into better outcomes for the firms especially in the longer
term (i.e., approximately three years after the training). Secondly, if business performance
is indeed constrained by the adoption of these practices, receiving mentoring alone - as in
Brooks, Donovan, and Johnson (2018) - may not induce improved business performance in
the medium and long term. However, such an effect maybe possible through the provision of
mentoring by trained mentors – provided that communication of the better business practices
happens effectively through the mentoring.
Together, the formal business training program and the mentoring component is known as
the Ethiopia Women Agribusiness Leaders Network (WALN) project. The evaluation of this
project allows us to investigate the importance of business practices such as marketing, stock-
keeping, record-keeping, and financial planning for small, women-owned firms in Ethiopia,
and the longer-term consequences of adopting these practices on business performance.
The remainder of this section provides a more comprehensive review of the literature. Section
2 describes the WALN project. Section 3 lays out our experimental design, with section 4
explaining our empirical approach. Section 5 presents our results and section 6 concludes.
1.1 Additional Literature Review
Business and Management Training
Business training is the broader approach encompassing business skills training, mentoring
and consulting interventions to improve the poor business skills and management practices
that are common in developing countries. These inefficiencies more severely affect women
who constitute a larger share of self-employment in small enterprises and often see lower
returns than their male counterparts (Calderon, Cunha, and Giorgi, 2020; Gine, Xavier and
Mansuri, 2014; De Mel, McKenzie, and Woodruff, 2012).
A number of impact evaluations of business training programs have yielded mixed results.
A study in rural Mexico increased the use of formal accounting techniques, and improved
3revenue, profits and the number of clients of female business owners (Calderon, Cunha,
and Giorgi, 2020). In urban Sri Lanka, on the other hand, although training improved the
business practices of self-employed women, there was no effect on business profit, sales or
capital stock. When the business training was coupled with a grant however, there was a
significant—albeit short-term—improvement in business profitability (De Mel, McKenzie,
and Woodruff, 2012).
Combining business training with large loans (about seven times the average loan size) to
microfinance clients in rural Pakistan, Gine, Xavier and Mansuri (2014) find that although
business training alone increases business knowledge, improves business practices (such as
record-keeping of sales), and increases household expenditures, group cohesion and general
outlook on life these beneficial effects are largely reaped by male clients. Women clients do
show a significant improvement in business knowledge, however they have little control over
their businesses— 40 percent reported that their (male) spouses are responsible for most of
their business decisions. Adding the loan to the training has little effect irrespective of client
gender, perhaps indicating that existing loan sizes already meet the demand for credit.
Karlan and Valdivia (2010) find that providing 30 to 60 minute business training to female
microfinance clients in Peru improved business knowledge and client retention for the MFI,
but there was no impact on business outcomes such as profits or revenue. Valdivia (2015),
studying another Peruvian sample, finds that personal development, business management
and productive skills training intervention aimed at empowering women and improving their
access to credit and their business practices has some interesting effects. Women who were
offered an additional three-month technical assistance package were more likely to make
business process innovations and saw an 18% increase in sales. By comparison, women who
did not receive technical assistance were more likely to close their businesses.
McKenzie and Woodruff (2016), mentioned earlier, demonstrate that business training pro-
grams which have larger effects on management practices also have larger impacts on profits.
They suggest that most entrepreneurship training programs appear to fail because they do
not improve business practices sufficiently, not because business practices themselves do not
matter.
Some more recent work on training has emphasized the importance of curriculum choices.
For example, Campos et al. (2017) compare a standard business training and one that
emphasizes personal initiative. The personal initiative training focuses more on mindset
than particular practices. They find that the personal initiative training shows significantly
higher profits than standard training, and that this difference is more pronounced for women.
4In another innovation in the design of curriculum for business/management training, Bloom
et al. (2013) demonstrate that individualized consulting programs can be effective. Using
high-frequency data from large textile factories in Mumbai, India, Bloom et al. show that
an intensive consulting intervention greatly improved output per worker and quality. They
also show that management practices (specific to textile production) improved significantly.
Finally, some emerging evidence indicates that individual business consulting may improve
managerial skills and self-confidence of owners of small and medium enterprises (Bruhn,
Karlan, and Schoar, 2018 in Mexico) and business literacy (Karlan, Knight, and Udry, 2015
in Ghana). A randomized controlled trial in the Dominican Republic has also shown that
simpler business advice is more efficient in improving outcomes for lower-profile participants
(Drexler, Fischer, and Schoar, 2014).
In summary, existing evidence suggests that the impact of business training and consulting
is highly sensitive to geographical and business contexts as well as to curriculum content and
add-on interventions such as technical assistance and finance. In light of this evidence, it is
important to understand the specific business environment, needs and constraints faced by
local entrepreneurs before implementing a business skill training program. Special attention
needs to be paid to the specific needs of women entrepreneurs, especially their need for
training and finance. The importance of one-to-one counseling as well as the need to tailor
advice to the level of the participants should be kept in mind; making WALN’s mentoring
component a particularly relevant alternative to classical business training.
Mentoring
The appeal of mentoring, as an intervention oriented to bridging gender gaps, lies in its
ability to fit the needs of women-owned and women-managed small and medium enterprises,
for whom a lack of positive gender-role models may be a significant barrier to participating
in high-earning male-dominated sectors and to overcoming productivity and earnings gaps
even when they are able to participate (Campos et al., 2015).
In this section we briefly situate the WALN mentoring component in the theoretical and em-
pirical literature on mentoring in general and in how it relates to women’s entrepreneurship.
The current conceptual framework about mentoring is based on Kram (1988; 1983) who views
mentoring as a combination of career oriented advice and behavior modeling and personal
psychosocial support that facilitates goal oriented knowledge acquisition, social learning and
behavior change. The mentor serves as a role model for effective business behavior (Allen
et al., 2004) while the mentee receives career and psychosocial (self-esteem) benefits.
5A Canadian study by St-Jean and Audet (2012) finds that mentee entrepreneurs benefit most
significantly on cognitive and skill-based learning, e.g., management knowledge and skills,
improved vision for their business venture and identifying new opportunities. Mentees also
experience affective learning benefits to a lesser degree, such as an improved self-efficacy,
validation of entrepreneurial self-image and a lowered sense of solitude, factors that could
in turn influence entrepreneurial resilience. St-Jean (2012), using another Canadian en-
trepreneur mentoring dataset, finds that the career-related functions of mentoring are the
most effective factor in the development of learning, followed by psychological and role-model
functions. Trust, perceived similarity and mentee self-disclosure are found to be essential to
build a highly effective mentoring relationship.
Several recent studies have experimentally tested the impact of effective mentoring (or
mentoring-like) which are cost effective (with some being better suited for less-experienced
businesses). As referred to earlier, Brooks, Donovan, and Johnson (2018) find that in the
short term, one-to-one mentoring results in higher business profits for less experienced mi-
croenterprises. In this non-incentivized setting, mentees who continue to meet with their
mentors 12 months after the official end of the treatment period are more profitable than
those who are no longer meeting. Despite a clear selection issue, this finding highlights the
possibility that introducing incentives in mentoring interventions may increase the intensity
and durability of the mentoring interaction, which, in turn, can improve longer-term business
performance.
Lafortune, Riutort, and Tessada (2018) compare the impact of a personalized consulting
intervention and a role model-type intervention for microenterprises in Chile. Both programs
have large impacts (which are similar in magnitude) on business profits, with the latter
shown to be more cost effective. Another recent study on mentoring is a long-running
field trial involving junior female economists in the USA which experimentally varied access
to mentoring workshops on advancing research careers in academia (Ginther et al., 2020).
Treated women are found to be more likely to stay in academia and more likely to have
received tenure in an institution ranked in the top 50 in economics in the world.
The theoretical literature on social networks suggests that beliefs and ideas are more likely
to be changed when the changes originate from trusted social bonds (Jackson, 2010). In
traditional societies, homogeneous networks may reinforce social norms, in turn reinforcing
current behavior and attitudes, especially for women. Diversifying networks may help to
connect women to new ideas, role models and business contacts, even encouraging greater
innovation. Kandpal, Baylis, and Arends-Kuenning (2012) find that a women’s empower-
ment program intervention in northern India was able to affect social norms by increasing
6participants’ social contacts outside their own caste group. They also find that participating
women have higher physical mobility, political participation, and access to employment as
well as spillover effects on non-participants relative to women in untreated areas.
Conley and Udry (2010), Bandiera and Rasul (2006), Munshi (2004) and Foster and Rosen-
zweig (1995) measure the consequences of social learning in various contexts. More recently,
BenYishay and Mobarak (2019) and Beaman et al. (2018) experimentally vary the introduc-
tion of information in social network nodes and measure its impact in information dissemina-
tion and adoption. Related to our study, Atkin, Khandelwal, and Osman (2017) and Cai and
Szeidl (2018) measure the impact of potential knowledge transfers from exogenously selected
partners among (relatively larger) businesses. Atkin, Khandelwal, and Osman (2017) study
the diffusion of knowledge in the context of supplier-customer relationships by randomly
allocating new foreign rug orders to Egyptian rug makers, and Cai and Szeidl (2018) study
the creation of randomly formed business groups in China. Both studies find a sustained
impact on profits as a result of the interventions.
The goodness of fit between the mentor and mentee has been identified in the literature
as a key ingredient of a successful mentoring intervention. The WALN project leverages
existing social ties between mentors and mentees, i.e. mentors identify promising mentees,
helping overcome lack of trust which is a typical barrier to information dissemination. Sim-
ilar to Brooks, Donovan, and Johnson (2018), the WALN mentoring component was not
incentivized.
Also similar to Brooks, Donovan, and Johnson (2018), in the WALN project, both the
mentors and mentees are women, which may provide a beneficial support structure. Es-
pecially in the male-dominated Ethiopian agribusiness sectors, women-to-women mentoring
may help reinforce achievement-oriented behavior, providing task-specific feedback and al-
leviating stress (Noe, 1988; Burke and McKeen, 1990; Nelson and Quick, 1985). Campos
et al. (2015) hint at a counter-argument that men with existing networks in male-dominated
sectors might be able to open more doors for women mentees, but their argument is more
about business entry rather than success conditional on entry. Overall, there is no consensus
in the literature on the relative effectiveness of women and men mentors for women mentees
(Hansford, Tennent, and Ehrich, 2002).
In summary, there is a broad acceptance in the literature of the idea that mentoring is a
useful and effective method of transferring knowledge, and improving business and career
outcomes, especially since each program can be adapted to fit the needs of the participants.
72 Program Description
The Women in Agribusiness Leaders Network (WALN) project involved a first-stage of busi-
ness training and a second-stage of mentoring—which was carried out by the business women
trained in the first-stage. The randomized controlled trial design of the program led half of
the potential mentors and mentees—who were eligible to participate in the WALN project—
to be randomly assigned to receive business training and mentoring interventions, respec-
tively. The other halves formed the control groups that did not receive any intervention.
Comparing the treated groups to the control groups allows us to separately measure the
impact of the business training program and the mentoring program.
2.1 Program Overview
WALN was embedded in the Agribusiness and Market Development (AMDe) component of
the Government of Ethiopia’s USAID and World Bank-funded Agricultural Growth Program
(AGP) and was part of USAID’s wider Feed the Future programming. WALN aimed to
improve business skills of female participants, enabling them to be community leaders and
change makers.
The particular focus of the WALN project on women was guided by USAID/Ethiopia’s
mission-wide gender analysis which found that while women constituted 45% of the agricul-
tural labor force, they accounted for only 20% of the members of agricultural cooperatives
and had less access to productive resources and opportunities than their male counterparts.
Similarly, Aguilar et al. (2013) analyze household survey data from rural Ethiopia and find
a 23% gender gap in productivity (in terms of gross value of output) per hectare between
female farm managers and male farm managers.
WALN sought to improve agribusiness outcomes by addressing gender differences in produc-
tivity, profitability, participation and leadership in the sector. The intervention was based
on the idea that training, mentoring and networking could expand women’s capacity to play
leadership roles in sectoral organizations and manage business profitably. WALN was ex-
pected to improve women’s participation in leadership and decision-making in the overall
agriculture sector in Ethiopia.
A focused business and leadership training, as well as a mentoring program may help women
strengthen and expand a fledgling support network to expand economic empowerment. In-
8creased female membership and leadership in cooperatives, more savings and better market-
ing may result as more women are visible, credible and effective business leaders. Bringing
the voices of women to the table more effectively impacts issues such as health, nutrition,
early marriage and household financial management.
The Africa Gender Innovation Lab of the World Bank partnered with USAID and the Gov-
ernment of Ethiopia to evaluate the impact of WALN. The impact evaluation of WALN
was designed to capture the business and social-network effects of business training and
mentoring on mentors and mentees.
2.2 Description of the Interventions
The WALN project was composed of three components: (i) a business training course; (ii) a
mentoring system; (iii) establishing a formal network of women entrepreneurs.
The objective of this project was to engage high-potential women business leaders to achieve
the following objectives: (1) build skills in key areas such as negotiation, marketing, net-
working, financial planning and communication; (2) develop enhanced leadership capabilities
that will enable them to grow and manage their business more profitably, (3) develop a pro-
fessional network with women leaders in agriculture and related business, and (4) serve as
mentors to aspiring businesswomen in their networks or community and be a role model.
WALN focused on 9 specific value chains that were part of AGP-1, namely chickpeas, coffee,
honey, maize, sesame, wheat, livestock, dairy and teff. Businesswomen in these value chains
working in 96 targeted woredas across 5 regions in Tigray, Amhara, Oromia, SNNPR, and
Addis Ababa were eligible to participate.
Business and Leadership Training
This training package sought to provide basic business management skills that are essential
for running profitable and sustainable businesses. Intensive business and leadership training
was provided, to test if it could expand women’s capacity to play leadership roles in sectoral
organizations and manage businesses more profitably. International and national business
specialists were called upon to deliver this training using adult-learning methods such as case
studies, facilitated discussions, group work, interactive presentations, plenary sessions, role-
play, individual exercises and games. Between July and December 2014, 99 women received
approximately 60 hours of classroom training spread over 6 sessions of 2 days each on the
9four skill areas/modules detailed in Appendix Table A.3. These women were referred to as
‘WALN Mentors’. All modules except Module IV that focuses on Mentoring and Coaching
were meant to improve the mentor’s business. Module IV focused on giving mentors the
skills to advise mentees. Further details on the business training curriculum are available in
Appendix Section A.3.
The training curriculum was developed by technical experts hired by ACDI/VOCA. It is a
fairly standard curriculum for these types of training, but it does not explicitly follow some
of the more established curricula like EMPRETEC or ILO SYB.4 The focus on mentoring
and the integration of a mentoring component in the program are the more innovative and
novel elements of this intervention.
Compliance to the business training program was quite high. Approximately 94% of the
businesses randomized to the business training/‘WALN Mentors’ treatment report to have
attended at least one training session. Moreover, average, treatment mentors participated
in 5.2 sessions (out of 6 sessions in total).
Mentors, who completed the business training, reported mentoring 1.3 mentees on average.
Only 10% of these mentors report that they did not provide mentoring to anyone after
completing the business training.
Mentoring Program
Generally, mentoring is a professional relationship in which a mentor, an experienced person,
assists a mentee, a less experienced person seeking help and advice, to develop specific skills
and knowledge that will enhance the latter’s professional and personal growth. In the setting
of WALN, the mentoring component leveraged existing social ties between the mentors and
mentees to deliver elements of customized business training and counseling in a semi-formal
setting.
During the application for the WALN business and leadership training programs (later to
become potential mentors) applicants were asked to nominate potential mentees from among
their social networks. On average each mentor nominated close to 7 mentees. Within each
4
EMPRETEC is a capacity building program by the United Nations Conference on Trade and Devel-
opment (UNCTAD) to ‘promote the creation of sustainable, innovative, and internationally competitive
small- and medium-sized enterprises (SMEs).’ The Start and Improve Your Business (SIYB) program is a
management-training program developed by the International Labour Organization (ILO) with a focus on
starting and improving small businesses as a strategy for creating more and better employment for women
and men, particularly in emerging economies. With an estimated outreach in over 100 countries, it is one of
the world’s largest program in this field.
10mentor’s nominees, on average 3 mentees were randomly assigned to receive mentoring.
Mentees were typically younger women, who wanted to start their own agribusiness, were in
the informal sector, or those who were not yet competitive in the agribusiness market but
had the potential. The intervention encouraged these women to formalize their businesses
and become better business managers.
Once mentors had undergone the business and leadership training described above, they
were asked to use their knowledge to mentor and coach their prospective mentees who were
randomly assigned to receive mentoring for 6 months. The project used a series of intensive,
in-the-field workshops and mentor-mentee sessions, along with ongoing coaching and sup-
portive contact among women in their network. Mentors received ongoing oversight from
the project staff, including site visits to observe progress and provide targeted technical as-
sistance – leveraging, where possible, existing project efforts and staff. Time was set aside
at the quarterly network meetings for mentors to share lessons learned and challenges faced
in order to improve their performance.
Compliance to the mentorship program is moderately high. Of the businesses randomized
to receive the mentoring treatment, 77.6% report to have attended at least one session with
their mentors.
Business Convention/Networking
The third component of this intervention created networks and linkages between mentors
and mentees at sessions, forums and workshops, including encouraging the use of digital
networking via email, blogs and social network. This created opportunities to develop new
businesses, learn about new opportunities, solve problems and increase visibility for both,
mentors and mentees. As a result, networks were created at the regional as well as national
level, and 87.9% of treatment mentors and 68.4% of treatment mentees attended at least
one regional networking session.
2.3 WALN Selection Process and Program Cost
ACDI/VOCA solicited applications from high-potential women agribusiness entrepreneurs in
Ethiopia through advertisements and community mobilization. Women eligible to participate
in WALN had to be owners or managers of a registered business or association at the time
of enrollment; active at any point in one of the 9 selected value chains in the targeted
regions; holders of a bank account (individual or association/business); able to nominate 6-8
11businesswomen and willing to mentor 3-5 of them; and able to provide a professional letter
of recommendation in support of their application.
Women who met the eligibility criteria for participating in the WALN project—as outlined
in Appendix Table A.2—who completed the application form, provided at least one letter of
recommendation and nominated five to eight mentees were considered in the pool of potential
mentors who would receive the business and leadership training. Mentees were selected from
among the nominated candidates who met the corresponding eligibility criteria. Mentees
were assigned only to the mentors who nominated them. To minimize non-compliance and
maximize the effectiveness of existing network ties, if multiple mentors nominated the same
mentee, the mentee would be allowed to pick the mentor.
Altogether, approximately $2,400 was spent per treatment mentor, while approximately $500
was spent per treatment mentee. Because of data limitations, the cost of attending several
forums, workshops and conference participation cannot be disaggregated from the basic cost
of business training and mentoring.
3 Experimental Design and Data
Randomization
The pool of eligible applicants became the sample for the baseline survey. Treatment was
then randomly assigned to eligible applicants who responded to the baseline survey. The
WALN project operated in Ethiopia’s Agricultural Growth Program’s (AGP) target woredas
of five regions of Ethiopia: Tigray, Amhara, Oromia, Addis Ababa and SNNPR. The impact
evaluation covers the business training and mentoring activities across the entire geography
covered by the project.
Business training treatment randomization was stratified by region and firm-size tercile. This
is the pool that would become the mentors in the second stage, so henceforth we refer to
them as such. Half of the mentors received formal business training covering the modules
listed above. Treated mentors came to a training facility two days a month for six consecutive
months. Control group mentors were not given any business training, but they were tracked
and surveyed in each round of follow-up surveys.
Half of the mentees of treated mentors were randomly assigned to receive mentoring, while the
remaining half were assigned to the control group. After the business training was concluded,
12mentors were asked to meet their mentees one day a month for six consecutive months.
Mentors were specifically encouraged to provide mentoring only to mentees randomly selected
to receive mentoring. However, since both treatment and control mentees belong to the
mentor’s social and business networks, there was a possibility of spillover across treatment
status among the mentees. To address this issue, we include mentees nominated by control
mentors in the impact evaluation. This helps us measure the spillover effect of being in a
treatment mentor’s network by directly comparing the outcomes of the control mentees (of
the treatment mentors) and the pure control mentees (of the control mentors—who did not
receive any business training). Appendix Table A.1 shows the sample size for both mentors
and mentees across the different survey rounds and treatment status.
We report balance tests for the mentor and the mentee samples in Tables 1 and 2, respectively,
on a set of individual, household, and business characteristics. The relative size of the mentor
and mentee businesses is evident. For example, the monthly (winsorized) profits of mentors
at baseline are approximately 3.5 times as large as those of their (potential) mentees.5 Most
of the variables are balanced across the different treatments. Imbalance in some of the
baseline variables is accounted for by controlling for them in all subsequent (and relevant)
regression analyses.
Follow-up Surveys
Table A.1 as well as Appendix Tables A.4 - A.5 show the WALN impact evaluation design
in detail, and in particular, the number of women surveyed in each round of data collection
as well as the attrition in the sample from baseline through three post-intervention follow-up
data. At baseline, we have a sample of 197 mentors - 99 treatment and 98 control mentors.
The mentee sample, on the other hand, consists of 295 treatment, 294 spillover and 539
control mentees. Given the small initial sample of mentors, we placed a premium on follow-
up. As observed in Tables A.1, A.4 and A.5, overall attrition is low and does not vary by
treatment status.
The WALN baseline survey was conducted from March to August 2014. Business training
took place from August to December 2014 and this was followed by mentoring sessions from
January to July 2015. The first follow up survey took place between August and December
5
The large, albeit statistically insignificant, differences in raw profit and revenue at baseline between
treatment and control mentors (as well as between treatment and control mentees) is driven by a handful
of (two or three) firms which are mainly large cooperatives. Rerunning all the estimates by dropping these
firms produce very similar estimates for all the relevant analysis, implying that these large firms do not drive
the main results.
132015, while data collection for the second follow-up was carried out in the summer of 2017.
Data collection for the final and the third follow up was carried out in February-April, 2018.
4 Outcomes of Interest and Estimating Equations
4.1 Outcomes of Interest
Due to the fact that we have a number of variables which capture similar or identical con-
structs, we have regrouped the variables of interest into families of outcomes whenever it
was possible to do so. For each family of outcomes, we have created an average z-score index
by ensuring all variables in the outcome were coded in the same direction, calculating the
z-score of each variable by subtracting the control-group mean and dividing by the control
group standard deviation, and averaging the z-scores of the outcomes for each family.
The individual outcome variables that were used to create the following family of outcomes
are explained in Appendix Section A.1. Given the goals of the intervention we focus on
a top level of outcome of profits and revenues (combined into an index) and a secondary
(mechanisms) index of business practices. To better understand how the intervention worked,
the business practice index is broken out into marketing, stock control, record keeping and
financial planning indices.
4.2 Estimating Equation: Basic Treatment Effects
Business Training
We measure the basic (intent-to-treat) program effects of the business training in the follow-
ing ANCOVA specification:
k
yi,t = β0 + βT BusinessTrainingi + β1 Y i,0 + θs 1(i ∈ s) + δj 1(j = t) + εi,t (1)
X X
j=1
where yi,t is the outcome variable of interest (e.g., profit) for firm i, survey round, t; θs is
the strata fixed effects; δj survey round fixed effects; εi,t is the error term, which is clustered
14at the firm level (because of firm level randomization within a strata); Yi,0 is the lag of the
dependent variable in order to maximize power (McKenzie, 2012).
Mentoring
We can separately measure the effect of being a treatment and a ‘spillover’ mentee who
belong to the social and business network of the same treatment mentor in relation to pure
control mentees. This is done to evaluate the spillover across treatment and control mentees
of treatment mentors which can bias the treatment effects downwards.
We measure the basic (intent-to-treat) effects of receiving mentoring in the following way:
k
yi,t = β0 +βT TreatmentMenteei +βS SpilloverMenteei +β1 Y i,0 + θS 1(i ∈ S)+ δj 1(j = t)+εi,t
X X
j=1
(2)
where yi,t is the outcome variable of interest (e.g., profit) for firm i, survey round, t; θs is the
strata fixed effects; δj survey round fixed effects; εi,t is the error term, which is clustered at
strata level; Yi,0 is the baseline value of the dependent variable in order to maximize power..
The omitted category in the above regression is the (pure) control mentee.
5 Results
As indicated in Equations (1) and (2), our primary specification is an intent-to-treat analysis
using all the follow-up rounds pooled together, with the baseline value of the dependent
variable used on the RHS in order to maximize statistical power. Tables 1 and 2 show
that the treatment and control arms in the business training and mentorship programs are
balanced at baseline for most of the relevant observables.
5.1 Impact on Mentors
We test the hypothesis6 that a business training improves business performance by looking
into an index of profit and revenue as well as their individual components (Table 3). Given
6
as pre-specified in our analysis plan
15the relatively small sample size, we pool impacts over the three post-treatment waves to
maximize statistical power, with the coefficients then representing the average impact over
3 years post-treatment. Point estimates suggest large and statistically significant impacts of
attending the business training on revenue and profits. The profit and sales index suggests
an improvement of 0.21 standard deviation. The estimates for the winsorized revenue and
profit variables suggest a pooled impact of 62% and 80%, respectively.
Table 4 shows the impact of the business training intervention on business practices that
were covered extensively in the training curriculum. Point estimates suggest that treatment
mentors fare markedly better in terms of the business practices identified by McKenzie and
Woodruff (2016) as well as Bloom and Van Reenen (2007) and Bruhn, Karlan, and Schoar
(2010). The business practices index suggests an improvement of 0.13 standard deviation
(Table 4), with the largest gain observed for marketing practices (a 0.14 SD improvement over
control mentors). Record-keeping and stock control show improvements similar in magnitude
to marketing practices while financial planning improves by 0.08 SD for treatment mentors
compared to control mentors.
Digging deeper into which particular practices may be driving these results, Appendix Ta-
bles A.6 - A.9, show the disaggregated results for the underlying 26 business practices for
marketing practices, record-keeping, stock control and financial planning. Specifically, treat-
ment mentors are 21.4 percentage points (49.5%) more likely to have written business records
than control mentors (Table A.8). A similar magnitude of impact holds for keeping finan-
cial records for every purchase and sale; using records to calculate cash on hand; and using
records to evaluate whether sales of a particular product were increasing or decreasing from
one month to another. Treatment mentors were also found to have negotiated or attempted
to negotiate with suppliers for a lower price on raw materials -- 16 percentage points (27.4%)
higher than the control group (Table A.7). Similarly, marketing practices show strong and
positive movements as a result of the business training (Table A.6). Treatment mentors are
more likely to visit at least one of their competitors’ businesses to see what prices they are
charging or what products they are selling. Treatment mentors are also 17 percentage points
more likely to attract customers with a special offer; 19 percentage points more likely to
ask suppliers which products are selling well in this business industry; and 20 percentage
points more likely to ask at least one former customer to find out why former customers have
stopped buying from this business. While a fairly wide range of practices are changing, it is
also worth noting that a number of these effects are large in magnitude.
In addition to changes in practices, Table 5 documents some evidence of diversification.
Treatment mentors have an average of 0.23 more businesses, indicating that the training
16has spurred some business creation. Qualitative work also indicates that one entrepreneur
opened a supermarket as an outlet for the dairy products she was processing.
Distribution of treatment effects
Figure A.1 shows that, relative to control mentors, the distribution of monthly profit and
revenue z-score is shifted to the right for treatment mentors. This suggests that the differ-
ences in the means of treatment and control mentors are not being driven by a small number
of firms but rather that profits and revenues are generally higher among treatment mentors.
A Kolmogorov-Smirnov test rejects the null hypothesis that the two distributions are equal
at the 1 percent level.
5.2 Impact on Mentees
We test the hypothesis that the mentoring component of this project improves business
performance of mentees by looking into an index of profit and revenue as well as their
business practices. Since (treatment) mentors were assigned to work with a random subset
of their mentees, it is possible that they either spoke about the practices they had learned
with all of their potential mentees or that mentees spoke with each other, since they were
part of the same pre-existing social network. Given the possibility of spillovers, we compare
treatment and spillover mentees within the same regression framework. This allows us to
separately measure the effect of being a treatment and a ‘spillover’ mentee who belong to
the social and business network of the same treatment mentor in relation to pure control
mentees. We also test whether there is jointly no treatment effect and no spillover effect,
and whether the spillover effects are equal to the treatment effects.
In Table 6, we examine impacts on profits and revenues. Similar to the business training, we
pool impacts over the three post-treatment waves to maximize statistical power, with the
coefficients then representing the average impact over 3 years post-treatment. Although the
point estimates are mostly positive, they are quite small and the impact of the mentoring
component is not statistically significant for revenues, profits, or an aggregated index of these
measures.
In Table 7, we examine the impact of being mentored on business practices. We find statisti-
cally significant impacts on almost all of our measured business practices, for both treatment
and ‘spillover’ mentees, suggesting strong spillover effects. Point estimates suggest that both
treatment and ‘spillover’ mentees do better in terms of some of the key skills identified by
17Mckenzie and Woodruff (2016) as well as Bloom and Van Reenen (2007) and Bruhn et al.
(2010) and which were covered extensively in the first-stage business training (for mentors).
Mentors were encouraged to disseminate the importance of the business practices while con-
ducting the subsequent mentoring sessions and we see an indication that the knowledge
permeated their networks.
The business practices index suggests an improvement of 0.28 standard deviation for treat-
ment mentees, with the largest gain observed for marketing practices (a 0.27 SD improvement
over control mentors). Record keeping, stock control and financial planning, similarly, show
improvements in the range of 0.18 and 0.27 SD for treatment mentees compared to pure
control mentors. The magnitude of the impact on ‘spillover’ mentees is similar in size to the
treatment mentees; in fact, we fail to reject the hypothesis that the coefficients for treatment
mentees and spillover mentees are equal for indices of the four different types of business
practices (although, as one might expect, the point estimates are lower). These results
indicate widespread spillover impacts among the control mentees of treated mentors.
In Table 8, we see a (marginally) statistically significant impact of being mentored on the
index of business expansion, which is comprised of the total number of businesses that the
mentees have, as the number of unique products that they sell and their number of employees.
There is no significant impact on the spillover mentees, which would be consistent either with
the lower point estimates of changes in skills or that the mentoring had a wider range of
impacts when it was a direct, rather than indirect, relationship.
Taken together these results show that the treatment impacted the practices, but apparently
not the profits of the mentees of the treated mentors. This is counter to the results of
the mentors, who show a change in both practices and profits. The lack of effect of being
mentored on the business profits could possibly be attributed to the fact that it was unable to
induce large enough changes in the business practices of the mentees. This is consistent with
Mckenzie and Woodruff’s (2016) argument that the relationship between ‘better’ business
practices and performance is causal and that the lack of effect for existing business trainings
is because they do not change business practices enough rather than because these practices
do not matter. Along the lines of Mckenzie and Woodruff (2016), we investigate whether
the effect of the mentoring treatment on profit is consistent with the predicted effect given
the observed changes in business practices, to which we now turn.
Business practices and profits for mentees - Power issues
The point estimate for the impact of mentoring on winsorized profits as seen in Col (3) of
Table 6, is 216 Ethiopian Birr (ETB), which is 14.4% of the (pure) control mean. A 95%
18confidence interval is [-97 ETB, + 533 ETB] or [-6%, + 35%] which allows for mentoring to
have had a relatively sizable impact on profits; just that there is no power to detect them.
Among the (pure) control mentees, a positive and statistically significant correlation between
business practices and business outcomes is observed. Table 9 shows that a 1 SD increase
in the business practice score is associated with an improvement in (winsorized) profit by
822 ETB7 . If we multiply this by the mentoring treatment effect on business practices in
Table 7 (mentoring causes an improvement of business practice index by 0.27 SD) we get an
estimate of how much the change in business practices is likely to change profits, which is
0.27 x 828 ETB = 223.6 ETB. Not only is this within the confidence interval of the estimate
of profits, it’s also quite close to the point estimate of 216 ETB for the mentoring treatment
effect on business profit.
6 Conclusion
The Women in Agribusiness Leaders Network (WALN) project is an interesting departure
from the standard business training model. Under a stratified randomized controlled trial
framework, experienced business women who were involved in agriculture-related businesses
were given formal business training. The more innovative part in this project is a second-
stage mentoring component in which a random selection of women mentees within the social
and business network of mentors received customized mentoring from the trained mentors.
Over a post-training period of three years, we find that formal business training for the
mentors causes large impacts on business performance such as reported profits as well as the
number of business activities. This effect appears to be driven by the continued adoption of
several of the ‘better’ business practices identified by McKenzie and Woodruff (2016).
Given the extent of micro-entrepreneurial activities in developing countries, it is also im-
portant to identify low-cost interventions that can lead to the adoption of these business
practices that may improve performance for small businesses. Mentoring could be a rela-
tively low-cost solution to this problem. We tested this by connecting trainees of the formal
business training to a random subset of small firm owners within their social and business
networks and evaluate the outcome of the treatment mentees compared to control mentees
7
McKenzie and Woodruff (2016) report an increase of profits in the range of 65% to 100% for a 1 SD
improvement in business practices score. Among the pure control mentees in our sample, this association is
at 91% (Table 9). This comes with a caveat - we use IHS transformations whereas McKenzie and Woodruff
(2016) use log transformations for profits.
19(who did not receive the mentoring). We find that the treatment mentees exhibit strong
effects in the adoption of some business practices; however, this does not translate to higher
profits. The apparent muted results for the impact of mentoring on profits are consistent
with the lackluster results from recent evaluations of business mentoring such as Brooks,
Donovan, and Johnson (2018).
It is, however, possible that the adoption of practices observed among treatment mentees
is not of a large enough magnitude to change profits substantially. We find some evidence
for this possibility—the effect of mentoring on profit is consistent with the predicted effect
given the observed changes in business practices. This is similar to the exercise carried out
by McKenzie and Woodruff (2016), in which they show that the modest observed effects of
business training on profits and sales in six developing countries are remarkably consistent
with the predicted effects given the observed changes in business practices.
7 Tables
20Table 1: Mentor Baseline Balance (comparing Treatment vs. Control Mentors)
(1) (2) T-test
Control Mentor Treatment Mentor Difference
Variable N Mean/SE N Mean/SE (1)-(2)
Monthly Profit (Raw) 76 17982.593 83 1.04e+06 -1.02e+06
(10186.831) (1.00e+06)
Monthly Profit (Winsorized) 76 5751.117 83 5816.470 -65.353
(1194.538) (1036.791)
Monthly Revenue (Raw) 96 72306.990 97 42861.835 29445.155
(52534.630) (17733.741)
Monthly Revenue (Winsorized) 96 14171.573 99 15834.323 -1662.750
(2649.646) (2982.843)
Number of products 98 5.531 99 5.556 -0.025
(0.840) (0.892)
Total Num. of Businesses 98 1.531 99 1.687 -0.156
(0.076) (0.090)
Owner’s age 98 37.500 99 37.424 0.076
(0.919) (0.924)
Owner’s Years of School 98 9.214 99 9.808 -0.594
(0.525) (0.488)
Operational years of business 96 6.823 94 7.787 -0.964
(0.519) (0.634)
Owner’s years of bus. experience 98 11.031 99 11.697 -0.666
(0.797) (0.800)
Baseline Prac. Score (%) 98 30.952 99 39.057 -8.105
(3.495) (3.889)
Has Bus. Plan 98 31.633 99 40.404 -8.771
(4.722) (4.957)
Has Annual Budget 98 22.449 99 30.303 -7.854
(4.236) (4.642)
Has Financial Record 98 38.776 99 46.465 -7.689
(4.947) (5.038)
Notes: The value displayed for t-tests are the differences in the means across the groups. Fixed
effects using stratas are included in all estimation regressions. ***, **, and * indicate significance at
the 1, 5, and 10 percent critical level.
21Table 2: Mentee Baseline Balance (comparing Pure Control, Spillover and Treatment Mentees)
(1) (2) (3) T-test
Pure Contr. mentee Spillover Contr. Mentee Treatment Mentee Difference
Variable N/[Clusters] Mean/SE N/[Clusters] Mean/SE N/[Clusters] Mean/SE (1)-(2) (1)-(3) (2)-(3)
Monthly Profit (Raw) 531 2433.547 283 61300.992 283 10409.782 -5.89e+04 -7976.235 50891.210
[90] (510.955) [94] (58946.793) [94] (7164.466)
Monthly Profit (Winsorized) 531 1374.332 283 1657.882 283 1712.992 -283.550 -338.660* -55.110
[90] (124.080) [94] (142.270) [94] (164.861)
Monthly Revenue (Raw) 531 15236.655 291 17223.773 292 42132.318 -1987.118 -2.69e+04 -2.49e+04
[90] (6666.054) [94] (5105.080) [94] (23805.750)
Monthly Revenue (Winsorized) 539 5484.071 294 6854.976 295 6703.041 -1370.906 -1218.970 151.936
[90] (497.579) [94] (695.983) [94] (644.533)
Number of products 539 4.824 293 5.604 295 5.003 -0.780 -0.180 0.601
[90] (0.510) [94] (0.708) [94] (0.550)
Total Num. of Businesses 539 1.468 294 1.374 295 1.393 0.093 0.074 -0.019
[90] (0.038) [94] (0.043) [94] (0.044)
Owner’s age 538 35.626 293 35.188 295 34.786 0.439 0.840 0.401
[90] (0.586) [94] (0.784) [94] (0.685)
Owner’s Years of School 539 7.492 294 7.694 295 8.244 -0.202 -0.752* -0.550
[90] (0.361) [94] (0.376) [94] (0.319)
Operational years of business 493 7.473 267 6.719 271 7.018 0.754 0.454 -0.299
[90] (0.713) [92] (0.551) [93] (0.497)
Owner’s years of bus. experience 539 10.477 294 9.918 295 9.793 0.558 0.684 0.125
[90] (0.706) [94] (0.646) [94] (0.554)
Baseline Prac. Score (%) 539 12.554 294 14.286 295 18.644 -1.732 -6.090* -4.358*
[90] (1.647) [94] (1.992) [94] (2.457)
Has Bus. Plan 539 11.317 294 14.286 295 17.627 -2.968 -6.310 -3.341
[90] (1.962) [94] (2.430) [94] (2.821)
Has Annual Budget 539 8.905 294 6.463 295 12.881 2.443 -3.976 -6.419***
[90] (1.595) [94] (1.910) [94] (2.583)
Has Financial Record 539 17.440 294 22.109 295 25.424 -4.669 -7.984** -3.315
[90] (2.220) [94] (2.885) [94] (2.997)
Notes: The value displayed for t-t ests are the differences in the means across the groups. Fixed
effects using stratas are included in all estimation regressions. Standard errors are clustered at the
mentor level. ***, **, and * indicate significance at the 1, 5, and 10 percent critical level.
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