Salman Alibhai Markus Goldstein Some examples of the work of the Africa Gender Innovation Lab
• Figure out what works and what does not to improve gender equality and use it to shape policy
• How? – Rigorous inferential work to understand problems– Target (and help develop) innovative interventions– Impact evaluations (50) of government, donor, NGO, private company
programs• What for?
– Estimates of gender gaps in productivity the cost of inaction
– Identified programs that work the right action
– The benefits of action, vs. the cost the payoff
What is the Gender Innovation Lab?
1. Men’s jobs vs. women’s jobs2. Empowering adolescent girls3. Business training for the mind4. Lending without collateral
Today
1. Men’s jobs vs. women’s jobs2. Empowering adolescent girls3. Business training for the mind4. Lending without collateral
Today
Industry segregation patterns
Men’s jobs vs. Women’s jobs:It happens in Mexico and in Sweden
Source: World Development Report 2012
• For economic growth:– In 1960, 94% of US doctors and lawyers were white men. By 2008
this was 62%• This decline in segregation contributed 15-20% of the
aggregate growth in output per worker (Hsieh, et. al. 2013)
• And for enterprise performance– Once you control for sector of operation, the differences in profits
between male and female firms in Sri Lanka disappear (de Mel, et. al. 2009)
And it matters
But there are women who defy the odds
Today: 2 studies• Ethiopia: survey of
entrepreneurs• Uganda: survey, plus life
histories and focus groups with community members/leaders
Sector is important for earnings (Uganda)
Monthly profit by sector among informal enterprises in Uganda
$296
$371
Metal Fabrication Electricals
$86
$148
Saloons Catering
Crossing over is more profitable
0
100
200
300
400
500
600
700
800
crossovers non-crossovers
Profits in the last month (USD) - Ethiopia
And when they crossover, they make the same as men
$217 $221
$-
$50
$100
$150
$200
$250
Male Female cross over
Comparison of Monthly profits in male dominated sectors: Males vsfemales
In both Ethiopia and in Uganda (shown here)
What it’s NOT: Education
0
10
20
30
40
50
60
Primary education Secondary education Post secondary education
Crossovers Non-Crossovers
• Interestingly a wide range of these characteristics do not seem to differ between cross-overs and non-crossovers including:
• Digit span score• Raven test score• Self efficacy score• Achievement striving score• Impulsiveness score• Passion for work score• Tenacity score• Locus of control score
What it’s NOT: cognitive and non-cognitive skills
• Women did not choose the sector for capital requirements
• But could delay start
Uganda
Finance does not seem to be a factor in sector selection
• A woman’s first job matters – there is path dependence
• Parental occupation matters (Ethiopia) with positive effects from wage work but not farms
• Having the right type of mentorship and exposure are key
In both contexts
Psycho-social factors matter
• Crossovers are twice as likely to have a male role model compared to non-crossovers
• Crossovers are 3.5 times more likely to be introduced to their sector by their father or other male family member
• Non-crossovers are 15 times more likely to be introduced to their sector by their teachers.
“Through his encouragements [and] help, I kept my savings until I got what was enough to start up. He mentored me after I finished my diploma”
“My spouse was in carpentry when we married. His friend taught me the skill because my spouse wanted me only to manage and do sales for him”.
Male mentors matter
• Work with teachers so that they stop sending girls to be caterers and boys to be carpenters
• Target technical and vocational training to encourage switching– Example of Kenya auto mechanics
• Apprenticeship programs that provide incentives for girls to switch and build in the right kind of mentors
Start young
• Information is clearly a problem– Work in information through the education system– But also make it more widely available (adult switchers?)
• Can we do this in business training (for adults), or is it too late? – Lots of switching for folks going through business training
programs– Can we bring in the right set of information and mentoring to
help open up the occupational space?
Markets and mentoring
1. Breaking the metal ceiling2. Empowering adolescent girls3. Business training for the mind4. Lending without collateral
Today
Fact 3: they are having more children, younger
Opportunities?
Fact 1: Lots of youth Fact 2: Girls are less likely to be working
For girls, adolescence is the critical time to intervene
• Risk of HIV/STI, unintended pregnancy
• Early motherhood can limit future earnings (path dependence)
• Barriers to labor market entry– smaller networks/access to information– domestic work burden– concurrent labor market/fertility
decisions.
So how about a program that targets girls?
• Think about ways to facilitate the school to work transition1. Need to take into account
constraints unique to girls2. Possibility of multi-dimensional
intervention – not just job training, but other skills – both in their daily life (e.g. health) and “soft skills” for jobs
1. EPAG - Liberia
• $4m, funded through WB AGI• Target girls age 16-27 with:
1. Job or Business Skills training (6 months)
1. Placement/start-up support (6 months)
2. Life skills, e.g., communication, leadership, GBV.
• Led by Ministry of Gender, implemented by NGOs
2. ELA - Uganda
• Run by BRAC, funded by Mastercard & Nike
• Target girls 14-20 with: 1. Safe social space 2. Life skills training (focus
on reproductive health)3. Short livelihood training
based on local market4. In future: microfinance
How will we know if it works?
• Why evaluate? – Girl space filled with lots of advocacy,
but what about rigorous evidence on what works, what are the payoffs?
• Our approach: randomized control trials– Liberia: phase-in, 1300 girls in the first
wave– Uganda: 100 villages in program, 50 in
control
So, we collected lots of data
• Uganda: 4888 girls, 2 interviews, 2 years apart• Liberia: 1620 girls, 2 interviews, 1 year apart
• Wide range of outcomes: not just employment but also: self-confidence, savings, expenditures, health, GBV, time use, etc.
Did it work? Liberia
In terms of employment and earnings:
Employment 47%
Earnings 32 USD per month (80%) • Stronger effects for Business Skills trainees than for Job
Skills trainees
Savings by 36 USD
Did it work? UgandaEmployment and earnings outcomes:
Engagement in IGAs by 72%• Driven by self-employment activities
Spending on themselves by 38%
No adverse effects on schooling outcomes, e.g. enrollment or time spent on studying
Impacts beyond economics in Uganda
Fertility: reported motherhood decreases by 26%
Proportion of those always using a condom increases by 26%
No effect on use of other contraceptives or reported STDs
Incidence of sex against their will drops by 41%
Impacts beyond economics in Liberia
No impact on fertility – actual or desired
No impacts on contraception, # of boyfriends, incidence of GBV
Positive impacts on self confidence, satisfaction with job outcomes
Is it worth it? Liberia
• Cost per beneficiary:– 1650 USD for Job Skills track– 1200 USD for Business Skills track
• Compare to 700-2000 USD for Jovenesprograms in Latin America
• Set this against average monthly increase in earnings: – 2 years to recoup investment (Business Skills)– 8 years to recoup investment (Job Skills)
Is it worth it? Uganda
• Cost per potential beneficiary is $17.9 in year 2
• Corresponds to– .54% of hh income at baseline– 21% of a girl’s self-reported annual
expenditures
• Set this against: – increase in employment– lower fertility– drop in sex against her will
1. Men’s jobs vs. women’s jobs2. Empowering adolescent girls3. Business training for the mind4. Lending without collateral
Today
• Commonly believed (by governments, NGOs, International Development Agencies) that entrepreneurs could have higher profits if they had better skills
• Evidence so far? McKenzie and Woodruff (2013)– Most rigorous studies find entrepreneurs (modestly) implement the
practices they are taught – Few find impact on profits– Results are weaker for women
• Are skills not the problem? Are we training the wrong people? Are we teaching the wrong things?
Skills training: The evidence so far
An innovation: personal initiative training
Personal Initiative
Being self-starting
Future thinking
Overcoming barriers
Goal setting
Planning
Innovation & creativity
Successful small businessFinancing
(Bootstrapping)
Feedback
© Frese Group
• Self starting means that you have to:– spend energy– face uncertainties and obstacles while trying new ways– take some risks– keep on trying in spite of obstacles!!!
• Exercise: – in groups of 2, write down all of your daily business activities
yesterday.– Now analyze: what was not good, where have you been passive and
reactive, where did you not act self-starting? Write down or draw all good and self-starting behavior you showed.
A sample of the training
o Accounting and financial managemento Customer relations and marketingo Human resource managemento Negotiationo Fiscal obligations and government regulations
• Both trainings: 12 half day sessions plus 4 months of personalized mentoring (3 hours per month)
Business Edge
We compared PI with a more standard business training in Togo
Preliminary results
Which works better for women?
Compared to PI, Business Edge lead to: Higher record keeping and
financial management practices More likely to have a business
bank account
Compared to BE, Personal Initiative lead to: Significantly higher assets More capital investments More workers More paid workers More likely to introduce new
products or services Borrowing higher amounts of
moneyWhere they are equally effective: Other business practices (marketing, HR, seeking new information) Firm changed sector of activity Introduce new processes networks
• Women have higher returns to certain skills (non-cognitive skills) than men do
• With limited evidence so far, these skills seem to matter (in a range of contexts) more when faced with adversity or systemic disadvantages
• We can train women in these skills, with success. And it makes a difference for their business outcomes
Summing up: skills
1. Men’s jobs vs. women’s jobs2. Empowering adolescent girls3. Business training for the mind4. Lending without collateral
Today
• Microfinance worldwide: – $60-100 billion in capital– 200 million clients, most of them women– Rigorous evidence: modest but not transformative enterprise
effects
• But for banks, women are disadvantaged. In developing countries:– women are 20 percent less likely than men to have an
account at a formal financial institution– 17 percent less likely to have borrowed formally in the past
year– And loan sizes tend to be smaller
Credit for women. Credit for business?
Gender Aspect
Collateral requirements are particularly constraining for women entrepreneurs
Women often do not … own; or… hold formal titles over
assets that can be pledged as collateral
Why focus on Psychometrics?
Psychometrics or psychological measurement
Research on psychometrics has revealed a strong correlation with repayment behavior across continents
Our Innovation
• Partner with a microfinance institution/bank and financial technology startup to give loans of $2,500 to $50,000 for women in Ethiopia
• Psychometric screening of loan applicants
• Credit score, based on the predicted default rate, as collateral substitute
How it works now
TraditionalScreening Collateral
You’re out You’re out
Yes
Yes
No No
Loan
Psychometric Screening Loan
Now you’re really out
No
Psychometric Screening
Assess the Ability and Willingness to Repay
Business Skills
Intelligence
Ethics & Honesty
Attitudes & Belief
Screening Process
QuestionnaireSelf-administered (about 1h)
Scoring ModelBased on database of historic loan performance of other tested loan takers
ScoreCut-off or categorization
Constant Development
• Iterative process
• Scoring model constantly incorporates new data
• Aim is to develop an accurate ‘local’ model
Summing up: credit
• Collateral requirements can be particularly constraining for women entrepreneurs
• There is no easy or simple solution
• Piloting and rigorously evaluating an innovative psychometric scoring technology is an important step forward
• Segregation discussion based on work by Buehren et. al. (Ethiopia) and Campos et. al. (Uganda)
• Adolescent girls discussion based on Bandiera et. al. (Uganda) and Adoho et. al. (Liberia)
• These and the other projects on the web: www.worldbank.org/en/programs/africa-gender-innovation-lab
For more on this:
Thank you