Some examples of the work of the Africa Gender Innovation...

Salman AlibhaiMarkus 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

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

Profits

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

Crossing the divide

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

Information matters

Non-crossovers’ beliefs on profitability (Ethiopia)

• 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

Policy

• 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

Opportunities?

Fact 1: Lots of youth

Fact 2: Girls are less likely to be working

Fact 1: Lots of youth

Opportunities?

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%

And changing gender roles in Uganda

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


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


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?

How it usually works

TraditionalScreening Collateral

You’re out You’re out

Yes

No No

Loan

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

Solution?

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 usually works



Yes

No No

Loan

How it works now



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

Sample Questions

Screening in Ethiopia

Constant Development

• Iterative process

• Scoring model constantly incorporates new data

• Aim is to develop an accurate ‘local’ model

How is it going, so far?

With more, rigorous evidence to come…

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

Some examples of the work of the Africa Gender Innovation...

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