Supporting Women's Economic Empowerment - Gender-Transformative Global COVID-19 Recovery Plan - Fraym
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Supporting Women’s
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Economic Empowerment
Gender-Transformative Global
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COVID-19 Recovery Plan
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J U N E 20 21
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Supporting Women’s I. Why It Matters
Economic Empowerment
II. Bilateral & Multilateral Support
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III. Country Simulations
Gender-Transformative Global a. Approach & Methods
b. Nigeria
COVID-19 Recovery Plan
c. Uganda
IV. Conclusion
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V. Appendix
a. Selecting Focus Countries
for Impact Simulations
b. References
c. About Fraym
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d. Data Sources
Fraym • Mapping Humanity 2
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Why ItRG
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Matters
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Fraym • Mapping Humanity 3
WHY IT MATTERS
Covid-19 Has Laid
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Bare Gendered
Divides Globally
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The economic fallout of COVID-19 Women have been
has disproportionately affected disproportionately burdened by
The COVID-19 pandemic is a once-in-a-century crisis. sectors with large female caregiving responsibilities, with
Well over 3 million people have died as of June 2021 workforces, including retail, children out of school and family
hospitality, and healthcare. members falling ill, which also
and entire economies have been disrupted in ways
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has negative knock-on effects
previously unimaginable. This global pandemic in terms of current and future
further reinforces how crises shine a light on the many workforce participation.
ways in which gender norms and gendered practices
disproportionately burden women and girls.
The pandemic has deepened gender inequalities
and reinforced gender stereotypes, with women and
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girls bearing the brunt of care work and disruptions
in education and employment. Compared to men
and boys, they face poorer access to health and
other essential services, and greater risk of intimate
partner violence, being dispossessed of land and Child marriage and early These developments
property, and digital and pay divides. unions are projected to threaten to expand
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increase, particularly among the gender wealth gap
the poorest families seeking and set countries back
to reduce their household years in terms of gender
size and spending. equality.
Fraym • Mapping Humanity 4
WHY IT MATTERS
From Crisis Comes Opportunity
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Despite these challenges, there are signs The global community—led by the G7 and supporting multi-dimensional programs and
of hope for a more equitable post-COVID G20 and supported by the World Bank and interventions will drive a pandemic recovery
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world, with countries recognizing a need regional multilateral development banks that helps countries build back better and
to invest in childcare and gender-based (MDBs)—has a momentous opportunity contribute to a more equitable and prosper-
violence prevention like never before. After to launch a Gender-Transformative Global ous future for all women and girls, as well
years of advocacy by local and global civil COVID-19 Recovery Plan. Such a recovery as to broader economic benefits for soci-
society and women’s rights groups, there must incorporate, at minimum, investments eties overall. By some estimates, pursuing
is a growing understanding that deep in programs proven to empower women and gender-intentional and equitable programs
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societal change is needed to build more girls through not just individual, but soci- and policies now could add $13 trillion to
equitable societies. etal change. Collectively, this approach of global GDP in 2030.1
Gender-Transformative Policy Framework
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Programs & Interventions
Caregiving
Economic Lifelines
Women’s Economic Empowerment Gender-Transformative
Pandemic Recovery
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Health Systems
Gender-Based Violence
Girls’ Education
Note 1: Madgavkar, Anu, et al. “COVID-19 and Gender Equality: Countering the Regressive Effects.” McKinsey & Company, McKinsey & Company, 15 July 2020,
www.mckinsey.com/featured-insights/future-of-work/covid-19-and-gender-equality-countering-the-regressive-effects.
Source: Fraym Fraym • Mapping Humanity 5
WHY IT MATTERS
Political
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Movements
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Political moments throughout the
year present a historic opportunity to
launch a highly ambitious and impactful
Gender-Transformative Global COVID-19
Recovery Plan.
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IDA-20 Replenishment
G20 Summit
END-2021
30-31 OCT 2021
IDA contributors, led by the G7,
At Rome, the G20 reaffirms
UNGA a global commitment to
commit to an unprecedented
SEPT 2021 replenishment agreement with an
a Gender-Transformative
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ambitious Gender-Transformative
Generation Official plenary meeting, Global COVID-19 Recovery
Recovery Plan framework and
Equality Forum high-level gatherings, Plan, including through
performance milestones.
and official commu- targeted domestic programs
30 JUNE – 2 JULY 2021
niques emphasize a and financial support for IDA
G7 Summit In Paris, bilateral and global commitment to a and other multilateral devel-
11-13 JUNE 2021 multilateral development Gender-Transformative opment banks.
agencies, private compa- COVID-19 Recovery Plan.
At Carbis Bay, the G7
nies, and non-governmental
commits to pursue an ambi-
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organizations commit to
tious Gender-Transformative
specific gender-equality
Global COVID-19 Recovery
programs and policies.
Plan, including through bilat-
eral and IDA-20 commitments
for supporting women’s
economic empowerment.
Fraym • Mapping Humanity 6
WHY IT MATTERS
Women’s Economic Empowerment Policy & Impact Framework
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In this report, we focus on one pillar of of work through the targeted provision growth, and social inclusion.1 This report
the proposed Gender-Transformative of bundled services including, produc- first analyzes similar interventions that
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Global COVID-19 Recovery Plan: interven- tive assets, business training, and modest have been rolled out in a variety of coun-
tions geared toward women’s economic cash transfers. These types of focused try contexts and then simulates a range
empowerment—that is, interventions programs can reduce extreme poverty, of potential impacts if targeted programs
that don’t just allow women to cope with measured in terms of consumption, and were launched in Nigeria and Uganda.2
economic shocks, but empower them to allow households and countries overall to
transition to more stable, profitable forms benefit through greater economic activity,
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Women’s Economic Empowerment Intervention — Policy and Impact Framework
Programs & Interventions3 Impact Effects
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Graduation-Style Approach Household Consumption (↑)
Vocational Training Employment (↑)
Digital and Financial Inclusion
Economic Productivity (↑)
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Education
Decision-Making Power (↑)
Family Planning
Note 1: For example, a 2020 McKinsey report builds on the McKinsey Global Institute’s (MGI’s) Power of Parity work to estimate that taking action now could increase 2030 GDP by $13 trillion
relative to the “do-nothing” scenario. A 2016 report using the same Power of Parity work finds that the economic benefits of narrowing gender gaps are six to eight times higher than the social
spending required.
Note 2: Country simulations were restricted to Nigeria and Uganda due to the lack of recent geo-tagged household consumption and spending survey data for the other target countries.
Note 3: Programs and interventions to support women’s economic empowerment are multi-faceted and wide ranging. This list is not exhaustive of the many policies that can contribute to
empowering women. Fraym • Mapping Humanity 7
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Bilateral &
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Multilateral Support
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Fraym • Mapping Humanity 8
BILATERAL & MULTILATERAL SUPPORT
Past Funding
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Over the last decade, multilateral and bilateral donors have increased invest-
ments in skills training and economic empowerment support programs. These
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programs have shown promise and have the potential to be scaled significantly
through a Gender-Transformative Global COVID-19 Recovery Plan.
Economic Empowerment ODA Disbursements — Multilateral Agencies, G7 Countries, and Other DAC Countries1
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Low-Income Country Recipients
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G7 Countries M
G7 Countries Multilaterals Othe
G7 Countries Multilaterals Other DAC Countries
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Note 1: In this instance, we categorize economic empowerment disbursements as combining several sectors, including basic life skills for adults, vocational training, advanced technical
and managerial training, employment creation, informal/semi-formal financial intermediaries, education/training in banking and financial services, business development services, and
SME development. These disbursements are not necessarily strictly targeted at women however, unlike our analysis.
Source: OEDC-DAC Creditor Reporting System (CRS). The World Bank country classifications are used to define low-income and lower-middle income countries. Fraym • Mapping Humanity 9
BILATERAL & MULTILATERAL SUPPORT
IDA Support
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Multilateral organizations and G7 countries have been
the largest supporters of economic empowerment
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programs, accounting for over half of all related donor
assistance over the last decade.
Economic Empowerment ODA Disbursements — G7 Countries and IDA1
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Low-Income Country Recipients
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Note 1: Economic empowerment disbursements combines several sectors, including basic life skills for adults, vocational training, advanced technical and managerial training,
employment creation, informal/semi-formal financial intermediaries, education/training in banking and financial services, business development services, and SME development.
These disbursements are not necessarily strictly targeted at women however, unlike our analysis.
Source: OEDC-DAC Creditor Reporting System (CRS). The World Bank country classifications are used to define low-income and lower-middle income countries. Fraym • Mapping Humanity 10D
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Country
Simulations RG
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a. Approach & Methods
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b. Nigeria
c. Uganda
Fraym • Mapping Humanity 11COUNTRY SIMULATIONS
Approach
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Fraym has simulated the potential based upon initial rollout opportu- MEASURABLE
effects of measurable, actionable, nities and constraints. Longer-term
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and effective programs designed opportunities to deliver fully scaled
to support the economic empower- up and sustainable program coverage
ment of women. These simulations for all target beneficiaries including
apply a range of assumptions drawn traditionally marginalized groups are ACTIONABLE EFFECTIVE
from peer-reviewed studies as well as considered and presented as well
sequencing of programmatic coverage (e.g., “Path to 2030 & beyond”).
1 2
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To pursue the simulation, Upon identifying an To simulate the policy at a national Using the effect from prior
Fraym identified policies intervention for simulation, level, Fraym considered a range studies, Fraym estimated the
that are measurable in existing Fraym defined the target of effect sizes, recognizing the projected impact of the programmatic
national household surveys, population (e.g., individuals challenges with external validity and intervention. The long-term projections
actionable and well-studied eligible for the program) scaling interventions to full coverage reflect an aspiration of fully scaled up
by the policy and global and the outcome of interest, of target beneficiaries. Fraym then coverage across all target beneficiaries
development communities, and (e.g., most common impact applied assumptions to initial- and within the entire country, whereas
found to be effective. Fraym indicator) based upon a longer-term rollout impact effects. initial rollout projections focus on a
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selected graduation-style broad range of peer-reviewed The range of impact can be considered sub-set of all target beneficiaries in a
programs as the exemplar studies of graduation-style as the best a country could do if such a way that may reflect near-term fiscal,
intervention, which typically interventions in developing policy was fully scaled up and applied capacity, and operational constraints.
provide productive assets along countries. to all respective beneficiaries.
with vocational training and
modest cash transfers.
Fraym • Mapping Humanity 12COUNTRY SIMULATIONS Program
Impact
Selected
Country Program Description (Household
Name
Consumption)
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This program targeted ultra poor, rural women in West Bengal, many of
Exemplar
BRAC
them dependent on begging or wage labor. Beneficiaries were given a 18-19%
India Graduation
productive asset of their choice, asset training, cash transfers, savings increase2,3
Program
support, and home visits.
Intervention
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BRAC
South This program targeted ultra poor women in Yei county. Beneficiaries were 23%
Graduation
Sudan given a productive asset of their choice, asset training, and cash transfers. increase 4
Program
Academic evaluations have found BRAC This program targeted ultra poor women in Northern Ethiopia, many of them
that graduation-style programs— 19%
Ethiopia Graduation food insecure. Beneficiaries were given a productive asset of their choice,
increase3,5
which provide women with produc- Program asset training, cash transfers, savings support, and home visits.
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tive assets (e.g. livestock, sewing
machines), business training, and BRAC
This program targeted ultra poor women in the Northern and Upper East
regions of Ghana. Beneficiaries were given a productive asset of their 19%
other resources—consistently raise Ghana Graduation
choice, asset training, cash transfers, savings support, home visits, and increase3,6
household consumption between Program
were enrolled in the national health insurance program.
5 to 23 percent.1
BRAC This program targeted poor women, especially those with children not
2%
Honduras Graduation receiving assistance. Beneficiaries were given a productive asset of their
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increase3,7
Program choice, asset training, cash transfers, savings support, and home visits.
BRAC This program targeted ultra poor women in the Coastal Sindh region.
9%
Pakistan Graduation Beneficiaries were given a productive asset of their choice, asset training,
increase3,8
Program cash transfers, savings support, and home visits.
This program targeted ultra poor women in the rural communities of
BRAC
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Canas and Acomayo of the Cuzco region. Beneficiaries were given a 5%
Peru Graduation
productive asset of their choice, asset training, cash transfers, savings increase3,9
Program
support, and home visits.
The program targeted poor individuals, mostly women, in 120 war-affected
WINGS 29%
Uganda villages, and tried to help them start small enterprises. Beneficiaries were
Program increase10
provided with a cash grant, skills training, and ongoing support.
Note 1: This programmatic effect range reflects the majority of
examined peer-reviewed studies, with a small number of studies
that find lower or much higher effects.
Source: Fraym. For additional citations, see Appendix. Fraym • Mapping Humanity 13COUNTRY SIMULATIONS
Methodology Details
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Based on literature and available data, Fraym has estimated the potential impact
of investing in graduation-style programs in two countries. The impact simu-
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lations focus on consumption, while recognizing that these types of targeted
programs have multiple economic and social returns.1
STEP 1 STEP 2 STEP 3
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Target Population Initial Rollout (Near-Term Targeting) Range of Effect Sizes Impact Projection
Across peer-reviewed interventions, We consider a range of near-term Based on peer-reviewed intervention We simulate and then measure the potential increase in household
program eligibility was typically ultra feasibility factors, such as impact, program results, we consider the following consumption at the national and first administrative division levels.
poor, rural households. In the majority fiscal space, and government effect size range:2
We calculate these potential impact effects for the two distinct
of studies considered, a woman in delivery capacity. For these reasons, • Lower bound: 5 percent increase in phases, including: (1) initial rollout for female-headed households;
the household was the one to choose we focus on one specific sub-group: household consumption and (2) a fully scaled programmatic application that reaches all
the productive asset and to receive target households with female • Upper bound: 23 percent increase in potential target beneficiaries (i.e. poor, rural households).
subsequent training on that asset. heads. household consumption
Drawing from these eligibility
Path to 2030 (Long-Term Targeting)
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thresholds, we define the target
beneficiary population as For the long-term assumptions, we
households that: assume that all target beneficiaries Key Assumptions
would be reached effectively and
• Are in the bottom quintile of The baseline is a pre-pandemic figure and the true
sustainably.
consumption, and baseline, considering the economic shocks of the
pandemic, may be lower.
• Live in rural areas (< 300 people
Focus Outcome Indicator
per km2) Without differential effects available in the literature,
The focus outcome indicator is
Fraym assumes uniform impact.
average household consumption.
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Note 1: In addition to increases in consumption, research from JPAL and IPA finds that program participants on average had significantly more assets and savings, spent more time
working, went hungry on fewer days, and experienced lower levels of stress and improved physical health compared to those who did not receive the program. More specifically, the
study found positive returns in five of six countries, ranging from 133 percent in Ghana to 433 percent in India. In other words, for every dollar spent on the program in India, ultra-poor
households had $4.33 in long-term benefits.
Note 2: Fraym used household consumption surveys to perform these simulations. Please see the appendix for details on the exact surveys used.
Fraym • Mapping Humanity 14NIGERIA SIMULATION
Target Beneficiary Population
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In Nigeria, 8 percent of all households meet the general eligibility definition and
would be potential beneficiaries of a fully-scaled up graduation-style interven-
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tion. Overall, this totals roughly 16.8 million individuals.1
Percent of households that are potential Total number of potential candidates
candidates for a graduation-style intervention2 for agraduation-style intervention2
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Kano Kano
Abuja
Abuja
Lagos Lagos
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0 100% 0 50+
Note 1: Of these 16.8 million, 4.7 million live in female-headed households where rollout and take up of the program are most likely.
Note 2: Target households are defined as rural (< 300 people per km2) and in the bottom quintile of annual household consumption. (Source: Fraym, 2019 GHS) Fraym • Mapping Humanity 15NIGERIA SIMULATION
Estimating
Baseline (Pre-Intervention)1
Average household consumption across Nigeria is $4,000 USD
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Potential
2019 PPP annually. Among target households that figure is $1,010,
and among female-headed target households it is $760.2
Benefits
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Areas with total
population fewer
The initial rollout of a Nigerian program than 30 people
could be implemented first among per sq km
female-headed households in the target
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City Large cities
population, comprising 2 percent of the
total population or 4.7 million individuals.
Among this group, household consump-
tion could increase by 5 to 23 percent.
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Low consumption High consumption
Areas with total population
City Large cities
fewer than 30 people per sq km
Target Population Projected Impact
Initial Rollout
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Female-headed target 4.7 million individuals will live in households
households only consuming $40 to $170 more annually
Fully Scaled Coverage (‘Path to 2030 & Beyond’)
16.8 million individuals will live in households
All target households
Note 1: This map presents baseline consumption among target consuming $50 to $230 more annually
households. Urban areas are colored white because they do not
contain target households.
Note 2: Target households are defined as rural (< 300 people per
km2) and in the bottom quintile of annual household consumption.
(Source: Fraym, 2019 GHS) Fraym • Mapping Humanity 16NIGERIA SIMULATION
State-Level
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Benefits to Initial Rollout Projected Impact1
Top Five States by Target Population
Consumption
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Decisionmakers may also want to
consider focusing initial rollout in
states with particularly large concen-
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tration of target beneficiaries such as
Niger, Kogi, Oyo, Kaduna, and Borno.
Annual household consumption is
projected to increase between $50 to
$250 (USD PPP) in these five states.
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Note 1: The height of each bar represents the average annual
household consumption at baseline, using the lower bound
effect size, and using the upper bound effect size. The bars are
ordered by initial rollout target population, with Niger having the
largest. Fraym • Mapping Humanity 17UGANDA SIMULATION
Target Beneficiary Population
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In Uganda, 9 percent of all households meet the general eligibility definition and
would be potential beneficiaries of a fully-scaled up graduation-style interven-
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tion. Overall, this totals roughly 3.7 million individuals.
Percent of households that are potential Total number of potential candidates
Total number of potential candidates for1 a
candidates for a graduation-style intervention1 for agraduation-style intervention
graduation-style intervention1
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0 100% 0 50+
Note 1: Target households are defined as rural (< 300 people per km2) and in the bottom quintile of annual household consumption. (Source: Fraym, 2019 NPS)
Note 2: Of these 3.7 million, 1.5 million live in female-headed households where rollout and take up of the program are most likely. Fraym • Mapping Humanity 18UGANDA SIMULATION
Estimating
Baseline (Pre-Intervention)1
Average household consumption across Nigeria is $4,000 USD
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Potential
2019 PPP annually. Among target households that figure is $1,010,
and among female-headed target households it is $760.2
Benefits
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Based upon similar country program Areas with total population
effect ranges, the initial rollout of a fewer than 30 people per sq km
Ugandan program could be implemented
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first among female-headed households City Large cities
in the target population, comprising
4 percent of the total population or
1.5 million individuals. Among this group,
household consumption could increase
by 5 to 23 percent.
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Low consumption High consumption
Areas with total population City Large cities
fewer than 30 people per sq km
Target Population Projected Impact
Initial Rollout
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Female-headed target 1.5 million individuals will live in households
households only consuming $30 to $120 more annually
Fully Scaled Coverage (‘Path to 2030 & Beyond’)
3.7 million individuals will live in households
All target households
Note 1: This map presents baseline consumption among target consuming $30 to $130 more annually
households. Urban areas are colored white because they do not
contain target households.
Note 2: Target households are defined as rural (< 300 people per
km2) and in the bottom quintile of annual household consumption.
(Source: Fraym, 2019 NPS) Fraym • Mapping Humanity 19UGANDA SIMULATION
State-Level
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Benefits to Initial Rollout Projected Impact1
All Regions of Uganda by Target Population
Consumption
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Decisionmakers may also want to
consider focusing initial rollout in regions
with the largest concentrations of target
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beneficiaries, namely the Eastern
region. At the region level, household
consumption among the initial rollout
population is projected to increase
between $30 and $130 annually.
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Note 1: The height of each bar represents the average annual
household consumption at baseline, using the lower bound
effect size, and using the upper bound effect size. The bars are
ordered by initial rollout target population, with Eastern having
the largest. Fraym • Mapping Humanity 20D
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Conclusion
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Fraym • Mapping Humanity 21CONCLUSION
Supporting 1 2
An initial rollout of a targeted gradua- A fully scaled-up program
tion-style program promoting women’s over time could potentially
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economic empowerment could increase reach as many as 3.7 million
Women’s Economic
household consumption by as much people in Uganda and 16.8
as $170 in Nigeria and $120 in Uganda, million people in Nigeria.
impacting nearly 6 million people.
Empowerment
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3 4
The global community has a unique Specifically, the G7 Summit,
opportunity to financially support a Generation Equality Forum, G20
targeted, efficient, and sequenced Summit, and IDA20 Replenishment
The COVID-19 pandemic is a once-in-a-century
rollout of these types of economic present key political moments
crisis. The pandemic has deepened gender empowerment programs. for ambitious action.
inequalities and reinforced gender stereotypes,
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with women and girls bearing the brunt of
care work and disruptions in education and
employment. The global community—led by the
G7 and G20 and supported by IDA and regional Intervention Simulation
multilateral development banks (MDBs)—has Annual household
a momentous opportunity to launch a Gender-
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consumption could
Transformative Global COVID-19 Recovery Plan. increase as little
as $30 USD and as
This report highlights how an ambitious scaling much as $230 USD
of proven graduation-style interventions targeted
at women’s economic empowerment can support
equitable economic opportunities and contribute
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to a broader-based recovery. This includes between
1.2 million and 4.7 million impacted individuals,
respectively, in Nigeria and Uganda alone through
an initial programmatic rollout. Upper-bound, fully scaled Lower-bound, fully scaled
Upper-bound, initial roll-out Lower-bound, initial rollout
Fraym • Mapping Humanity 22D
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Appendix
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a. Selecting Focus Countries
for Impact Simulations
b. References
c. About Fraym
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d. Data Sources
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Fraym • Mapping Humanity 23APPENDIX
Selecting
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Focus Countries
for Impact
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Target Country Program Households Targeted
Simulations
978 households
India BRAC Graduation Program
in West Bengal1
2,600 households
Kenya BRAC Graduation Program
in three disricts2
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Graduation-style programs have been
rolled out in many countries across Nigeria
In Care of the People 12,500 households
the world, though typically in a limited (COPE) Program in 6 states and the capital3
number of regions. Senegal is an excep- The Sahel Adaptive Social 308,381 households
Senegal
tion, whose program covers over 300,000 Protection Program (SASPP) across the country4,5
households across the country. For this
report, simulations are limited to Nigeria South Africa None identified N/A
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and Uganda due to the lack of recent,
BRAC Youth Graduation 1,650 households
geo-tagged household consumption Uganda
Program in three districts6
data in other target countries.
Note 1: Banerjee, A., Duflo, E., Chattopadhyay, R., & Shapiro, J. Besides the above target-countries, BRAC and BRAC-style graduation programs have
(2016). The long term impacts of a “Graduation” program: Evidence
from West Bengal. Unpublished paper, Massachusetts Institute of been rolled out in other countries including Afghanistan, Bangladesh, Colombia, Ecuador,
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Technology, Cambridge, MA.
Note 2: BRAC. (2020, February). Ultra-Poor Graduation in Kenya. Egypt, Ethiopia, Ghana, Haiti, Liberia, Myanmar, Mexico, Mongolia, Nepal, Pakistan,
Note 3: Akinola, O. (2014, May). Graduation and social protection in Paraguay, Philippines, Sierra Leone, South Sudan, Tanzania, Uruguay, Yemen, and Zambia,
Nigeria: A critical analysis of the COPE CCT programme. In Interna-
tional Conference: “Graduation and Social Protection” Serena Hotel, among others.7
Kigali, Rwanda (pp. 6-8).
Note 4: World Bank Group. (2018). Sahel Adaptive Social Protection
Program. Annual Report 2018.
Note 5: World Bank Group. (2019). Sahel Adaptive Social Protection
Program. Annual Report 2019.
Note 6: BRAC. (2019, October). Youth Graduation in Uganda.
Note 7: BRAC. (2017, May). Lifting People Out of Extreme Poverty
through a Comprehensive Integrated Approach: Expert Group
Meeting UNDESA.
Fraym • Mapping Humanity 24APPENDIX
References
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Studies used to simulate the selected exemplar intervention (slide 13):
1 Fahey, A. “Building stable livelihoods for the ultra-poor.” IPA & J-PAL, Cambridge, MA (2015). Accessed: https://www.poverty-action.org/sites/default/files/
publications/building-stable-livelihoods-ultra-poor.pdf
2 Banerjee, A., Duflo, E., Chattopadhyay, R., & Shapiro, J. (2016). The long term impacts of a “Graduation” program: Evidence from West Bengal. Unpublished paper,
Massachusetts Institute of Technology, Cambridge, MA.
3 Banerjee, A., E. Duflo, N. Goldberg, D. Karlan, R. Osei, W. Pariente, . Shapiro, B. Thuysbaert, and C. Udry. “A Multifaceted Program Causes Lasting Progress for
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the Very Poor: Evidence from Six Countries.” Science 348, no. 6236 (May 14, 2015): 1260799–1260799.
4 Morel, R., & Chowdhury, R. (2015). Reaching the Ultra‐Poor: Adapting Targeting Strategy in the Context of South Sudan. Journal of International Development,
27(7), 987-1011.
5 Karlan, D. , Goldberg, N. “Graduating the Ultra Poor in Ethiopia.” Innovations for Poverty Action (IPA). (ND). Accessed: https://www.poverty-action.org/study/
graduating-ultra-poor-Ethiopia.
6 Banerjee, A., E. Duflo, N. Goldberg, D. Karlan, R. Osei, W. Pariente, . Shapiro, B. Thuysbaert, and C. Udry. “Graduating the Ultra Poor in Ghana.” Innovations for
Poverty Action (IPA). (ND). Accessed: https://www.poverty-action.org/study/graduating-ultra-poor-ghana.
7 Karlan, D., Thuysbaert, B. “Graduating the Ultra Poor in Honduras.” Innovations for Poverty Action (IPA). (ND). Accessed: https://www.poverty-action.org/
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study/graduating-ultra-poor-Honduras.
8 Karlan, D., Parienté W. “Graduating the Ultra Poor in Pakistan.” Innovations for Poverty Action (IPA). (ND). Accessed: https://www.poverty-action.org/study/
graduating-ultra-poor-Pakistan.
9 Karlan, D., Thuysbaert, B., Timura, C. “Graduating the Ultra Poor in Peru.” Innovations for Poverty Action (IPA). (ND). Accessed: https://www.poverty-action.
org/study/graduating-ultra-poor-peru.
10 Blattman, C., Green, E., Annan, J., & Jamison, J. (2013). Building women’s economic and social empowerment through enterprise: an experimental
assessment of the women’s income generating support program in Uganda.
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Additional Resources:
Abdul Latif Jameel Poverty Action Lab (J-PAL). 2015. “Building stable livelihoods for the ultra-poor.” J-PAL Policy Insights. Last modified September
2015. https://doi.org/10.31485/pi.2353.2018
“Women’s Economic Empowerment.” Bill & Melinda Gates Foundation, www.gatesfoundation.org/equal-is-greater/.
Fraym • Mapping Humanity 251
APPENDIX The primary ML model input is data from high-quality, geo-tagged household surveys.
About Fraym
Key indications of a high-quality household survey include implementing organization(s),
sample design, sample size, and response rates. After data collection, post-hoc sampling
weights are created to account for any oversampling and ensure representativeness.
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The second major data input is satellite imagery and related derived data products, including
Fraym has built machine earth observation (EO) data, gridded population information (e.g., human settlement mapping,
etc.), proximity to physical locations (e.g., health clinics, ports, roads, etc.) and biophysical
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learning (ML) software that
surfaces like soil characteristics. As with the survey data, Fraym data scientists ensure that the
weaves together geo-tagged software only uses high-quality imagery and derivative inputs.
household survey data
3
with satellite imagery to To create spatial layers from household survey data, Fraym leverages machine learning to
predict an indicator of interest at a 1 square kilometer resolution. This methodology builds
create localized population upon existing, tested methodologies for interpolation of spatial data. The resulting model is
information (1 km2).
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used to predict the survey data for all non-enumerated areas. A similar approach was originally
developed by academic researchers focused on health outcomes, which were expanded upon
by USAID’s Demographic and Health Surveys program since then by Fraym and others.1
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ACQUIRE DATA HARMONIZE DATA MACHINE LEARNING GEOSPATIAL INSIGHT
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Geo-tagged household surveys Validate Proprietary algorithms Predictive modeling
Satellite imagery Clean Human-centric QA/QC API enabled
Partner datasets Geospatially enable Automation Analytic services
Mobility data from network operators Front-end tools
Note 1: Gething, Peter, Andy Tatem, Tom Bird, and Clara R. Burgert-Brucker. 2015. Creating Spatial Interpolation Surfaces with DHS Data DHS Spatial Analysis Reports No. 11. Rockville,
Maryland, USA: ICF International. Other notable, relevant work includes: Weiss DJ, Lucas TCD, Nguyen M, et al. Mapping the global prevalence, incidence, and mortality of Plasmodium
falciparum, 2000–17: a spatial and temporal modelling study. Lancet 2019 and Tatem A, Gething P, Pezzulo C, Weiss D, and Bhatt S. 2014. Final Report: Development of High-Resolution
Gridded Poverty Surfaces. University of Southampton. https://www.worldpop.org/resources/docs/pdf/Poverty-mapping-report.pdf Fraym • Mapping Humanity 26APPENDIX
Data Sources
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The main microdata sources for this report include national
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household consumption and spending surveys and WorldPop.
Recent geo-tagged consumption and spending surveys are not
available for India, Kenya, Senegal, and South Africa.
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Fraym used national household consump- Geo-tagged Household Surveys
tion and spending surveys as the primary ML
model input. These are the latest available Country Survey
geo-tagged surveys for each country.
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2018-2019 General Household
Nigeria
Survey (GHS)
Additionally, granular population distribution
data comes from WorldPop, a publicly avail-
able and detailed population distribution and 2018-2019 National Panel Survey
Uganda
(NPS)
composition data source that leverages exist-
ing census data to produce 100m x 100m
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resolution estimates of population density.
Fraym • Mapping Humanity 27Have questions about how Fraym data can help your organization?
info@fraym.ioYou can also read
