Download Analysis of Gender and Youth Employment in Rwanda

Analysis of Gender and
Youth Employment in Rwanda
ESTA & RWFO, May 2014 - www.afdb.org
Table of Contents
Summary
1. Introduction
2. Background on labour market, gender
and Youth issues in Rwanda
2.1. Structure of the economy
2.2. Youth and affirmative action
2.3. Literacy
2.4. Population structure
3. Data sources and methods
3.1. Data sources
3.2. Variables included in the analysis
3.3. Determinants of employment
4. The Rwanda labour market
4.1. Employment
4.2. Wage versus non-wage employment
4.3. Informal sector employment
4.4. Skill status of wage employees
4.5. Education and employment
4.6. Unemployment and
underemployment
4.7. Determinants of employment
5. Conclusions and policy implications
References
This ESW was prepared by Alice Nabalamba,
Statistician, Statistics Department,
[email protected], +216-7110-2342; Edward
Sennoga, Country Economist, Rwanda Country
Office, [email protected], +216-7110-6064.
Dr. Ibrahim Kasirye (consultant) also supported the
preparation of this report. The authors wish to thank
the following people for their assistance with the
review process: Zuzana Brixovia (ECON),
Lawrence C. Tawah (ORVP), Gisela Geisler
(ORQR), Maria T.M Mdachi (ETFO), Egidia
Rukundo (ORQR) and Mary Sue Devereaux
(Consultant, ESTA)
Mr. M. Ncube
Chief Economist and Vice President
ECON
[email protected]
+216 7110. 2062
Summary
D
uring the past decade, Rwanda has
been among the fastest-growing economies in the world. Between 2000/01 and
2010/11, the economy grew at nearly 8%
per year, while income poverty declined from
59% to 45%. Although employment rates
have remained relatively stable, there has
been a substantial shift from self-employment
to wage and unpaid employment.
This study focuses on labor outcomes of
women and youth—the former have moved
into low-quality employment, while the latter
have high rates of underemployment. Labor
market outcomes are examined through geographic analysis and a study of factors affecting employment at the individual level.
The analysis is based on cross-sectional
data collected by the National Institute of
Statistics of Rwanda (NISR). The study uses
the two most recent waves of the nationally
representative household surveys for 2005/06
and 2010/11. The other source was the
2010 Rwanda Demographic and Health Survey. The methods used to meet the study
objectives were a literature review of previous
work on the Rwandan labor market, participation profiling via a descriptive analysis,
and econometric analysis of determinants of
employment outcomes.
Rwanda’s population pyramid has a wide
base, indicating a high dependency ratio.
Given that women in Rwanda still bear the
burden of child nurturing and care, this population structure suggests that women’s
employment prospects are constrained by
their reproductive and domestic roles. Between
2005/06 and 2010/11, the overall dependency
ratio fell as the percentage of the population
aged 18 or younger declined from 54% to
52%. This reduction in the percentage of
children in the total population reflects trends
in the fertility rate, which decreased from 6.2
to 4.6 children per woman during the 2005to-2010 period.
The urban population is characterized by a
“youth bulge”; that is, in urban areas, the
percentage of people aged 15 to 34 is higher
than in rural areas. This is partly explained by
rural-urban migration: 64% of youth in urban
areas were migrants, compared with 38% of
youth in rural areas.
From 2005/06 to 2010/11, the overall employment rate remained around 82% for
people aged 15 to 64. At 85%, women’s rate
was relatively high. The rate was much lower
in urban than rural areas: 76% versus 83% in
2010/11. The relatively low urban rate was
attributable to the predominance of agricultural
employment in rural areas and higher unemployment and school attendance in urban
areas. Furthermore, in urban areas, women’s
employment rate was about 5 percentage
points lower than men’s. To some extent,
this may be because urban employment
tends to require higher educational attainment,
and women’s attainment is relatively low. Employment is also affected by seasonality. Agricultural workers experience a reduction in
employment opportunities during July and
August—employment rates for July and August
were about 10 percentage points lower than
in other months.
The majority of Rwandan workers are engaged
in non-wage employment. Even so, the percentage of the labor force in non-wage employment fell from 73% in 2005/06 to 64% in
2010/11. In both urban and rural areas, shifts
were evident in the sectors in which women
were employed-in urban areas, from agricultural self-employment to wage non-farm employment; in rural areas, to the unpaid family
worker category. In both urban and rural
areas, the shift among men was from agricultural self-employment and the unpaid family
Mr. Z. Sakala
Vice President, ORVP
Mr. C.L. Lufumpa
Director
Statistics Department
ESTA
[email protected]
+216 7110 2175
Mr. G. Negatu
Director, EARC
This document was prepared by the Statistics Department and the Rwanda Country Office of the African Development Bank. Its
findings reflect the opinions of the authors and not necessarily those of the African Development Bank, its Board of Directors or the
countries they represent. Designations employed in this report do not imply the expression of any opinion on the part of the African
Development Bank Group concerning the legal status of any country or territory, or the delimitation of its frontiers. While every
effort has been made to present reliable information, the African Development Bank accepts no responsibility whatsoever for any
consequences of its use.
Layout and production by
African Development Bank, Tunis—Tunisie
A f r i c a n
D e v e l o p m e n t
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
worker category to wage employment,
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
specifically, private informal employment
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infra(largely construction
and domestic services).
structure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
The
15-to-34
age
group
benefited
most
services.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of governfrom theincome
increase in wagehave
opportunities:
ance
anceand
and incomeinequality
inequality havehampered
hampered
the share of employed youth in wage nonfarm employment rose by 15 percentage
-
points
between
2005/06
and six
2010/11,
cient,
remains
high,
and
in
2010,
of
the
cient, remains high, and in 2010, six of the
compared
with an
11 percentage-point
in10
most
countries
worldwide
10
mostunequal
unequal
countries
worldwide were
were
crease
for the general
Thehas
ininin
Sub-Saharan
Africa.
While
Sub-Saharan
Africa.33population.
While poverty
poverty
has
crease
in
youth
employment
was
mainly
in
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
The percentage of Rwandans aged 15 to
young
will be
be critical
critical in
in order
order
young population
population will
64 who were unemployed fell from 9.3%
to
harness
the
potential
of
the
youth
bulge
to harness the potential of the youth bulge
in
2005/06
to
6.9%
in
2010/11.
However,
and
so-called ‘demographic
‘demographicdivdivand capture
capture the
the so-called
in urban
areas, one though,
in four Africa
womenhas
and
idend.
’
Concurrently
an
idend.’ Concurrently though, Africa has an
one
in
five
men
were
classified
as
unemaging
In 2010,
2010, people
people aged
aged 60
60
aging population.
population. In
ployed
inaccounted
2010/11. for
On just
the other
hand,
a
or
older
6%
of
Africa’s
or older accounted for just 6% of Africa’s
relatively low percentage
of youth
were
population,
this is
is expected
expected
to rise
rise
to
population, but
but this
to
to
unemployed,
which
attributable
to
13%
over the next
50may
yearsbe
(Figure
1).
Some
(Figure 1). Some
delayed labor
entryand
as Nigeria,
a resultare
of
countries,
such force
Nigeria,
are
as Liberia
continuingtoeducation.
expected
double their population
population size
size
in education will be required to benefit
in less
less than
than 20
20years.
years.8 8
in
from the youth bulge in urban areas.
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
Women account for more than half of
Rwanda’s
workers,
but men are
more
likely
youthbulge
bulge
andpopulation
population
aging
willexert
exert
youth
and
aging
will
to
have
wage
employment.
In
fact,
a
large
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highpercentage
of women
workfamily
without
pay.
lightingthe
theneed
need
address
planning
lighting
totoaddress
family planning
Men
are more
likely
than
women
to work
services,
maternal
and
child
healthcare,
and
services,
maternal
and
child
healthcare,
and
in the formal and the informal sector where
earnings are relatively high. Among youth,
8 Ibid.
Ibid.and females have nearly similar farm
8males
Underemployment is very high in Rwanda:
wage earnings, but males fare better in
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
In 2010/11, median monthly salaries were
-RWF 22,000
for men
and
RWFstill
13,200
for
ulation
(excluding
North
Africa)
subsists
ulation
(excluding
North
Africa)
still
subsists
44
women.
Median
increased
between
on
$1.25
day
adjusted).
As
on
$1.25or
orless
lessaawages
day (PPP
(PPP
adjusted).
As
48% of people aged 15 to 64 reported
every other wage category. Women’s
seeking additional or new work in 2010/11,
concentration in unpaid family work sug-
up from 46% in 2005/06.
gests that cultural factors (norms about
2005/06 and 2010/11, but the gender pay
Rwanda has made great strides in reducing
role in labor market decisions. Consequently,
gap
widenedhealth
from outcomes,
aoutcomes,
percentage
difference
improving
health
with
women,
toto
improving
with
women,
rural
dwellers
and
othermarginalized
marginalized
popof about
33%and
to other
67%.
People with postrural
dwellers
populations
bearing
disproportionate
burden.
secondary
education
received theburden.
highest
ulations
bearing
aadisproportionate
Over
thenext
next
50years,
years,gap
projected
that
Over
itit isiswas
projected
pay, the
but
the 50
gender
widestthat
for
the
continent’s
economic
growth rate
rate will
will
the
continent’s
economic
growth
such
individuals.
Nonetheless,
between
55
continue
at
around
5-6%
per
annum.
continue
at
around
5-6%
per
annum.
2005/06 and 2010/11, the gender gap in
extent
which
this
translates
into better
better
extent
totowhich
this
translates
into
pay among
those
with
postsecondary
eduhealth
outcomes
though
is
contingent
on
health
outcomes
though
is
contingent
on
cation fell from 80% to 56%. Youth received
a
number
of
factors,
including
not
only
the
arelatively
number of
factors,
including
notaonly
the
high
wages,
earning
median
level
of
budgetary
allocations
to
the
sector
level
of budgetary
the sector
salary
about 10%allocations
more thantothat
of the
the percentage
of the
sizepopulation
in 2010
Population
2010 without
even if more wage employment becomes
education, especially among youth. No-
available, women’s access to such jobs
netheless, the need to invest in education
may not be equal to men’s. Land rights le-
persists, because of the association bet-
gislation was a step toward reducing cultural
ween higher education attainment and bet-
constraints that limit women’s labor market
ter jobs. Specifically, it is necessary to
opportunities. In addition, given that the
ensure that young people receive postse-
cultural constraints are linked to women’s
condary education, as this appears to be
reproductive roles, if the reduction in fertility
a prerequisite for high-paying non-farm
is sustained, it will free up time for women
wage employment. As well, investment is
to engage in high-paying employment. Si-
population overall. Median public sector
needed in skills development, especially
milarly, availability of childcare or other
be
deployed
torespond
respond
to emerging
emerging
chalbe
deployed
chalwages
wereto27%
highertothan
those in
the
lenges.
Equitable
access
and
treatment
for
lenges.
Equitable
access
and
treatment
for
private formal sector.
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
for women, to allow them to compete in
forms of social protection schemes would
the labor market and to reduce the male-
significantly benefit women, allowing them
female wage gap. In addition, investment
to enter paid employment.
construction and domestic services.
domestic
responsibilities)
Figure 1. Africa’s population
population will
will double
double
size
by2050
2050 play an important
ininsize
by
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
2
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
1. Introduction
Because women’s socioeconomic status
to 4.6 births per woman (National Institute
tends to be low in developing countries, re-
of Statistics Rwanda, et al., 2012).
ducing gender differences and empowering
On the other hand, attitudes toward gender
women are considered key for overall im-
equality are slow to change. For instance,
provement in household conditions (Blackden
the percentage of Rwandan women who
et al., 2007; Quinsumbing and Malluccio,
agree that a husband is justified in beating
2003). Gender bias, and consequently, une-
his wife if she neglects the children has de-
qual control of household resources, affect
clined, but the figure was still relatively high
not only human development outcomes
at 44% in 2010 (National Institute of Statistics
such as child nutrition, but also the productivity
Rwanda, et al., 2012). As well, women who
potential of a household. International evi-
are employed and are breadwinners are
dence shows that gender inequities have
more likely to face a male backlash through
constrained female labor force participation,
sexual violence (Finnoff, 2012).
The limited availability of gender-disaggregated
statistics in developing countries is a major
During implementation of the Poverty Re-
constraint in policy-making and development
duction Strategy Papers, a number of coun-
planning. Assessing progress on Millennium
tries in Sub-Saharan Africa (SSA) initiated
Development
Goal80%
(MDG)
3, Gender
Equality
data.
At
of
countries
data.
Atpresent,
present,
80%
of African
African
and
Empowerment
of
Women,
particularly
claim
claimto
tobe
beusing
usingtelemedicine
telemedicine or m-health
women’s
share
non-agricultural
employ(also
known
as
mobile
health),
(also
known
asof
mobile
health), although
ment,
has
been
difficult
in
Africa.
Rwanda
is
themajority
majority of
of these
these projects
projects are still in
the
no exception.
Although
severalscaling
waves up
of
their
infancy. In
In
this respect,
respect,
their
infancy.
this
interventions
targeting
gender equality.
Despite
technology
ininAfrica
technology(ICT)
(ICT)revolution
revolution
Africa
especially
in primary
and secondary
isprogress,
rapidly
connectivity
across
is
rapidlyincreasing
increasing
connectivity
across
school enrolment (World Bank, 2010), gender
gaps
remain
in Internet
spheres
such
as labor market
health
sector.
Internet
broadband
penehealth
sector.
broadband
peneoutcomes,
asset
ownership,
andaaentrepretrationhas
hasrisen
risenrapidly,
rapidly,from
from
meager
tration
meager
neurship.
For
instance,
in
2006,
women
in
0.1%
of
the
population
in
2000
to
anestiesti0.1% of the population in 2000 to an
9
9
mated
7%inin2010.
2010.
By2060,
2060,coverage
SSA
accounted
for By
only
28%
ofcoverage
non-agrimated
7%
isis
projected
to
rise
dramatically
to
99%
cultural
wage
employment
(Morrison
et
al.,
projected to rise dramatically to 99% ofof
1010 interested in thethe
African
population.
2008).
Policy-makers
are
the
African
population.
tion
provides
the
opportunity
to
overcome
types
of interventions
that canto
improve
wotion
provides
the opportunity
overcome
men’s labor market conditions (World Bank,
humanresources,
resources,and
andininthe
theprovision
provisionofof
2012).
human
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
for
example,
can
expand
service
delivery
forDuring
example,
can
servicehas
delivery
the last
10expand
years, Rwanda
made
and
ensure
greater
accountability
in
health
and
ensure greater
accountability
in gender
health
tremendous
progress
in ensuring
servicesthrough
through
errorreduction,
reduction,
diagservices
error
diagequality in
school enrolment
and empowering
11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItItcan
can
nostic
women.
By 2009, Rwanda
was among the
also
increase
the
transparency
of
medical
also
thecountries
transparency
of medical
fewincrease
developing
with 100%
gender
procurement and distribution operations.
procurement
and and
distribution
operations.
parity in primary
secondary
enrolment
(World Bank, 2011). The share of women in
by streamlining processes, reducing waitbythe
streamlining
processes,
reducing
national legislature
increased
fromwait17%
ing times, and improving the accuracy of
ing
times,
and
improving
the
accuracy
of
in 1995 to 56% in 2010. Rwanda’s land title
registration policy improved women’s pros-
9 Ibid.
9 pects
of owning and inheriting land (Ali et
10Ibid.
Ibid.
1011 Ibid.
al., 2011). The use of modern contraception- 11formation and communication technologies (ICT)
methods,
acommunication
key measure
of women’s
emformation
and
technologies
(ICT)
for health.
Examples
include treating
patients,
conforpowerment,
health. research,
Examples
include
treating
patients,
conducting
educating
the
health
workforce,
doubled to 44%. Between 2005
ducting
research,
the health
tracking
diseaseseducating
and monitoring
publicworkforce,
health.”
and 2010,
theand
fertility
rate dropped
from”6.0
tracking
diseases
monitoring
public health.
the Enquête Intégrale sur les Conditions de
12
Vie des Ménages
(EICV) health
are available,
opportunity
toimprove
improve
health
systems.inopportunity
to
depth examinations of labor market outcomes
The
changing
environmental
land for women
are scarce.
The recently available
The
changing
environmental
scape
threatens
to increase
increase
poverty
and
thematic
report on
gender based
on and
the
scape
threatens
to
poverty
health
problems
in
Africa.
Addressing
2011 EICV
survey in
focused
more
on diffehealth
problems
Africa.
Addressing
the
health
impacts
fromand
climate
change
rences
between
femalemale-headed
the
health
impacts
from
climate
change
households (National Institute of Statistics
which
the continent
continent
is ill-equipped
ill-equipped
to
of Rwanda,
2012).
Because
of unequal shawhich
the
is
to
handle.
Increased
climate
variability
and
handle.
Increasedresources,
climate variability
ring of household
an analysisand
of
the
expected
temperature
warming
will
the
temperature
warming
will
thisexpected
nature based
on household
headship
may fail to capture key intra-household is-
humanaspects,
aspects,mediating
mediating health
health outcomes
outcomes
human
sues—such as who
in the household
works
across
the
continent,
through
both
direct
across
through
both
direct
for paythe
andcontinent,
who provides
unpaid
services.
and indirect channels. Climate change will
and indirect channels. Climate change will
exacerbate food and water insecurity and
exacerbate
food andofwater
insecurity
and
A large population
young
people and
threaten the livelihoods and health of many
threaten
the livelihoods
and health
many
rising educational
attainment
makeofyouth
African populations. Droughts are likely
African
populations.
Droughts
are
likely
employment a challenge in most countries
to become more prevalent, both in fretoin become
more
prevalent, Bank,
both in
freSSA (Africa
Development
2012;
quency and severity, reducing farm yields
quency
and severity,
yields
World Bank,
2009). Inreducing
2011, anfarm
estimated
and increasing hunger and starvation, parand
increasing
hunger
and
starvation,
200 million Africans were aged 15 to par24,
ticularly
in Southern Africa and the Sahel
ticularly
in Southern
Africa andeducation.
the Sahel
and around
40% had secondary
Recent job creation has not benefited young
12 Economist Intelligence Unit (2011).
1
people,
and youth
unemployment
12
Economist
Intelligence
Unit (2011). could be
A f r i c a n
A f r i c a n
3
D e v e l o p m e n t
D e v e l o p m e n t
regions. Various infectious diseases includregions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever,
meningitis,
and schistosomiasis
are
a source
of social unrest
and conflict2. Only
20% of the 73 million jobs created by African
productivity, and earnings in many developing
countries (World Bank, 2007).
AfDB
AfDB
geographical range of vector-borne disgeographical
range
of vector-borne
countries between
2000
and 2008 wentdisto
eases
has been linked
with
regional warmeases
has
been
linked
with
regional
warm15- to 24-year-olds (Africa Development
ing
and the consequent altered length of
ing
and2012).
the consequent
altered
of
Bank,
Consequently,
youthlength
account
seasons.
Climate
change could
increase
the
seasons.
Climate change could increase the
for a disproportionate share of those who
population
at risk
riskof
ofmalaria
malariaininAfrica
Africaby
by
population
at
are
unemployed
or
underemployed.
Questions
an additional
additional170
170million
millionby
by2030
2030and
andthe
the
an
remain population
about what at
factors
influence
youth
global
risk
of
dengue
fever
global population at risk of dengue fever
employment
in
and how
13 youth unemby
billion by
byAfrica
the 2080s.
2080s.
13 Furthermore,
by
22 billion
the
Furthermore,
ployment
affects
poverty
and
the distribution
the rapid
rapidand
andunplanned
unplannedurbanization
urbanization
that
the
that
of
incomes
on
the
continent.
is happening
happening on
on the
the continent
continentisisfraught
fraught
is
-In Rwanda, the increasing number of young people
graduate from
school
but find
cient
orwho
contaminated
drinking
water,
poor
cient
or
contaminated
drinking
water,
poor
limited employment
opportunities
heighsanitation
and sewage
sewage
systems,has
industrial
sanitation
and
systems,
industrial
tened the
to associated
focus on youth
waste,
andneed
stress
withemploypoverty
waste,
and
stress
associated
with
poverty
14
ment.
Against
this
background,
thepolicies
African
and unemployment.
unemployment.14 Sustainable
Sustainable
policies
and
Development
Bank
has
undertaken
an ashouseholdenergy,
energy,agricultural
agriculturalproducproducfor household
sessment
of labortransportation,
market outcomes
for wotivity,
nutrition,
transportation,
water
and
tivity,
nutrition,
water
and
men
and
youth
in
Rwanda.
The
ultimate
obsanitation, could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
15
jective is
development
impact
ontothe
theinform
burden
ofdiseases.
diseases.15policies
impact
on
burden
of
aimed at economic inclusion of women and
youth. The analysis is based on the two
mostlikely
recent
surveys
are
to
decline.
Foreign
from
are
likely
tonational
decline.household
Foreignaid
aid
from
(EICV2
and
EICV3),
complemented
by
setraditional
international
donors
to
develtraditional international donors to developing
countries
isisdeclining
will
condary
information
from theand
Rwanda
Deoping
countries
declining
and
willlikely
likely
play
a
reduced
role
in
African
developmographic
and
Health
Survey.
The
present
play a reduced role in African development
over
50
years.
the
study adopts
thenext
official
ment
over the
the
next
50Rwandan
years.In
Indefinition
thepast,
past,
African
healthcare
systems
have
been
heavof youth healthcare
as personssystems
aged 15have
to 34been
years.
African
heavily
ily reliant
reliant on
oninternational
internationaldonor
donorfunding
funding
from
development
banks,
UN
This study
is organised
as follows.
Section
2
from
development
banks,
UNagencies,
agencies,
and
organizations
as
provides
background such
on
gender
andGlobal
youth
and
organizations
such
as the
the
Global
Fund.
light
uncertain
condition
Fund.
In
light of
of the
the
uncertain
condition
issues In
in Rwanda,
notably,
educational
atof
the
global
economy,
African
countries
of
the global
African
countries
tainment
and economy,
demographic
composition.
will
need
reevaluate
their
will
need3to
to
reevaluate
theirrelationships
relationships
Section
explains
the data
sources
and
with
international
aid
agencies
and
bilateral
with
international
aid agencies
bilateral
analytical
methods used.
Sectionand
4 presents
partners
and possibly
look
totoSouth–
partners
possibly
lookmore
more
South–
key laborand
market
outcomes.
Determinants
South and private–public partnerships.
South
and private–public
of employment
outcomes arepartnerships.
discussed in
Section 5. Section 6 concludes with recom-
domestic ownership of health systems and
domestic
ownership of health systems and
mendations.
the involvement of new international aid
the involvement of new international aid
1
players.
The development literature contains various definiplayers.
tions of youth. UNICEF, WHO, UNAIDS and ILO define youth as persons aged 10 to 24; the UN uses the
15-to-24 age range; and the African Charter on the
13
YouthAfDB,
(2006),A15Strategic
to 30. ForFramework
consistency,for
the Improving
official
13
AfDB,
A Strategic
Framework
for Improving
Health
in definition
Africa
(2012);
WHO
Fact Sheet
Rwandan
of youth
as persons
aged No.
15 to266,
34
Health
in
Africa
(2012);
WHO
Fact
Sheet
No. 266,
was adopted
Oct.
2012. for this report.
2
Oct.
2012.
Riots
in North
Africa during
the “Arab
Spring”
14
AfDB,
A Strategic
Framework,
” op.
cit. in 2011
wereIbid.
partly attributed
to high
levels of”joblessness,
es14
AfDB,
A Strategic
Framework,
op. cit.
15
pecially
among youth in urban areas.
15
Ibid.
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
young population
will be gender
critical in orderand
in less
than 20 years.
2. Background on labor
market,
youth
issues
African subregions are expected to grow
to harness the potential of the youth bulge
and capture the so-called ‘demographic divthe fastest, tripling their populations over
in Rwanda
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infrastructure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
services.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of governance
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
8
young population will be critical in order
to harness the potential of the youth bulge
and capture the so-called ‘demographic dividend.
though, Africa
Africa has
hasan
an
idend.’’ Concurrently
Concurrently though,
aging
In 2010,
2010, people
people aged
aged 60
60
aging population.
population. In
remittances
to developing
countries
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
(UNCTAD, 2012).
Remittances
a
population,
this is
is
expected to
to are
rise to
to
population, but
but this
expected
rise
major
driving
force
in
the
services
sector,
13% over the next 50 years (Figure
(Figure 1).
1).Some
Some
for
example,
construction
and
education.
countries, such as Liberia and Nigeria,
Nigeria, are
are
expected to double their population
population size
size
in less than 20 years.8
African subregions are expected to grow
the fastest, tripling their populations over
Although agriculture remains the mainstay
Ibid. from 35% to 32%. Around 85% of
88slightly
Ibid.
among the fastest-growing economies
of the Rwandan economy, it accounts for
Rwandans are engaged in agriculture
3
.MDG
In 2009,
pace
ofpoverty
economic
globally
meet
the
goal
of
by
meet
theMDG
goalthe
of halving
halving
poverty
by
a diminishing share of Gross Domestic
(National Institute of Statistics of Rwanda,
growth slowed because of stagnation in-the industrial
sector
and
a still
significant
ulation
(excluding
North
subsists
ulation
(excluding
NorthAfrica)
Africa)
still
subsists
Product (GDP). During the past 10 years,
2012), which means that 32% of GDP
the share of GDP growth attributable to
employs 85% of the population.
44
decline
sector.
To some
on
$1.25
or
less
aaday
adjusted).
As
on
$1.25in
orthe
lessservices
day (PPP
(PPP
adjusted).
As
agriculture
lagged
behind
that of the
Figure
population
will double
doubleininsize
sizeby
by2050
2050
1. Africa’s
population
will
2.1.
Structure of the economy
-Fromremains
2002 tohigh,
2011,and
Rwanda
experienced
cient,
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
positive
real Gross
Domestic
Product
10
most
countries
worldwide
were
10
mostunequal
unequal
countries
worldwide
were
33 average of more
(GDP)
growth-an
annual
inin
Sub-Saharan
Africa.
While
poverty
Sub-Saharan Africa. While poverty has
has
than
8%by
(Table
1). the
This
places
Rwanda
declined
9%
20
this
declined
by
9%over
over
the past
past
20 years,
years,
this
degree, this may be explained by the
industrial and services sectors. Over the
after-effects
of outcomes,
the
2008/09
global
improvinghealth
health
outcomes,
withwomen,
women,
toto
improving
with
2002-to-2011
period,
agriculture
GDP
size in
2010
Population
2010
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
youth
Services contribute
the
largest
share
of
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highGDP—averaging
44%
to
lighting
theneed
needtotoaddress
addressfrom
family2002
planning
lighting
the
family
planning
2011.
The
share
contributed
by
industry
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
services,
rose slightly from 14% to 16%, while the
share contributed by agriculture declined
3
The other countries among the World’s 10
fastest-growing economies, based on annual
average GDP growth from 2001 to 2010, are
Angola, China, Myanmar, Nigeria, Ethiopia,
Kazakhstan, Chad, Mozambique, and Cambodia (International Monetary Fund, 2011).
rural
dwellers
andother
other
marginalized
popfinancial
crisis,
which
reduced popthe
growth averaged 5%, compared with
rural
dwellers
and
marginalized
ulations
bearing
adisproportionate
disproportionate
burden.
more than 10% for both industry and
demand
for agoods
(especiallyburden.
from
ulations
bearing
Over
thenext
next
50years,
years, it
it isis projected
projected
that
Over
the
50
European
countries)
and
the levelthat
of
services.
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
continueatataround
around5-6%
5-6% per
per annum.
annum.55
continue
Table 1. Rate of economic growth and share of GDP, by industrial sector, Rwanda, 2002-2011
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
Industrial sector
2002
2003
2004
2005
2006
2007
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
level
budgetary
allocations
to the
the sector
sector
level
ofofbudgetary
to
Annual
GDP growthallocations
rate
2008
2009
2010
2011
(%)
beTotal
deployed
torespond
respond to
to emerging
emerging chalchalGDP to
13.2
be
deployed
lenges.
Equitable
access
and
treatment
for
lenges.
Equitable access and treatment16.9
for
Agriculture
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
Industry
7.2
challenge.
challenge.
Services
11.6
2.2
7.4
9.4
9.2
7.6
11.1
6.2
- 3.1
1.8
6.5
2.8
2.6
6.4
7.7
4.7
15.5
9.3
11.7
15.1
1.3
6.9
10.2
11.9
13.3
12.2
13.8
6.3
5
8.4
9
8.6
4.7
17.6
8.9
Predicted population
Predicted
population size
size in
in 2050
2050
Share of GDP (%)
severe
healthchallenge.
challenge.African
AfricandemogrademograAgriculture
35.4
severe
health
Industry
9
7.2
13.9
38.3
38.6
38.4
38.4
35.6
32.4
33.9
12.8
13.9
14.1
13.8
13.9
14.8
14.4
46.4
45.5
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
Services
44.1
42.4
41.2
41.4
42
44.6
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
size
by2020,
2020,
toreach
reach
2.7billion.
billion.66 What
What
is dataset (28/06/2012 release)
Source:
Rwanda
Macroeconomic
Variable
size
by
to
2.7
is
more, the majority of this population will
more,
the majority
of this period,
population
will
During the
2002-to-2011
changes
same time, the share of employed women
belong
to the
youth cohort.
Africa
is the
belong
to
the
youth
cohort.
Africa
is
the
working as unskilled or skilled manual lain
the
structure
of
the
economy
were
miworld’s youngest region and is expected
world’s youngest region and is expected
nimal.
the
characteristics
the
borers doubled from 5% to 10%. As well,
to
haveHowever,
the largest
workforce
in the of
world
to have the
largest workforce in the world
7
labor
market
changed
espethe percentage of employed women who
by
2040.
Ensuring
thesubstantially,
good health of
this
by 2040.7 Ensuring the good health of this
cially for women. The percentage of em-
aged
15 to 49forwho
were
3ployed
AfDB,women
“A Strategic
Framework
Improving
3Health
AfDB,
“A Strategic
Framework for Improving
in Africa”
(2012).
in
agriculture
fell
from
86%
in
2005/06
to
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
4577%
WHO,
Atlas
Statistics
(2011b).
in 2010/11,
the percentage
of
AfDB,
AfricaofinHealth
50while
Years’
Time
(2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
employed men in agriculture remained re6Miracle or Malthus?” (2011b).
lativelyorconstant
atYears’
62%Time
(Figure
1). At the
Miracle
Malthus?”
7 AfDB,
Africa in 50(2011b).
(2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
32.2
15
46.7
31.9
16.3
45.6
show that between 2005 and 2010, the
percentage of 15- to 49-year-olds with no
education declined from 23% to 17%
among women and from 16% to 12%
were unpaid family workers fell from 57%
among men. Nonetheless, gender gaps
to 18%.
in the labor market persist. For instance,
in 2010, 19% of women received their ear-
Source:
AfDB
These shifts
may
be(2011a).
partly attributable to
Source: AfDB (2011a).
nings in cash, compared with 38% of men
rising educational attainment. The Rwanda
(National Institute of Statistics Rwanda, et
Demographic and Health Surveys (RDHS)
al., 2012).
4
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
regions. Various infectious diseases includ-
Figure 1. Percentage distribution, by gender and occupation, employed population aged
15 toVarious
49, infectious diseases includregions.
ing malaria, cholera, diarrhea, dengue
Rwanda, 2005/06 and 2010/11
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
Percent
100
86
77
80
62
61
60
40
20
4
14
8
13
0
Agriculture,
2005
Agriculture,
2011
Unskilled
Manual,
2005
Unskilled
Manual,
2011
Female
Male
data.
countries
data. At
At present,
present, 80% of African countries
technology
claim
m-health
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine or m-health
Source:
Authors’
calculations
from
EICV2,
2005
and
EICV3,
2011
datasets
isisrapidly
increasing
connectivity
across
(also
known
as
mobile
health),
although
rapidly increasing connectivity across
(also known
although
the
still in
in
the majority
majority of these projects are still
health
sector.
Internet
broadband
penetheir
infancy.
In
this
respect,
scaling
up
health sector. Internet broadband penetheir infancy.
scaling up
tration
trationhas
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
12
12
0.1%
population
in
opportunity
improve health
systems.
0.1%
the
population
in2000
2000to
toan
anestiestiopportunity
systems.
2010/11; thetocorresponding
drop
among
2.2.ofofthe
Youth
and
affirmative
99
mated7%
7%action
2010. By
By2060,
2060,coverage
coverage isis
mated
inin2010.
their male contemporaries was from 14%
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
The
changing
land projected
The
changing
to about
5%. environmental land theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
and
the
scape
poverty
and
Given that a third of Rwandans-about 3.7
tionprovides
providesthe
theopportunity
opportunityto
to overcome
health problems
problems in Africa. Addressing
tion
health
Addressing
million individuals-are
aged 15 toovercome
34, youth
Rwanda has a number
of affirmative
action
the health
health impacts from climate change
the
change
employment is a critical policy issue. Youth
programmes to address inequalities in achumanresources,
resources,and
andininthe
theprovision
provisionof
of
human
employment rates are relatively high (for
cess to economic opportunities. For examhigh-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
which the
the continent is ill-equipped
high-quality
which
ill-equipped to
to
example, 71% for women and 91% for
ple, the Vision 2020 Umurenge Programme
for
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
formen
example,
can expand service delivery
handle.
Increased climate variability and
aged 20 to 24 in 2010/11), but labor
(VUP) is both a cash transfer scheme and
and
ensure
greater
accountability
in
health
the
expected
temperature warming
and ensure greater accountability in health
the expected temperature
warming will
will
segmentation is pronounced. Young women
a public works programme (Ministry of Loservices
through
error
reduction,
diagservices through error reduction, diagare more likely than their male counterparts
cal Government, 2009). The programme is
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes
to work on family farms. For instance, in
means-tested, targeting households in the
also
increase
the
transparency
of
medical
across
the
continent,
through
also increase the transparency of medical
across the continent, through both
both direct
direct
2010/11, 74% of employed women aged
lowest two ubudehe or poverty/consumpprocurement
and
distribution
operations.
and
indirect
channels.
Climate
change
procurement and distribution operations.
and indirect channels. Climate change will
will
20 to 24 were in agriculture, compared to
tion quintiles.
households
earn
exacerbate
foodEligible
and water
water
insecurity
exacerbate
food
and
insecurity and
and
55%
of employed
men. At the
same waittime,
wages bythe
working
on community
infrastrucstreamlining
processes,
reducing
threaten
livelihoods
and
bybystreamlining
processes,
reducing
waitthreaten
the livelihoods
and health
health of
of many
many
rising
school
enrolment
has
meant
that
ture
projects.
It
is
expected
that
thelikely
VUP
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
ing times, and improving the accuracy of
African populations. Droughts are likely
youth entering the labor market have higher
willbecome
improvemore
the prevalent,
welfare of households
to
to
become more
prevalent, both
both in
in frefreattainment, and thus, are likely
throughand
increased
consumption
and yields
asset
quency
severity,
reducing
farm
9educational
Ibid.
quency and severity, reducing farm yields
9 Ibid.
10 seek
Ibid. different kinds of jobs. The percenandincreasing
livestock acquisition.
and
hunger and starvation, par10to Ibid.
and increasing hunger and starvation, par11
11tage of women aged 15 to 34 with no edu-ticularly
in
Southern
Africa and the Sahel
formation and communication technologies (ICT)
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
for
health.
include
treating patients,
cation
fellExamples
from 16%
in 2005/06
to 4%conin
for health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
Other examples of affirmative action pro-
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and the consequent altered length of
seasons. Climate change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
global population
populationatatrisk
riskofofdengue
denguefever
fever
global
13
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.13 Furthermore,
by
the
rapid
and
unplanned
urbanization
that
the rapid and unplanned urbanization that
happening
onthe
the11
continentisisfraught
fraught
11
isis happening
on
continent
2
1
--Skilled
Skilleddrinking water, poor
cient
or
contaminated
cient or contaminated drinking water, poor
Manual,
Manual,
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
2005
2011
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
tivity,
nutrition,
transportation,
water
and
tivity, nutrition, transportation, water and
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditional
internationaldonors
donorstotodeveldeveltraditional
international
grammers include:
oping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
play
aa reduced
role
developplay
reduced
roleininAfrican
African
develop• the
Law on Matrimonial
Regimes,
Doment
over
the
next
50
years.
InInthe
ment
over
the
next
50
years.
thepast,
past,
nations, Succession and Liberalities
African
healthcare
systems
been
heavAfrican
healthcare
systemshave
have
beenrights
heav(1999),
which guarantees
the land
ily
on
international
donor
funding
ilyreliant
reliant
on
international
donor
funding
of legally married women, ensures equal
from
development
from
developmentbanks,
banks,UN
UNagencies,
agencies,
rights in inheritance by boys and girls,
and
organizations
such
asasthe
Global
andand
organizations
such
the
Global
requires spousal consent in any
Fund.
In
light
of
the
uncertain
condition
Fund.
In light of the uncertain condition
land transfer;
of
the
global
of the globaleconomy,
economy,African
Africancountries
countries
• the 2003 Constitution that earmarked
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
at least 30% of posts in the public
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
sector for women;
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
• the Organic Land Law (2005), which
South
and
private–public
partnerships.
South and private–public partnerships.
ensures equality among men and wo-
men in land ownership;
and
domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
•
implementation
of
Organic
Land Law
the
involvement
of
new
international
the involvement of new internationalaid
aid
through the land tenure regularization
players.
players.
programme; initial assessments show
that the law increased land ownership
13 AfDB, A Strategic Framework for Improving
13 among
AfDB, Amarried
Strategicwomen
Framework
Improving
(Ali etforal.,2011).
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
5
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
30
20
10
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
especially,
literacy
For with
this
improving
healthstatus.
outcomes,
withanalysis,
women,
toto
improving
health
outcomes,
women,
rural
dwellers
andother
other
marginalized
popliteracy
is defined
as
themarginalized
ability to readpopand
rural
dwellers
and
ulations
bearing
disproportionate
burden.
write “abearing
letter
or aaadisproportionate
simple
note.” In 2010/11,
ulations
burden.
Over
the
next
50years,
years,
projected
that
Over
50
isis projected
that
52%the
of next
women
ageditit15
to 64 were
the
continent’s
economic
growthwith
rate62%
will
the
continent’s
growth
rate
will
categorized
as economic
literate,
compared
continue
around5-6%
5-6% per
per annum.
annum.55
continue
of men. atataround
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
health
outcomes
though
contingent
on
health
though
isis contingent
on
In theoutcomes
recent past,
literacy
rates have
a
number
of
factors,
including
not
only
the
aincreased,
number ofand
factors,
including
not only the
among
15- to 30-year-olds,
level
of
budgetary
allocations
to
the sector
sector
level
of budgetary
the
the gap
between allocations
males and to
females
has
Population size in 2010
2010
80+
75-79
70-74
65-69
60-64
55-59
50-54
Rwanda are in educational attainment—
45-49
0
40-44
increases
their
earnings
meet
the
goal
halving
by
meet
theMDG
MDG
goalof
oflifetime
halving poverty
poverty
by
opportunities (UNESCO, 2008).
-ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
Some
gender
gaps44 As
in
on
$1.25
less
adjusted).
on
$1.25ofor
orthe
lessawidest
aday
day (PPP
(PPP
adjusted).
As
Ibid.
88 Ibid.
40
35-39
more likely to keep children in school, which
50
30-34
knowledge-driven
economy—for
instance,
cient,
remains
high,
and
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
technologies
such
as mobile
phones
10
most
countries
worldwide
were
10
mostunequal
unequal
countries
worldwide
were
33
demand
that
users
be
literate.
Furthermore,
inin
Sub-Saharan
Africa.
While
poverty
Sub-Saharan Africa. While poverty has
has
research
shows
that
literate
parents
are
declined
9%
the
past
years,
declinedby
by
9%over
over
the
past 20
20
years, this
this
25-29
new skills, a critical ability in the current-
20-24
Those who are literate can easily acquire
Although programmers are needed to
maintained, the gender
disparity will
young
will be
be critical
critical in
in order
order in
in
less than
than 20
20years.
years.8 8
young population
population will
less
improve literacy among women aged 35 or
disappear in the future.
African
subregionsare
areexpected
expectedtotogrow
grow
to
potential of
of the
the youth
youth bulge
bulge African
subregions
to harness
harness the
the potential
older,
if
current
education
policies
are
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
and capture
capture the
the so-called
the
idend.
’
Concurrently
though,
Africa
has
an
idend.’ Concurrently though, Africa has an
Figure
2. Literacy
gender
and60
age
group,
2010/11
aging
population.
Inrates,
2010,by
people
aged
60five-year
youth
bulge
andRwanda,
population
agingwill
willexert
exert
aging
population.
In
2010,
people
aged
youth
bulge
and
population
aging
or
older
accounted
for
just
6%
of
Africa’s
increasing
pressure
on
health
systems,
highor older
accounted for just 6% of Africa’s
increasing pressure on health systems, high90
population,
this is
is expected
expected to
to rise
rise to
to lighting
lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
population, but
but this
80
13% over the next 50 years (Figure
(Figure 1).
1).Some
Some services,
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
70
countries, such as Liberia and Nigeria,
Nigeria, are
are
60
expected to double their population
population size
size
15-19
2.3. Literacy
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infraA key determinant
of whether individuals
structure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
can obtain
jobs
inofthe
formal
sector
is their
services.
In
spite
this,
issues
of
governservices. In spite of this, issues of governability toincome
read and write, that
is, “literacy.”
ance
anceand
and incomeinequality
inequalityhave
havehampered
hampered
Literacy Rate (%)
AfDB
AfDB
Age (years)
Female
Male
Total
Source: Authors’ calculations from the EICV3 2011 dataset
Literacy rates of women and men vary
employed. For instance, in agricultural
by occupational activity and rural-urban
self-employment, 55% of men compared
location. The occupational activities de-
with 35% of women were literate. Diffe-
fined by the EICV3 are farm and non-
rences in literacy rates by rural-urban lo-
disappeared (Figure 2). This reflected
farm wage and self-employment, and an
cation were relatively small—urban resi-
be
deployed
torespond
respond
to emerging
emerging chalchalbe
deployed
to
increased
primary
schooltoenrolment.
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
of societyisisone
onecritical
critical
the
On the other
hand, society
at older ages,
the
challenge.
challenge.
unpaid worker category. The literacy rate
dents’ literacy rate was about 7 percen-
was low among farm workers in 2010/11-
tage points higher than that of their rural
about 20 percentage points below that
counterparts. Among youth, gender dif-
percentage of women who are literate is
of non-farm workers (Table 2). This sug-
ferences in literacy were minimal. The
less than that of men, and the gap widens
gests that literacy is key to non-agricultural
exception was non-agricultural self-em-
with advancing age-for example, from 10
severehealth
healthchallenge.
challenge.African
African demograsevere
percentage points
at ages 35 todemogra39 to 30
percentage points at ages 55 to 59.
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Predicted population
size
Predicted
population
size in
in 2050
2050
self-employment.
Gender differences
in
ployment where the difference between
literacy rates by occupational activity
male and female youth was 7 percentage
were evident, particularly among the self-
points.
Source: AfDB (2011a).
Source: AfDB (2011a).
6
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table 2. Literacy rates, by urban-rural location, occupational activity and gender, population aged
15 toVarious
64 andinfectious
15 to 34, diseases includregions.
regions.
Various
infectious
diseases includRwanda, 2010/11
ing malaria, cholera, diarrhea, dengue
ing malaria, Ycholera,
diarrhea,
dengue
outh (and
15 to schistosomiasis
34)
fever, meningitis,
are
fever, meningitis, and schistosomiasis are
Working
ng--age popu
pullation
Urban-rural loca
cattion and occ
ccu
upational
activity
(15 to 64)
Total
Total
Female
range
of vector-borne
disTogeographical
tageographical
l
Ferange
m
ale of
Male
vector-borne
dis-
Male
56.3
51.5
62.2
44..6
44
42
48..1
48
62
62
62..1
62
45..2
45
35..1
35
54..9
54
66
59..3
59
73..1
73
53..2
53
51..4
51
62..7
62
62.5
58.7
67.5
48..8
48
42..2
42
56..2
56
68
69..5
69
67..1
67
Independen
ndependentt farmer
43..1
43
36
56..4
56
Independen
ndependentt nonnon-farmer
69..3
69
63..7
63
77..9
77
57
55..2
55
68..6
68
55.5
50.7
61.6
44..3
44
42
47..5
47
Wage farm
Wage non
non--farm
Independen
ndependentt farmer
Independen
ndependentt nonnon-farmer
Unpa
npaiid famililyy worker
Urban
Wage farm
Wage non
non--farm
Unpa
npaiid famililyy worker
Rural
Wage farm
Wage nonnon-farm
technology
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
Independen
ndependentt farmer
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
Independen
ndependentt nonnon-farmer
data.
80% of African
countries
data. At
At present,
present,
countries
60..4
60
58..5
58
60..9
60
claim
m-health
claim to
to be
be using telemedicine or m-health
45..4
45
35
54..8
54
(also
although
(also known
known as mobile health), although
65..3
65
58..2
58
72..3
72
the
still in
in
the majority
majority of these projects are still
53 In this respect,
51..2 scaling up
51
62..4
62
their
their infancy.
infancy.
scaling up
Unpa
npaiid fambroadband
ililyy worker
health
healthsector.
sector.Internet
Internet
broadband penepenetration
has
risen
rapidly,
from
a
meager
tration
has
risen
rapidly,
from
a
meager
Source: Authors’ calculations from 2005 EICV2 dataset.
0.1%
opportunity
systems.1212
0.1%ofofthe
thepopulation
populationinin2000
2000to
toan
anestiestiopportunity to improve health systems.
99
mated
7%Population
2010. By
By2060,
2060,coverage
coverage isis
mated
inin2010.
2005/06 to 52% in 2010/11. This is in line
2.4. 7%
structure
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
The
changing
land
projected
The
environmental
land-with changing
trends in fertility,
which decreased
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
and
the
scape
poverty
and
from 6.2 to 4.6 children per woman over
The demographic composition of a poputionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
tion
health
Addressing
the same period (National
Institute
of Stalation has implications
for employment.
the health
health impacts from climate change
the
change
tistics of Rwanda et al., 2012).
Appendix 1 shows population pyramids
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
generated from the EICV2 and EICV3 for
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
which the
the continent is ill-equipped
high-quality
which
ill-equipped to
to
The structure of the population differs in
Rwanda’s population overall and by ruralfor
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
forurban
example,
can expand service delivery
handle.
Increased climate variability and
rural and urban areas. The urban
location. The broad bases of the
and
ensure
greater
accountability
in
health
the
expected
temperature warming
and ensure greater accountability in health
the expected temperature
warming will
will
population is characterised by a “youth
pyramids indicate a high dependency raservices
through
error
reduction,
diagservices through error reduction, diagbulge”; that is, the 15-to-34 age group
tio. Because women are responsible
for
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes
accounts for a larger share of the
child nurturing/caring, this population
also
increase
the
transparency
of
medical
across
the
continent,
through
also increase the transparency of medical
across the continent, through both
both direct
direct
population in urban than rural areas. To
structure suggests that women’s employprocurement
and
distribution
operations.
and
indirect
channels.
Climate
change
procurement and distribution operations.
and indirect channels. Climate change will
will
some extent,
this
may
be insecurity
attributable to
ment prospects will continue to be
exacerbate
food
and
water
exacerbate
food
and
water
insecurity and
and
migration.
the EICV3,
64%
constrained
by their
reproductive
and
dostreamlining
processes,
reducing
waitthreaten
theAccording
livelihoodstoand
bybystreamlining
processes,
reducing
waitthreaten
the
livelihoods
and health
health of
of many
many
4
.
Nonetheless,
a
slight
reof
youth
in
urban
areas
were
migrants,
mestic
roles
ingtimes,
times,and
andimproving
improvingthe
theaccuracy
accuracyof
of
African populations.
populations. Droughts
ing
African
Droughts are
are likely
likely
duction in overall dependency is evident,
compared
with
38%
of
youth
inin rural
to
become
more
prevalent,
both
to become
more prevalent, both in frefreareas5. and severity, reducing farm yields
quency
9with
Ibid.the percentage of the population
quency and severity, reducing farm yields
9 Ibid.
10 Ibid. than 18 falling from 54% in
and increasing hunger and starvation, par10younger
Ibid.
and increasing hunger and starvation, par11
11
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
eases has been linked with regional warm7.3 linked with
66.4regional warm68.3
eases has6been
ing and the consequent altered length of
ing and the
consequent
altered
length
of
54..3
54
54.2
54.5
seasons. Climate change could increase the
seasons. Climate
change66.9
could increase65.7
the
66
population at risk of malaria in Africa by
population at risk of malaria in Africa by
63..6 170 million
63
62 by 2030 and
64.5
an additional
the
an additional 170 million by 2030 and the
74..2
74
70.7 of dengue fever
77.9
global
population
at
risk
global population at risk of dengue fever
13
Furthermore,
by 22 billion
billion
bythe
the2080s.
2080s.
63..4 by
63
63.413 Furthermore,
63.4
by
the
rapid
and
unplanned
urbanization
that
1.2 unplanned70.5
71.9
the rapid7and
urbanization that
happening
on the continent
fraught
isis happening
isisfraught
57..8 on the continent
57
53.9
61.8
70..5
70
71.3
69.9-72..2
72
71.4
73.2
cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
75..3and sewage systems,
75
72
79.3
sanitation
industrial
sanitation
and sewage systems, industrial
67..5 stress associated
67
67.5
67.5
waste, and
and
withpoverty
poverty
waste,
stress associated
with
14
14 Sustainable
andunemployment.
unemployment.
policies
66.7
65.8
67.8
and
Sustainable
policies
forhousehold
household
energy,agricultural
agricultural
producfor
produc54..1 energy,
54
54.2
54
tivity,
nutrition,
transportation,
water
and
tivity, nutrition,
transportation,
water and
64..6
64
64.6
64.6
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
63..1
63
61.1
64.2
impacton
onthe
theburden
burdenofofdiseases.
diseases.1515
impact
D e v e l o p m e n t
D e v e l o p m e n t
70.4
77.6
63..2
63
63.2
63.2
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditionalinternational
internationaldonors
donorstotodeveldeveltraditional
oping
countries
is
declining
and
will
likely
oping
countries
is
declining
and
will
likely
Between 2005/06 and 2010/11, the urban
play
reduced
role
African
developplay aabulge
reduced
roleinin
African
developyouth
remained
stable,
a demograment
over
the
next
50
years.
InInthe
past,
ment
over
the
next
50
years.
past,
phic phenomenon that could have the
serious
African
systems
have
heavAfricanhealthcare
healthcare
systems
havebeen
been
heavconsequences.
Unless
Rwanda
creates
ily
reliant
on
international
donor
funding
ily
reliant
on
international
donor
funding
jobs for this population, the potential for
from
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
civil unrest exists. As well, previous reand
organizations
such
asasthe
Global
and
organizations
such
the
Global
search has shown that the lack of urban
Fund.
In
light
of
the
uncertain
condition
Fund. In light of the uncertain condition
employment opportunities may result in
of
of the
the global
globaleconomy,
economy,African
Africancountries
countries
young girls being drawn into commercial
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
sex work (Sommers 2012).
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
to
South–
4partners and possibly look more
to
South–
An analysis of time use in Rwanda showed
South
and
private–public
partnerships.
that,
in
addition
to
market-based
activities,
South and private–public partnerships.
women spend an average of about 20 hours per
week on domestic responsibilities versus about
domestic
ofofhealth
and
5domestic
hours forownership
men (National
Institute
of Statistics
ownership
healthsystems
systems
and
Rwanda,
2006).
the
involvement
of
new
international
aid
5the involvement of new international aid
The migration rates are based on the following
players.
survey
question: “Have you always lived in this
players.
district?” Respondents were classified as migrants if they had not always lived in the district
where
they A
were
interviewed.
13
AfDB,
Strategic
Framework for Improving
13 AfDB, A Strategic Framework for Improving
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
7
A f r i c a n
A f r i c a n
74
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infrastructure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
services.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of governance
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
-cient,
remains
high,
and
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
10
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
33
ininSub-Saharan
Africa.
While
poverty
Sub-Saharan Africa. While poverty has
has
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
-ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Over
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
continueatataround
around5-6%
5-6% per
per annum.
annum.55
continue
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
young
will be
be critical
critical in
in order
order
young population
population will
to
harness
the
potential
of
the
youth
bulge
to harness the potential of the youth bulge
and
so-called ‘demographic
‘demographicdivdivand capture
capture the
the so-called
idend.
’
Concurrently
though,
Africa
has
an
idend.’ Concurrently though, Africa has an
aging
In 2010,
2010, people
people aged
aged 60
60
aging population.
population. In
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
population,
this is
is expected
expected to
to rise
rise to
to
population, but
but this
13% over the next 50 years (Figure
(Figure 1).
1).Some
Some
countries, such as Liberia and Nigeria,
Nigeria, are
are
expected to double their population
population size
size
in less
less than
than 20
20years.
years.8 8
in
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
youth
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highlightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
lighting
services,
maternal
and
child
healthcare,
and
services, maternal and child healthcare, and
Ibid.
88 Ibid.
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
Population size in 2010
2010
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
8
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
3. Data sources and methods
3.1.
Data sources
employment section of the questionnaire
gathered information on: employment sta-
The main data sources are the two most
tus; desire to work and seeking work; oc-
recent national household surveys—
cupation type; paid employment (nature
Enquête Intégrale sur les Conditions de
of activity and wages); and participation
Vie des Ménages (EICV) (Integrated
in non-remunerated activities. All the above
Household Living Conditions Survey)-
information was captured for the past 7
conducted in 2005/06 and 2010/11 by
days and for the previous 12 months. The
the National Institute of Statistics of
community module was administered to
Rwanda with the assistance of Oxford
the Umudugudu (lowest village-level ad-
Policy Management. The EICVs are multi-
ministrative unit) chairperson and captured
topic surveys modeled on the World
availability of and access to infrastructure
Bank’s living standards measurement
in the locality.
surveys. They are based on two-stage
stratified random sampling. In the first
In the analysis, individual worker charac-
stage, the principal sampling unit is the
teristics were matched to the household
enumeration
characteristics and to the characteristics
area
or
zone
de
dénombrement (ZD), with the 2002
of the community where the individual re-
Rwanda Census as the sampling frame.
data.
At
countries
data.
At present,
present, 80% of African countries
sided.
claim
m-health
claim to
to be
be using telemedicine or m-health
(also
known
as
mobile
health),
although
(also
knownare comprehensive, although
The EICVs
but they
the
majority
of
these
stillthe
in
the
majority
projects
are
still
in
have shortcomings. For instance, from
their
infancy.
In
this
respect,
scaling
up
their
infancy.
scaling
up
EIVC3,
it is not possible to directly
identify
technology
in
technology
(ICT)
revolution
in Africa
Africa
The ZDs (ICT)
were revolution
chosen using
the
isis
rapidly
increasing
connectivity
across
rapidly increasing
connectivity
across
probability
proportional
to size procedure.
In the second stage, households were the
health
sector.
broadband
penehealth
sector.Internet
Internet
broadband
penemain sampling
units, with
an average
of
tration
has
risen
rapidly,
from
a
meager
tration
has
risen
rapidly,
from
a
meager
12 households being randomly selected
0.1%
the
0.1%
thepopulation
populationinin2000
2000to
toan
anestiestifromofof
each
ZD/cluster.
mated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage isis
mated
projected
rise
dramatically to
to 99%
99% of
of
projected
totorise
The objective
of dramatically
the EICVs is to
provide
theAfrican
Africanpopulation.
population.1010
the
-nationally representative data on incomes
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
tion
and household consumption, upon which
national and subregion poverty estimates
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
will be based. The EICV2 was conducted
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
during June and September 2005. The
forexample,
example,can
canexpand
expandservice
servicedelivery
delivery
for
EICV3, conducted over a full year from
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
November 2010 through October 2011,
services
through
error
reduction,
diagservices through error reduction, diagwas designed to capture seasonal11 effects
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
in household incomes and consumption.
also
increase
the
transparency
of
medical
also increase the transparency of medical
The EICV2 covered 6,900 households
procurement
anddistribution
distributionoperations.
operations.
procurement
and
from 620 ZDs; the EICV3 covered 14,308
households
fromprocesses,
1,230 ZDs.
streamlining
reducingwaitwaitbybystreamlining
processes, reducing
ing
times,
and
improving
the
accuracy
of
ing times, and improving the accuracy of
The surveys consisted of three modules:
household; (2) community; and (3)
9(1) Ibid.
9 Ibid.
10
Ibid.The household module captured
price.
10 Ibid.
11
11the demographic characteristics of theformation and communication technologies (ICT)
formation and communication technologies (ICT)
for
health. Examples
includeattainment,
treating patients,
conhousehold,
educational
access
for health. Examples include treating patients, conducting research, educating the health workforce,
to health
services,
andthe
employment.
For
ducting
research,
educating
health workforce,
tracking diseases and monitoring public health.”
tracking
diseases
and
monitoring
public
health.
”
household members aged 6 or older, the
main sector of employment-agriculture,
12
12
opportunity
to improve healthinsystems.
systems.
opportunity
industry, or services-because,
2010/11,
information was collected on multiple jobs
The
changing
land
The
changing
rather
than onlyenvironmental
the main activity land
as inscape threatens
threatens to increase poverty
and
scape
poverty
and
EIVC2 in 2005/06. Main sector of
health problems
problems in Africa. Addressing
health
Addressing
employment can be
derived from
EICV3
the health
health impacts from climate change
the
change
data by using a combination of variables
(for example, maximum number of hours
which the
the continent is ill-equipped
which
ill-equipped to
to
worked on a particular job and job status),
handle.
Increased
climate
variability
and
handle.
Increased climate variability and
but the employment sectors generated
the
expected
temperature warming
the expected temperature
warming will
will
with this method are not comparable to
those collected directly in the EICV2. The
human aspects,
aspects, mediating
mediating health
human
health outcomes
outcomes
EICV2 did not capture information on skill
across
the
continent,
through
across the continent, through both
both direct
direct
status, whereas the EICV3 directly
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
captured occupational
which
exacerbate
food and
and water
watergroups,
insecurity
exacerbate
food
insecurity and
and
allows for
determination
of themany
skill
threaten
thethe
livelihoods
and
threaten
the
livelihoods
and health
health of
of many
status
of
paid
employees.
Consequently,
African populations.
populations. Droughts
African
Droughts are
are likely
likely
trend
analysis
of
the
skill
status
of
to
become
more
prevalent,
both
in
to become more prevalent, both in frefreemployees
not possible.
quency
and is
severity,
reducing farm
quency
and
severity,
reducing
farm yields
yields
and increasing hunger and starvation, parand increasing hunger and starvation, par3.2. inVariables
included
in Sahel
the
ticularly
Southern Africa
and the
ticularly in Southern Africa and the Sahel
analysis
12 Economist Intelligence Unit (2011).
12
Economist Intelligence
Unit enquire
(2011). about
Employment:
The EICVs
regions. Various infectious diseases includregions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
the economic activity status of all usual
and regular household
ageddis6
geographical
range of members
vector-borne
geographical range of vector-borne disor older
during
the with
pastregional
12 months.
eases
has been
linked
warmeases has been linked with regional warming
and the consequent
altered
length of
Respondents
aged 15 to 64
are classified
ing and the consequent altered length of
seasons.
Climate
change
could
increase
the
as being employed if, during the past 12
seasons. Climate change could increase the
population
at risk
of malaria
Africa
months, they:
cultivated
their in
farm;by
population
at risk
of malaria
inown
Africa
by
an
additional
170
million
by
2030
and
the
were
in
paid
agricultural
activity;
worked
an additional 170 million by 2030 and the
global
population
at
risk
of
dengue
fever
for
a
salary
or
wages
in
the
non-farm
global population at risk of dengue fever
13
by
billion
by
the2080s.
2080s.
sector;
ran aby
non-farm
business
for cash
13 Furthermore,
by
22 billion
the
Furthermore,
the
rapid
and
unplanned
urbanization
that
or profit;
or participated
in a Vision 2020
the
rapid and
unplanned urbanization
that
happening
onthe
thecontinent
continent
fraught
Uremenge
Program
(VUP)
public
works
isis
happening
on
isisfraught
program.
--cient
or
contaminated
drinking
water,
poor
Informal
sector: Consistent
with poor
the
cient
or contaminated
drinking water,
sanitation
and
sewage
systems,
industrial
International
(ILO)
sanitation
and Labor
sewage Organization
systems, industrial
waste,
andthe
stress
associated
poverty
definition,
informal
sector with
iswith
comprised
waste,
and
stress
associated
poverty
1414 Sustainable policies
and
unemployment.
and
Sustainable
policies
of unemployment.
people
who were
self-employed,
for
household
energy,
agriculturalproducproducfor
household
energy,
domestic
workers
or agricultural
wage-earners
who
tivity,
nutrition,
transportation,
water
and
tivity,
transportation,
water and
were nutrition,
not involved
in professional
or
sanitation,
could
have
a
large
and
positive
sanitation,
could
have
a
large
and
positive
technical fields, and in addition, were not
1515
impact
onthe
burdenofofdiseases.
diseases.
impact
on
burden
engaged
intheagricultural
activities (ILO,
2000). This definition is consistent with the
System of National Accounts (SNA 1993).
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditional
international
donors
develtraditional
international
donors
totodevelDemographics:
The following
household
oping
countries
is
declining
and
will
likely
oping
countries
is
declining
and
will
characteristics were considered in likely
the
play
a
reduced
role
in
African
developplay
a
reduced
role
in
African
developanalysis: gender, age, household
ment
over
next
In the past,
ment
overthe
the(children
next50
50years.
years.
composition
aged In0 the
to past,
6;
African
healthcare
systems
have
been
heavAfrican
healthcare
systems
have
been
heavchildren aged 7 to 14; males aged 15 to
ily
reliant
ily
relianton
oninternational
internationaldonor
donorfunding
funding
64; females aged 15 to 64; and people
from
development
from
developmentbanks,
banks,UN
UNagencies,
agencies,
aged 65 or older), and migration status
and
organizations
such
asasthe
Global
and
organizations
such
the
Global
(whether individuals had moved to the
Fund.
In
light
of
the
uncertain
condition
Fund.
In light of the uncertain condition
district where they resided at the time of
of
the
global
of the globaleconomy,
economy,African
Africancountries
countries
the interview). As earlier stated, youth
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
refers to people aged 15 to 34, which
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
accords with the official definition by the
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
Government of Rwanda.
South
and
private–public
partnerships.
South and private–public partnerships.
Socio-economic characteristics:
Consumpdomestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
tion expenditure is
used as
the household
the
the involvement
involvementofofnew
newinternational
internationalaid
aid
welfare measure. Previous studies have
players.
players.
shown that income data for African countries are under-reported (McKay, 2000).
13 AfDB, A Strategic Framework for Improving
13
AfDB, A Strategic
Framework
for of
Improving
Furthermore,
given the
seasonality
agriHealth in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct.
2012.
cultural incomes in Rwanda, household
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
consumption
is a more
stable” op.
measure
of
14
AfDB, A Strategic
Framework,
cit.
15 Ibid.
15
Ibid.
welfare status. However, the regression
9
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
AfDB
AfDB
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
analysis for employment outcomes includes variables relating to
education attained and four categories 8of attainment (no
rapid
young
will be
be
critical in
in order
order in
in less
less than
than 20
20years.
years.8
rapideconomic
economic growth
growth has
has boosted
boosted the
the
young population
population will
critical
a household’s non-agricultural income and the value of a
education, primary education, secondary education, and higher
amount
of
resources
allocated
to
health
infraAfrican
subregions
areexpected
expectedtotogrow
grow
to
harness
the
potential
of
the
youth
bulge
amount of resources allocated to health infraAfrican subregions are
to harness the potential of the youth bulge
household’s
agricultural
equipment
as
covariates.
education).
The
education
indicator
represents
accumulated
structure
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
the
human
capital
asan
well as skills acquired over time. The definitions
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
though,
Africa
has
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
Other socio-economic
characteristics
used in the
analysis pertainIn 2010,
of the
majoraged
variables
2005and
and
2010/11 are
described
ance
aging
people
60 used
youthfor
bulge
population
aging
willexert
exert
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In 2010, people
aged 60
youth
bulge
and population
aging
will
to educational attainment: the highest numberorofolder
yearsaccounted
of formal for in
the
table
below.
just
6%
of
Africa’s
increasing
pressure
on
health
systems,
highor older accounted for just 6% of Africa’s
increasing pressure on health systems, highpopulation,
this is
is expected
expected to
to rise
rise to
to lighting
-lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
population, but
but this
Definitions
of
key
variables
used
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
services,
maternal
and
child
healthcare,
and
cient, remains high, and in 2010, six of the
(Figure 1). Some
services, maternal and child healthcare, and
10
countries, such as Liberia and Nigeria,
Nigeria, are
are
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
33
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
2
0
0
5
Sub-Saharan Africa. While poverty has
population size 2011
Ibid.
88 Ibid.
declined
by
declined
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Employed
An individual is classified as employed if in An individual is classified as employed if in
the past 12 months she/he: (i) cultivated
the past 12 months she/he: (i) worked for
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
own farm; (ii) engaged in a paid agricultural
wages; (ii) worked as an own account
-worker; (iii) was engaged in agriculture; or activity; (iii) worked for salary or wages in
non-farm sector; (iv) ran a non-farm
(iv) worked for no pay in household or
ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
businessin
cash
profit ; or (v) partici44
external
business.
on
Figure 1. Africa’s population
population will
will double
double
inforsize
size
byor2050
2050
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted). As
As
by
pated in a voluntary works programme
(VUP).
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
Population size in 2010
2010
rural
dwellersand
and
othermarginalized
marginalized
popEmployed/Working-age population (15 to
rural
dwellers
other
Employment
-to-population
ratio popEmployed/Working-age population (15 to
64 years)
64
years)
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Over
the
continent’s
economic growth
growth rate
rate will
will
the
continent’s
Working-age (15 to 64 years) individuals
Labor
force economic
Working-age (15 to 64 years) individuals
employed or unemployed (actively
continueatataround
around5-6%
5-6% per
per annum.
annum.55
employed or unemployed (actively
continue
looking for a job or discouraged, that is,
looking
for
a
job
or
discouraged,
that
is,
extent
to
which
this
translates
into
better
extent to which this translates into better
not looking for a job)
not looking for a job)
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
numberofoffactors,
factors,including
including not
not only
only the
the
aanumber
In the labor force without a job
Unemployed
level
budgetaryallocations
allocations to
to the
the sector
sector
In the labor force without a job
level
ofofbudgetary
Unemployment rate
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
Source:
EICV2,
2005
and
EICV3,
2011
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Unemployed/Labor force
Unemployed/Labor force
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
10
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
3.3
Determinants of
employment
wage non-agriculture, and self-employment
in non-agriculture and agriculture. Separate
regressions for both categories of employ-
Following Cook (1998), a multinomial logit
ment are estimated for women and men,
model is used to examine factors associated
and for urban and rural areas (Box 1). For
with employment outcomes in Rwanda, in
each estimation, four employment out-
AfDB
AfDB
non-agriculture;
non-agriregions.
Variousself-employment
infectious diseases
includregions. Various infectious diseases includculture;
agriculture;
and not
employed.
For
ing
malaria,
cholera,
diarrhea,
dengue
ing malaria, cholera, diarrhea, dengue
youth
employment,
the
options
are:
fever, meningitis, and schistosomiasis(a)
are
fever, meningitis, and schistosomiasis are
enrolled in school only; (b) work only; (b)
work and school;
and
doing nothing.
geographical
range
of (d)
vector-borne
disgeographical range of vector-borne disAgain,has
separate
regressions
are estimated
eases
been linked
with regional
warmeases has been linked with regional warming
and the
altered
length
particular: (i) employment in formal and incomes are considered: (a) formal; informal;
for male
and consequent
female youth,
and for
urbanof
ing and the consequent altered length of
seasons.
formal sectors and agriculture, and (ii)
agriculture; and not employed; or (b) wage
and ruralClimate
areas. change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
Box 1. Model used for estimation of employment outcome
global population
populationatatrisk
riskofofdengue
denguefever
fever
global
13
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.13 Furthermore,
by
the
probability
that individual
Consider an individual with m potential employment outcomes. Let ∏ jk determine
the
rapid
and
unplanned
urbanization
that
the rapid and unplanned urbanization that
is happening
happening
onthe
the
continent
fraught
X j represent
j ends up in employment outcome k (for example, non-farm wage employment). isLet
thecontinent
individual’s
on
isisfraught
-characteristics (age, gender, asset ownership, migration status, household demographic composition and educational
th
-attainment), and let Z jk be the characteristics of the k employment outcome for individual j . For the multinomial
cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
logit, for each of the m employment outcomes, the probability that individual j ends
up in outcome
given by
k issystems,
sanitation
andsewage
sewage
systems,
industrial
sanitation
and
industrial
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
exp( β ' X j )
and unemployment. Sustainable policies
1
= m
(1) ∏ jk =
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducm
for
β
β
β
exp(
'
X
)
exp[(
−
)'
X
)]
l
j
l
k
j
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
1 present,
l =1
data.l =At
countries
tivity, nutrition, transportation, water and
technology
claim
m-health sanitation,
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine or m-health
1515
isisrapidly
increasing
connectivity
across
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
β1 ,....,connectivity
β m are m across
vectors of (also
the regression
1 is estimated
using
2010/11
EICV3
Where
rapidly
increasing
known parameters. Equation
although
impact on
the the
burden
of diseases.
the
majority
of
these
still
in
the
majority
projects
are
still
in
dataset. Apart from being the most recent survey, the EICV3 covered a much larger sample over a full year, and so
can
capture
seasonality
andpenehow it affects
employment
outcomes.
Based on
health
Internet
broadband
their
In this
respect, scaling
scaling
upthe above formulations, the marginal
healthsector.
sector.
Internet
broadband
penetheir infancy.
infancy.
up
tration
from
aa meager
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
probability
effects
of rapidly,
X on the
trationhas
hasrisen
risen
rapidly,
from
meagerof employment outcome k are estimated as
are
12
12
0.1%
to improve health
systems.
traditionalinternational
internationaldonors
donorstotodeveldevel0.1%ofofthe
thepopulation
anestiesti-  opportunity
opportunity
traditional
k
 systems.
δpopulation
Pr(Yi =inink2000
)2000totoan
=coverage
Pr(Yi =isisk )  β k1 − Pr(Yi = j ) β j1 
mated7%
7%
2010.9 9By
By2060,
2060,
coverage
oping
(2)inin2010.
mated
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
δ
X
j
=
0
i
projectedtotorise
risedramatically
dramatically
to 99%
99% of
of  The
The changing
changing environmental
land
play
projected
to
land-play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelop
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
ment
the
-scape
poverty and
and
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
African
tion
health
Addressing
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavthe health
health impacts from climate change
ily
the
change
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
humanresources,
resources,and
andininthe
theprovision
provisionof
of
from
human
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
which the
the continent is ill-equipped
and
high-quality
which
ill-equipped to
to
and organizations
organizations such
such asasthe
theGlobal
Global
for
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
for example, can expand service delivery
handle. Increased climate variability and
Fund. In light of the uncertain condition
and
ensure
greater
accountability
in
health
the
expected
temperature
warming
will
of
and ensure greater accountability in health
the expected temperature warming will
of the
the global
globaleconomy,
economy,African
Africancountries
countries
services
through
error
reduction,
diagwill
need
to
reevaluate
their
services through error reduction, diagwill need to reevaluate theirrelationships
relationships
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
also
increase
the
transparency
of
medical
across
the
continent,
through
both
direct
partners
and
possibly
look
more
also increase the transparency of medical
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
procurement
and
distribution
operations.
and
indirect
channels.
Climate
change
will
South
and
private–public
partnerships.
procurement and distribution operations.
and indirect channels. Climate change will
South and private–public partnerships.
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
streamliningprocesses,
processes,reducing
reducingwaitwaitthreaten the
the livelihoods
livelihoods and
bybystreamlining
threaten
and health
health of
of many
many domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
of
new
international
ing times, and improving the accuracy of
African populations. Droughts are likely
the involvement of new internationalaid
aid
to
become
more
prevalent,
both
in
freplayers.
to become more prevalent, both in freplayers.
quency
and
severity,
reducing
farm
yields
9 Ibid.
quency and severity, reducing farm yields
9 Ibid.
10 Ibid.
and increasing hunger and starvation, par10 Ibid.
and increasing hunger and starvation, par11
13 AfDB, A Strategic Framework for Improving
11
13 AfDB, A Strategic Framework for Improving
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
∑
∑
∑
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
11
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
population will be critical in order
4. The Rwanda laboryoung
market
to harness the potential of the youth bulge
young population will be critical in order
to harness the potential of the youth bulge
and
so-called ‘demographic
‘demographicdivdivand capture
capture the
the so-called
and 2010/11.
In fact,though,
womenAfrica
accounted
idend.
’
Concurrently
has
an
idend.’ Concurrently though, Africa has an
for
more
than
half
(55%)
of
the
employed
aging
In 2010,
2010, people
people aged
aged 60
60
aging population.
population. In
in 2005/06
(4.1 million)
and 6%
2010/11
(4.3
or
older
accounted
for
just
of
Africa’s
or older accounted for just 6% of Africa’s
million).
population,
this is
is expected
expected to
to rise
rise to
to
population, but
but this
13% over the next 50 years (Figure
(Figure 1).
1).Some
Some
The employment
rate was
lowest
in the
countries,
such as Liberia
Nigeria,
are
and
Nigeria,
are
capital city,
Kigali: 72%
2005/06 and
expected
to double
theirinpopulation
population
size
size
in less
less than
than 20
20years.
years.8 8
in
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
75% in 2010/11. The highest rate was in
Ibid. in urban employment was largely
88Growth
Ibid.
the Northern region, rising from 84% in
driven by increased opportunities in Ki-
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
Calculation of the employment rate (em--ployment-to-population
ratio)-the
ulation
(excluding
still
subsists
ulation
(excludingNorth
NorthAfrica)
Africa)
stillpercensubsists
44
tage
of
the
population
aged
15
to
64
on
As
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).who
As
2005/06 to 86% in 2010/11, followed by
gali—the area’s share of urban employ-
the Eastern region, where the rate fell
ment rose by about 8 percentage points
from 85% to 82%.
between 2005/06 and 2010/11.
are working—is based on information
In 2010/11, the regional distribution of
In urban areas, women’s employment
about
usualhealth
activity.
improving
health
outcomes,with
withwomen,
women,
toto
improving
outcomes,
the employed
reflected
of the overall
size that
in 2010
Population
2010
rates were about 5 percentage points lo-
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulations
bearingaadisproportionate
disproportionate
burden.
From 2005/06
to
2010/11, Rwanda’s
ulations
bearing
burden.
Over
theemployment
next50
50years,
years,
is projected
projected
that
Over
the
next
itit is
that
overall
rate
remained
relatithe
continent’s
economic
growth
rate
will
the
will
velycontinent’s
stable at economic
about
82%growth
(Table rate
3). Wo55
continue
around
5-6% per
per
annum.
continue
atataround
men’s rate
was 5-6%
about
3 annum.
percentage
extent
to
which
this
translates
into
better
extent
which
this
translates
into
better
pointsto
higher
than
men’s
in both
2005/06
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
population. Kigali accounted for 10% of
wer than men’s. This may partly be be-
the employed population aged 15 to 64,
cause urban employment tends to require
and 9.8% of the general population. The
higher educational attainment, and the
Southern region’s share of the employed
relatively low attainment of women puts
population fell by about 3 percentage
them at a disadvantage.
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infrastructure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
This section
analyses
employment
outservices.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of governcomes inincome
Rwanda and howhave
these vary for
ance
anceand
and incomeinequality
inequality havehampered
hampered
women and men and for youth—employ-
ment rates, the extent and size of the in--
formal
sector,high,
the skill
status
of employed
cient,
remains
and
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
people,
and the countries
earnings
of
those in were
paid
10
most
10
mostunequal
unequal
countriesworldwide
worldwide
were
33
employment.
inin
Sub-Saharan
Africa.
While
poverty
Sub-Saharan Africa. While poverty has
has
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
4.1.
Employment
Given the high poverty rates in the Sou-
thern region,
thispopulation
decline may
be will
attribuyouth
bulgeand
and
aging
exert
youth
bulge
population aging
will exert
table
to
migration
from
the
Southern
reincreasing
pressure
on
health
systems,
highincreasing pressure on health systems, highgion to
urban
areas.family
Even
so,
lighting
theneed
need
address
planning
lighting
the
totoaddress
family planning
employment
rates
remained
more
or
less
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
services,
stable in the Southern region.
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
points between 2005/06 and 2010/11.
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
12
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table 3. Employment rates and percentage distribution of employed, by rural-urban location, gender
and
region,infectious
population
aged 15includregions.
Various
diseases
regions.
Various
infectious
diseases
includto 64, Rwanda, 2005/06 and 2010/11
ing malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
distribution
of employed
fever, Percentage
meningitis,
and schistosomiasis
are
fever, meningitis, and schistosomiasis are
Employment-to-population ratio
Group
2011
2005
(% points)
(%)
National
Change
81.6
82.4
-0.8
Female
82.8
83.9
-1.1
Male
80.1
80.7
-0.6
Kigali City
74.9
71.8
3.1
Southern Region
81.6
82.7
-1.1
Western Region
80.9
83.3
-2.4
Gender
Region
Northern Region
85.9
84.3
1.6
Eastern Region
81.9
84.6
-2.7
75.6
73.1
2.5
73.2
70.6
2.6
78.4
75.9
2.5
Urban
Gender
Female
Male
Region
technology
revolution
in
technology(ICT)
(ICT)
revolution
in Africa
Africa
Kigali
City
isisrapidly
increasing
connectivity
across
rapidly increasing
connectivity
across
Southern
Region
Western Region
data.
countries
data. At
At present,
present, 80% of African countries
claim
telemedicine
m-health
claim to
to be
be using
73.7
69.9 or m-health3.8
(also
known
as
mobile
health),
although
(also known79.2
80.3 although
-1.1
the
of these projects are still
still in
in
the majority
majority74.8
73.3
1.5
their
In this respect, scaling
scaling up
up
their infancy.
infancy.
80.2
70
10.2
health
broadband
healthsector.
sector.Internet
Internet
broadband penepeneNorthern Region
tration
trationhas
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
Eastern Region
79
0
6.1
12
0.1%
ofofthe
to improve health
systems.12
0.1%
thepopulation
populationinin2000
2000to
toan
anestiesti- 79 opportunity
opportunity
systems.
Rural
82.7
84.4
-1.7
99
mated7%
7%inin2010.
2010. By
By2060,
2060,coverage
coverage isis
mated
Gender
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
The changing
changing environmental land
projected
The
land-Female
84.6
86.7
-2.1
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
the
-scape
poverty and
and
Male
80.5
81.7
-1.2
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
tion
health
Addressing
Region
the health
health impacts from climate change
the
change
Kigali City
82.2
83.7
-1.5
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
Southern
Region E-Health,
82
83.1
-1.1
high-qualityhealthcare
healthcare
services.
which the
the continent
is ill-equipped
high-quality
services.
E-Health,
which
ill-equipped to
to
Western
81.4 climate84.4
-3
forexample,
example,can
canexpand
expandRegion
servicedelivery
delivery
handle. Increased
Increased
for
service
handle.
climate variability
variability and
and
Northern
Region
86.3
85.8
0.5
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
the expected
expected temperature
temperature warming
and
the
warming will
will
Eastern
Region
82.1
84.9
-2.8
services
through
error
reduction,
diagservices through error reduction, diag11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes
Source: EICV2, 2005 and EICV3, 2011
also
increase
the
transparency
of
medical
across
the
continent,
through
also increase the transparency of medical
across the continent, through both
both direct
direct
procurement
and
distribution
operations.
and
indirect
channels.
Climate
change
procurement and distribution operations.
and indirect channels. Climate change will
will
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
streamliningprocesses,
processes,reducing
reducingwaitwaitthreaten the
the livelihoods
livelihoods and
bybystreamlining
threaten
and health
health of
of many
many
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
ing times, and improving the accuracy of
African populations. Droughts are likely
likely
to become
become more
more prevalent,
prevalent, both
to
both in
in frefrequency
and
severity,
reducing
farm
yields
9 Ibid.
quency and severity, reducing farm yields
9 Ibid.
10 Ibid.
and increasing hunger and starvation, par10 Ibid.
and increasing hunger and starvation, par11
11
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
2011 range of2005
Change
geographical
vector-borne
disgeographical range of vector-borne diseases has been linked with regional warmeases has been
(%)linked with regional
(% warmpoints)
ing and the consequent altered length of
ing and the consequent altered length of
100
seasons. Climate
change100
could increase 0the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional
170million
million
by2030
2030and
and
the
54.5 170
54.9by
-0.4
an additional
the
global
population
at
risk
of
dengue
fever
45.5
45.1
0.4
global population at risk of dengue fever
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.1313Furthermore,
by
the
rapid
and
unplanned
urbanization
that
10.1 unplanned 9.3
0.8
the rapid and
urbanization that
happening
onthe
thecontinent
continent
fraught
23.4 on
26.1
-2.7
isis happening
isisfraught
23.4
23.7
-0.3 - 19.3
17.9
1.4- cient
or
contaminated
drinking
water,
poor
23.8
22.9
0.9
cient or contaminated
drinking
water, poor
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
15
15.8
-0.8
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
andunemployment.
unemployment.
and
Sustainable
policies
13.9
14.6
-0.7
forhousehold
household
energy,
agricultural
producfor
energy,
agricultural
produc16.2
17.2
-1
tivity,nutrition,
nutrition,transportation,
transportation,water
waterand
and
tivity,
sanitation,
couldhave
haveaa49.4
largeand
andpositive
positive
sanitation,
could
large
57.1
7.7
1515
impact
on
the
burden
of
diseases.
impact on19.9
the burden of23.9
diseases.
-4
D e v e l o p m e n t
D e v e l o p m e n t
10.1
-0.5
7.3
9.2
-1.9
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
7.3
-1.2
traditionalinternational
internationaldonors
donorstotodeveldeveltraditional
85
84.2
0.8
oping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelop86.1
85.4
0.7
ment
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
83.8
82.8
1
African
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavily
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
1.8
1.8
0
from
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
24.1
26.4
-2.3
and
and organizations
organizations such
such asasthe
theGlobal
Global
25.8 of the uncertain
26.3
-0.5
Fund.
Fund. In
Inlight
light of the uncertaincondition
condition
21.4
19.6
1.8
of
of the
the global
globaleconomy,
economy,African
Africancountries
countries
26.9reevaluate their
25.9
1
will
willneed
needto
to reevaluate theirrelationships
relationships
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
South
and
private–public
partnerships.
South and private–public partnerships.
domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
the
involvement
of
new
international
the involvement of new internationalaid
aid
players.
players.
13 AfDB, A Strategic Framework for Improving
13 AfDB, A Strategic Framework for Improving
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
13
A f r i c a n
A f r i c a n
9.6
B a n k
B a n k
Employment rates were much lower in urban than rural areas, although the overall urban rate
attributable
to widespread
employment
in rural areas,
and school
increased
from 73%availability
in 2005/06oftoagricultural
76% in 2010/11.
The relatively
low urban
rates are
6
Indeed,
urban
employment
attendance
in
urban
areas,
especially
by
15to
19-year-olds.
Analysis
ofofGender
attributable
to widespread availability of agricultural employment in rural areas, andrates
school
Analysis
Genderand
and
Youth
Employment
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
6
Youth
Employment
inurban
Rwandaareas,aged
African
were lowest
amongininindividuals
15 to 19
4).
Indeed, urban employment
rates
attendance
especially
by (Figure
15- to 19-year-olds.
were lowest among individuals aged 15 to 19 (Figure 4).
Urban employment rates were significantly lower among women than among men at ages 20
viduals aged 15 to 19 (Figure 4).
they cannot afford child
Employment rates were much lower in
8 care.
8
rapid
economic
growth
has
boosted
young
population
will
be critical
critical
in
order
in
lessamong
than 20
20men
years.at
rapidto
economic
growth
has
boosted the
the age
young
population
will
be
in
order
in
less
than
years.
Urban
employment
rates
were
significantly
lower
among
women
than
ages
34,
the
prime
childbearing
range
(at
least
200
births
per
1,000
women)
(NISR
et
al., 20
Urban employment rates were signifiurban than rural areas, although the oveamount
of
resources
allocated
to
health
infraAfrican
subregions
are
expected
togrow
grow
to
harness
the
potential
of
the
youth
bulge
amount
of resources
allocated
to healthchildbearing
infra- among
African
subregions
are expected
to harness
the potential
of the
youth
bulgeper
toincreased
34,
the prime
age
range
(at
least
200
births
et
al., to
2012).
Thus,
low
employment
women
of women
these
ages
may
be 1,000
due
towomen)
the
high(NISR
cost
ofpeaks
cantly
lower
among
than
among
Women’s
employment
rate
at
ages
rall
urban
rate
from
73%
in
structure
survival-enhancing
social
and
the
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
structureand
andto
to
survival-enhancing
social
and capture
capture
thewomen
so-called
the
2012).
Thus,areas.
low
employment
among
ages
may
be
the 10
high
costlater
ofthan the
child
care
inthis,
urban
Womenidend.
may
stay
to these
look
their45
children
because
they
men
at
ages at
20 home
to though,
34, of
the
primeafter
childtodue
49, to
about
years
2005/06
tospite
76%
in
2010/11.
The
relatiservices.
In
of
issues
of
govern’
Concurrently
Africa
has
an
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
child
incare.
urban areas.
Women
may
stay(atatleast
home
look after peak
theirfor
children
because
they 4). This,
bearing age
range
200 to
births
men
to 39) (Figure
vely low
urban
ratescare
are attributable
to
cannot
afford
child
ance
aging
In 2010,
2010, people
people
agedper
60 youth
youthbulge
bulge
and(35
population
agingwill
willexert
exert
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In
aged
60
and
population
aging
cannot afford
child emcare. or
1,000
women)
(NISR
etjust
al., 6%
2012).
Thus,
too, may pressure
be linked
to
the systems,
constraints
widespread availability
of agricultural
older
accounted
for
of
Africa’s
increasing
on
health
highor older accounted for just 6% of Africa’s
increasing pressure on health systems, highWomen’s
rateatpeaks
at employment
ages 45
tothis
49,is about
10to
years
laterlighting
than the
peak
for
men
low
among
women
of
these
imposed
women
by family
reproductive
ployment
in rural employment
areas, and school
population,
but
expected
rise
to lighting
-theon
need
address
planning
population,
but
this
is
expected
to
rise
to
the
need
toto
address
family
planning
Women’s
employment
rate
peaks
at
ages
45
to
49,
about
10
years
later
than
the
peak
forby
men
(35
to
39)
(Figure
4).
This,
too,
may
be
linked
to
the
constraints
imposed
on
women
ages
may
be
due
to
the
high
cost
of
child
responsibilities.
They
may
not
be able and
to
tendance
in
urban
areas,
especially
by
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
services,
maternal
and
child
healthcare,
cient, remains high, and in 2010, six of the
(Figure 1). Some
services, maternal and child healthcare, and
(35
to
39)
(Figure
4).
This,
too,
may
be
linked
to
the
constraints
imposed
on
women
by
6
. responsibilities.
Indeed,
urban were
em- They
caremay
in urban
Women
may
stay
at
fullyin
participate
in the
labor market until
15to
19-year-olds
reproductive
not
be
able
to
participate
the labor
market
10
most
unequal
worldwide
countries,
suchareas.
Nigeria,
are
10
most
unequalcountries
countries
worldwide
were
as Liberia
andfully
Nigeria,
are
reproductive
responsibilities.
They
may
not
be
able
to
fully
participate
in
the
labor
market
3lowest
ployment
were
home to look
after their
because
their child care duties are
completed.
3 While
untilrates
their
child
careamong
dutiesindiare completed.
inin
Sub-Saharan
Africa.
poverty
has
expected
to double
theirchildren
population
size
Sub-Saharan
Africa.
While
poverty
has
population
size
until
their
child
care
duties
are
completed.
Ibid.
88 Ibid.
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Figure 4: Urban employment rates, by gender and age group, Rwanda, 2005/06 and
Figure 4: Urban employment rates, by gender and age group, Rwanda, 2005/06 and
2010/11
meet
the
goal
of
meet
theMDG
MDG
goalemployment
of halving
halving poverty
poverty
bygender and age group, Rwanda, 2005/06 and 2010/11
Figure
4. Urban
rates, byby
2010/11
AfDB
AfDB
-ulation
still
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)2005
stillsubsists
subsists
100
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
100
1002011
2011
Figure 1. Africa’s population
population
will double
doubleininsize
sizeby
by2050
2050
will
80
80
Population size in 2010
2010
65+
60-64
65+
55-659
60-64
50-54
55-659
50-54
45-49
45-49
40-44
40-44
35-39
Female
Female
MaleMale
30-34
25-29
35-39
30-34
15-19
65+
60-64
55-59
50-54
0
45-49
0
0
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.Equitable
Equitableaccess
access and
and treatment
treatment for
for
lenges.
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011
40-44
20
35-39
20
30-34
40
25-29
40
20-24
60
15-19
60
20-24
15-19
25-29
20-24
improving
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
80 health
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
60 next 50 years, it is projected that
Overthe
the
Over
next 50 years, it is projected that
thecontinent’s
continent’seconomic
economic growth
growth rate
rate Female
will
the
will
continueatataround
around5-6%
5-6% per
per annum.
annum.55
continue
40
Male
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
20
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011
Source: Authors’ calculations from EICV2, 2005Predicted
and EICV3, 2011 size in 2050
Predicted population
population size in 2050
severe
health
challenge.
African
demograSeasonal
variations
in
employment
rates
reflect the predominance of rain-fed agriculture.
severe
healthvariations
challenge.
African
demograSeasonal
in employment
rates rates
reflect reflect
the
August
is usually characterized
by minimal
agricultural activity,
Seasonal
variations
in
employment
the
predominance
of rain-fed
agriculture.
Rwanda’s first agricultural season occurs during
the September-to-January period; Julyand thus, lower employment rates. The EICV2 collected
predominance of rain-fed agriculture. Rwanda’s first agricultural
Rwanda’s
firsttoday,
agricultural
during the September-to-January period; Julypeople
livingin
inAugust
Africa
and itit characterized
theseason occurs
is usually
by minimal
agricultural
activity,
and
thus, lower
employment
people
living
Africa
today,
and
isis the
season
occurs
during
the
September-to-January
period;
Julyinformation
on monthly
employment
during the previous year
August that
is usually
characterized
agricultural
activity,
and thus,
lower employment
onlycontinent
continent
expected
todouble
double
in by minimal
only
that
isisexpected
to
in
rates.
The EICV2
collected
information
on
monthly
employment
during
the
previous
year
6
size
by
2020,
to
reach
2.7
billion.
rates.
The
EICV2
collected
6 What isinformation on monthly employment during the previous year
size by 2020, to reach 2.7 billion. What is
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth
cohort. Africa is the
6
world’s youngest
and is expected
Inregion
2010/11,
to-19 age group accounted for 20% of the working-age population (15 to 64).
world’s6 youngest region andtheis 15expected
In
2010/11,
the
15to-19
age
group accounted for 20% of the working-age population (15 to 64).
to have the largest workforce in the world
to have the
largest workforce in the world
16
7
by 2040. Ensuring the good health of this
by 2040.7 Ensuring the good health of this
16
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
14
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
(Figure 5). In 2005/06, employment rates for July and August were about 73%,
declined,Various
while the
percentage
in includwage
regions.
infectious
diseases
regions. Various infectious diseases includnon-farm
employment
in rural dengue
areas,
with more
than 85% inrates
the other
months.
ing
malaria,
cholera,rose;
diarrhea,
(Figurecompared
5). In 2005/06,
employment
for July
and August were about 73%, compared
ing malaria, cholera, diarrhea, dengue
the
percentage
of
women
in
the
unpaid
fever, meningitis, and schistosomiasis are
with more than 85% in the other months.
fever, meningitis, and schistosomiasis are
Figure 5. Monthly employment rates, by occupational category, Rwanda, 2005/06
Figure 5: Monthly employment rates, by occupational category, Rwanda, 2005/06
Percent of Labour Force
100
80
60
40
20
0
Jan
Feb Mar Apr May Jun
Agriculture
Industry
Jul
Aug Sep
Services
Oct Nov Dec
All Industries
Source:
Authors’
calculations
from
EICV 2, 2005 dataset.
Source: Authors’
calculations
from
EICV 2, 2005
dataset.
family worker category increased. In both
urban and rural
areas,
percentage disof
geographical
range
ofthe
vector-borne
geographical range of vector-borne dismale workers
were
in agricultural
selfeases
has beenwho
linked
with
regional warmeases has been linked with regional warming
and the consequent
length
employment
and unpaid altered
family work
de-of
ing and the consequent altered length of
seasons.
Climate
change could
the
clined, while
the percentage
in increase
wage emseasons. Climate change could increase the
population
at risk of Further
malaria analysis
in Africa by
ployment increased.
population
at risk of malaria
in Africa by
by
an
additional
170
million
by
2030
and
the
sector
of
work
and
industry
group
indian additional 170 million by 2030 and the
global
population
at
risk
of
dengue
fever
cates
an
increase
in
the
percentage
of
global population at risk of dengue fever
13
by
billion
byinthe
the
2080s.
male
workers
private
informal
employ13 Furthermore,
by
22 billion
by
2080s.
Furthermore,
the
rapid
and
unplanned
urbanization
that
ment—predominantly
construction
the rapid and unplanned urbanization and
that
happening
onthe
the
continentisisfraught
fraught
domestic
services.
Macroeconomic
data
isis
happening
on
continent
support this finding, with growth in the- construction industry averaging 23.5% du-- cient
orcontaminated
contaminated
drinking
water,
poor
ring or
the
2005-to-2011
periodwater,
(Rwanda
cient
drinking
poor
sanitation
andsewage
sewage
systems,
industrial
Macroeconomic
Dataset,
2012).industrial
This had
sanitation
and
systems,
waste,
andstress
stress
associated
withpoverty
poverty
little impact
on women’s
employment,
as
waste,
and
associated
with
1414 Sustainable policies
and
unemployment.
and
unemployment.
policies
most
construction jobsSustainable
entail high physical
for
household
energy,
agriculturalproducproducfor
household
demands;
onlyenergy,
a few agricultural
administrative,
cleativity,
nutrition,
transportation,
water
and
tivity,
nutrition,
and
ning and
other transportation,
light jobs in thewater
industry
sanitation,
could
haveaalarge
largeand
andpositive
positive
sanitation,
could
have
can be done
by women.
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
data.
countries
data. At
At present,
present, 80% of African countries
technology
claim
m-health
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine or m-health
4.2 isisrapidly
Wage
versus
non-wage
employment
increasing
connectivity
across
(also
known
as
mobile
health),
although
rapidlyWage
increasing
connectivity
across
(also
known By contrast, among
although
employment.
female
4.2.
versus
non-wage
the
majority
of
these
stilljust
in
the
majority
projects
are
still
in
However, the increase in female unpaid
workers,
non-wage transformation
employment fell by
Although wageemployment
employment is a key determinant
of economic
in agrarian
health
sector.
Internet
broadband
penetheir
infancy.
In
this
respect,
scaling
up
health
sector.
Internet
broadband
penetheir
infancy.
scaling
up
family labor should also be interpreted in
3
percentage
points
during
this
period.
settings (Timmer 1988), African countries typically have very low wage employment. The
tration
has
risen
rapidly,
from
a
meager
are
likely to
to
decline.
Foreignaid
aidfrom
from
tration
has
risen
rapidly,
from
a
meager
are
Foreign
the likely
context
ofdecline.
the demographic
shift
into
wage employment
is adimension,
key
lack ofAlthough
job opportunities
has a gender
with women spending more time on non12
12
0.1%
of
the
population
in
2000
to
an
estiopportunity
to
improve
systems.
traditional
international
donors
to
devel0.1%
of
the
population
in
2000
to
an
estiopportunity
health
systems.
traditional
international
donors
to
develemployment
by
young
individuals,
gender
determinant
of
economic
transformation
in
Men
accounted
for
75%
of
the
estimated
remunerated activities than do their male counterparts. According to the 2013 WDR, at least
99
7%settings
2010.
By2060,
2060,
coverage
oping
countries
isisdeclining
and
will
7%
inin
By
coverage
isis
oping
countries
declining
and
willlikely
likely
roles in
African countries,
and
changes
in
agrarian
African
590,000compared
increase inwith
the number
wage(World
85% mated
ofmated
women
in2010.
SSA(Timmer
are
in 1988),
non-wage
employment,
75% ofofmen
projected
to
rise
dramatically
to
99%
of
The
changing
land
play
a
reduced
role
in
African
developprojected
to
rise
dramatically
to
99%
of
The
changing
environmental
land
play
a
reduced
role
in
African
developthe way employment activities were capcountries
veryarelow
wage
between 2005/06
and to be
Bank, 2012).
In typically
addition,have
youth
more
likely non-farm
than anyworkers
other demographic
category
the
African
population.1010
scape threatens
threatens to increase poverty
and
ment
over
50
InInthe
past,
the
African
population.
scape
poverty
and
ment
overthe
thenext
nextEICV2
50years.
years.
the
past,
unpaid
family
workers.
tured between
the
and the
EICV3.
employment.
The lack of job opportunities2010/11. However,
men made
up only
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
African
healthcare
systems
tion
health
Addressing
African
healthcare
systemshave
havebeen
beenheavheavWith regard
to the demographic
transition,
has a gender
dimension, with
women
44% of the estimated
477,000
workers
While the majority of Rwandans are engaged inthe
non-wage
employment,
the percentage
fell
the
health impacts
climate
change
ily
reliant
on
international
donor
funding
health
from
change
ily
reliant
on
international
donor
funding
most of the increase in female unpaid labor
spending more time on non-remunerated
who moved out of independent/agricultural
sharply
fromresources,
73% inand
2005/06
to
64% of
in
human
resources,
and
inthe
theprovision
provision
of 2010/11 (Table 4). This decline was largely
from
development
human
in
from
developmentbanks,
banks,UN
UNagencies,
agencies,
is among youth, and research shows that
activities than do their male counterparts.
self-employment. Women were disproporattributable
to a healthcare
sharp
dropservices.
in the E-Health,
percentage
male the
workers
in non-wage
employment—
high-quality
healthcare
services.
E-Health, ofwhich
which
the
is ill-equipped
to
and
organizations
such
asasthe
Global
high-quality
continent
ill-equipped
to
and
organizations
such
the
Global
most youth in Africa start out as unpaid
According to the 2013 WDR, at least 85%
tionately represented among the increase
from for
68%
to 51%—as
men
moved
out
of
agricultural
self-employment
to
wage
non-farm
forexample,
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
can expand service delivery
handle.
Increased climate variability and
Fund.
In light of the uncertain condition
family workers—assisting relatives in vaof women in SSA are in non-wage
in the number of unpaid family workers.
employment.
By
contrast,
among
female
workers,
non-wage
employment
fell
by
just
3
and
ensure
greater
accountability
in
health
the
expected
temperature
warming
will
of
the
global
and ensure greater accountability in health
the expected temperature warming will
of the globaleconomy,
economy,African
Africancountries
countries
rious income-generating activities or runemployment, compared with 75% of men
Specifically, the number of women aged
percentage
points
during
this
period.
services
through
error
reduction,
diagwill
need
to
reevaluate
their
services through error reduction, diagwill need to reevaluate theirrelationships
relationships
ning errands (Chant and Jones, 2005). Gi(World Bank, 2012). In addition, youth
are
15 to 64 who were unpaid family workers
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
ven this pattern, the initial movement into
more likelyfor
than
anyofother
demographic
rose
by an estimated
350,000
during
the
Men accounted
75%
the estimated
590,000
increase
in the number
ofboth
wage
non-farm
also
increase
the
transparency
of
medical
across
the
continent,
through
direct
partners
and
possibly
look
more
also increase the transparency of medical
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
workers
between
2005/06
men
made
up only
44% change
ofwhile
the will
estimated
unpaid family work may not be permanent,
category
to be
unpaid and
family2010/11.
workers. However,
2005/06-to-2010/11
period,
the
procurement
and
distribution
operations.
and
indirect
channels.
Climate
South
and
private–public
partnerships.
procurement and distribution operations.
and indirect channels. Climate change will
South and private–public partnerships.
477,000
workers who moved out of independent/agricultural
self-employment.
Women
were
and young people may later be able later
number of men
an estimated
exacerbate
fooddecreased
and water
waterby
insecurity
and
exacerbate
food
and
insecurity
and
disproportionately
represented
among the
increase
in thethenumber
of unpaid
family
workers.
to engage in income-generating
activities.
While
the majority
of Rwandans
are
76,000.
streamlining
processes,
reducingwaitwaitthreaten
livelihoods and
of
domestic
bybystreamlining
processes,
reducing
threaten
the livelihoods
and health
health
of many
many
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
Specifically,
the
number
of
women
aged
15
to
64
who
were
unpaid
family
workers
rose
by
an
With
regard
to
gender
roles,
young
girls
engaged
in
non-wage
employment,
the
ingtimes,
times,and
andimproving
improvingthe
theaccuracy
accuracyof
of
African populations.
populations. Droughts
the
ing
African
Droughts are
are likely
likely
the involvement
involvementofofnew
newinternational
internationalaid
aid
These
gender
trends—a
shiftboth
frominagriperform a variety of chores and may spend
percentage fell sharply from 73% in
to
become
more
prevalent,
freplayers.
to become more prevalent, both in freplayers.
cultural and
self-employment
to unpaid
work
more time at gardening, water collection
quency
severity,
reducing
farm
yields
92005/06
Ibid. to 64% in 2010/11 (Table 4). This
9 Ibid.
17 quency and severity, reducing farm yields
10
Ibid. was largely attributable to a sharp
for
women
and
to
non-farm
wage
employand child care than do their male counterdecline
and increasing hunger and starvation, par10 Ibid.
and increasing hunger and starvation, par11
13 AfDB, A Strategic Framework for Improving
11drop in the percentage of male workers in13
AfDB,
A Strategic
Framework
for Improving
ment forinmen—may
be partly
parts.
Finally,
it is possible
that women
are
ticularly
Southern Africa
andexplained
the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
for
health. Examples
include treating patients,
non-wage
employment—from
68% conto
for health. Examples include treating patients, conducting research, educating the health workforce,
51%—as
meneducating
moved the
outhealth
of agricultural
ducting
research,
workforce,
tracking diseases and monitoring public health.”
tracking
diseases
and
monitoring
public
health.
”
self-employment to wage non-farm
by rural-urban location. Among female
workers in urban areas, the percentage
12 Economist Intelligence Unit (2011).
12
Economist
Intelligence Unit
(2011).
engaged
in agricultural
self-employment
Oct.
2012. in unpaid labor in combination
engaged
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
withAfDB,
otherA“mini”
income
generating
14
Strategic
Framework,
” op. cit. acti15 Ibid.
15
Ibid.
vity, which information was not captured
15
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
AnalysisofofGender
Genderand
and
Youth
YouthEmployment
EmploymentininRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
in the EICV2 survey. In 2011, the EICV3
rapid
rapideconomic
economicgrowth
growthhas
hasboosted
boosted the
the
survey collected information on labor force
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infrastatus during
the high and low seasons
structure
structureand
andtotosurvival-enhancing
survival-enhancingsocial
social
whereasIninspite
2005,
no
similar
information
services.
of
this,
issues
of
governservices. In spite of this, issues of governwasand
collected. Indeed
in the EICV3
survey,
ance
ance andincome
incomeinequality
inequalityhave
havehampered
hampered
at least 50% individuals surveyed indicated
having a secondary activity—during the-
high
and
low
seasons.
Consequently,
the
cient,
remains
high,
and
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
nature of
information
collected
in
10detailed
countries
worldwide
were
10most
mostunequal
unequal
countries
worldwide
were
ininSub-Saharan
Sub-SaharanAfrica.
Africa.3 3While
Whilepoverty
povertyhas
has
declined
declinedbyby9%
9%over
overthe
thepast
past20
20years,
years,this
this
meetthe
theMDG
MDGgoal
goalofofhalving
halvingpoverty
povertyby
by
meet
-ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
ulation
on
$1.25
or
less
a
day
(PPP
adjusted).
As
on $1.25 or less a day (PPP adjusted).44As
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
ruraldwellers
dwellersand
andother
othermarginalized
marginalizedpoppoprural
ulations
bearing
a
disproportionate
burden.
ulations bearing a disproportionate burden.
Overthe
thenext
next50
50years,
years,ititisisprojected
projectedthat
that
Over
the
continent’s
economic
growth
rate
will
the continent’s economic growth rate will
5
continueatataround
around5-6%
5-6%per
perannum.
annum.5
continue
extent
to
which
this
translates
intobetter
better
extent to which this translates into
healthoutcomes
outcomesthough
thoughisiscontingent
contingenton
on
health
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
levelofofbudgetary
budgetaryallocations
allocationstotothe
thesector
sector
level
2011 may also partly explain the changes
young
in order
order
young population
population will
will be
be critical
critical in
in female unpaid labor force rates.
to
harness
the
potential
of
the
youth
bulge
to harness the potential of the youth bulge
and
divandcapture
capture the
the so-called
so-called ‘demographic
‘demographic divAlthough
trends in youth
employment
geidend.
’
Concurrently
though,
Africa
has
an
idend.’ Concurrently though, Africa has an
nerally
followed
those
of
overall
employaging
aging population.
population. In 2010, people aged 60
ment,
the increase infor
wage
emor
older
just non-farm
6% of Africa’s
or older accounted
accounted
ployment was
greater
for youth. For
population,
but
is expected
population,
but this
to rise to
instance,
the
percentage
of
workers
13%
over
the
next
50
years
(Figure
1). aged
Some
13% over the next
15
to
34
in
wage
non-farm
employment
countries,
countries, such
such as Liberia and Nigeria, are
expected
to
expected to double
double their population size
increased by 15 percentage points bet-
in less
less than
than 20
20 years.
years.88
in
ween 2005/06 and 2010/11, compared
African subregions
subregions are
areexpected
expectedtotogrow
grow
African
with
an
11-percentage-point
increase
for
the fastest,
fastest, tripling
triplingtheir
theirpopulations
populationsover
over
the
workers overall. The increase in youth em-
ployment
was
in domestic
youth
bulge
andpredominantly
populationaging
aging
willexert
exert
youth
bulge
and
population
will
services
and
construction.
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highlightingthe
theneed
needto
toaddress
addressfamily
familyplanning
planning
lighting
6
In 2010/11,
the 15- to-19
age
group
accountedand
for
services,
maternal
and
child
healthcare,
services, maternal and child healthcare, and
20% of the working-age population (15 to 64).
Ibid.
88 Ibid.
Figure 1. Africa’s population will double
Figure
double inin size
sizeby
by2050
2050
Population size in 2010
Population
deployedtotorespond
respondtotoemerging
emergingchalchalbebedeployed
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsofofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
severe health challenge. African demograsevere health challenge. African demogra-
Predicted population size in 2050
Predicted population size in 2050
people living in Africa today, and it is the
people living in Africa today, and it is the
only continent that is expected to double in
only continent that is expected to double
in
size by 2020, to reach 2.7 billion.66 What is
size by 2020, to reach 2.7 billion. What is
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.7 7 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3 Health
AfDB,in “A
Strategic
Framework for Improving
Africa”
(2012).
Health
in Africa”
4 WHO,
Atlas (2012).
of Health Statistics (2011b).
4 5 WHO,
of in
Health
Statistics
AfDB,Atlas
Africa
50 Years’
Time (2011b).
(2011a).
5 6 AfDB, Africa in 50 Years’ Time (2011a).
6 Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
(2011b).
7 AfDB,
Africa in 50
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
A f r i c a n
A f r i c a n
16
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Youth Employment
in Rwanda
Analysis of Gender
and
Youth Employment in Rwanda
streamliningprocesses,
processes,reducing
reducingwaitwaitbybystreamlining
ing times, and improving the accuracy of
ing times, and improving the accuracy of
9 Ibid.
9 Ibid.
10 Ibid.
1011 Ibid.
11formation and communication technologies (ICT)
formation
communication
technologies
(ICT)
for health.and
Examples
include treating
patients,
conforducting
health. research,
Exampleseducating
include treating
patients,
conthe health workforce,
ducting
research,
the health
tracking
diseases educating
and monitoring
publicworkforce,
health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
-1.5
23.9
-14.1
2.2
-10.4
-0.5
19.5
-16.3
3.1
-5.8
15.3
12.3
32.3
11.5
28.6
13.8
36.2
18.2
13.7
18.2
-2.7
5.7
-14.7
1.4
10.1
17.4
5.5
23.7
9.5
44.0
14.7
11.2
9.0
10.9
54.1
13.8
12.7
44.9
10.6
18.0
13.3
32.2
28.6
13.7
12.2
-2.1
3.3
-13.8
1.3
11.3
16.3
5.1
33.2
8.5
36.9
14.2
8.4
19.4
9.9
48.2
-2.1
14.2
-14.4
1.8
0.5
-1.4
10.6
-14.8
2.1
3.5
domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
the involvement of new international aid
the involvement of new international aid
players.
players.
13 AfDB, A Strategic Framework for Improving
13 AfDB,
A Strategic
Framework
for Improving
Health
in Africa
(2012); WHO
Fact Sheet
No. 266,
Health
in Africa (2012); WHO Fact Sheet No. 266,
Oct.
2012.
Oct.AfDB,
2012. A Strategic Framework,” op. cit.
14
14 Ibid.
AfDB, A Strategic Framework,” op. cit.
15
15 Ibid.
17
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
Source:
Authors’
calculations
from EICV2,
2005
and 2011
EICV3,
2011 datasets
Source:
Authors’
calculations
from EICV2,
2005 and
EICV3,
datasets
6.5
37.7
15.3
19.2
21.4
5.0
55.6
5.1
19.2
15.1
16.4
8.6
27.6
10.4
37.1
6.4
37.1
20.9
19.0
16.5
5.4
49.4
11.0
20.8
13.4
humanaspects,
aspects, mediating
mediating health
health outcomes
human
outcomes
across
the
continent,
through
across the continent, through both
both direct
direct
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
threatenthe
the livelihoods
livelihoods and
and health
threaten
health of
of many
many
African populations. Droughts are likely
African populations. Droughts are likely
to become more prevalent, both in freto become more prevalent, both in frequency and severity, reducing farm yields
quency and severity, reducing farm yields
and increasing hunger and starvation, parand increasing hunger and starvation, particularly in Southern Africa and the Sahel
ticularly in Southern Africa and the Sahel
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditional
traditionalinternational
internationaldonors
donorstotodeveldeveloping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelopment
ment over
over the
thenext
next50
50years.
years.InInthe
thepast,
past,
African
healthcare
systems
have
been
heavAfrican healthcare systems have been heavily
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
from
development
banks,
UN
agencies,
from development banks, UN agencies,
and
and organizations
organizations such
such asasthe
theGlobal
Global
Fund.
In
light
of
the
uncertain
condition
Fund. In light of the uncertain condition
of
of the
the global
globaleconomy,
economy,African
Africancountries
countries
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
South
and
private–public
partnerships.
South and private–public partnerships.
14.3
22.7
13.2
12.2
37.6
15.0
12.7
25.8
11.8
34.8
12.8
27.9
11.9
13.3
33.9
which the
the continent
continent is
is ill-equipped
ill-equipped to
which
to
handle.
Increased
climate
variability
and
handle. Increased climate variability and
the expected
expected temperature
temperature warming
the
warming will
will
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and the consequent altered length of
seasons. Climate change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
global population at risk of dengue fever
global population at risk of dengue fever
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.1313Furthermore,
by
the
rapid
and
unplanned
urbanization
that
the rapid and unplanned urbanization that
happeningon
onthe
thecontinent
continentisisfraught
fraught
isis happening
--cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
tivity,
nutrition,
transportation,
water
and
tivity, nutrition, transportation, water and
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
Total
Na!onal
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
Youth (15 to 34)
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
Urban
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
Youth (15 to 34)
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
Rural
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
Youth (15 to 34)
Wage farm
Wage non-farm
Independent farmer
Independent non-farmer
Unpaid family worker
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
for
example,
can
expand
service
delivery
for example, can expand service delivery
andensure
ensuregreater
greateraccountability
accountabilityininhealth
health
and
services
through
error
reduction,
diagservices through error reduction, diag11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
also
increase
the
transparency
of
medical
also increase the transparency of medical
procurementand
anddistribution
distributionoperations.
operations.
procurement
regions. Various infectious diseases includregions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
15.2
8.5
38.4
9.5
28.5
13.9
12.5
35.9
10.8
26.8
12.5
23.6
21.7
13.0
29.2
The changing
changing environmental land
The
land -scape threatens
threatens to increase poverty and
scape
and
health
problems
in
Africa.
Addressing
health problems
Addressing
the health
health impacts
impacts from climate change
the
change
AfDB
AfDB
13.8
19.1
23.5
11.6
32.0
-1.2
16.8
-6.9
-0.9
-7.6
-1.3
10.8
-7.1
0.9
-4.4
6.1
52.3
15.3
18.7
8.7
6.1
49.8
10.6
19.7
13.8
4.9
66.6
3.7
18.7
6.2
-1.6
19.5
-13.6
1.0
-5.4
6.8
25.1
20.1
18.7
29.3
5.2
44.6
6.5
19.7
23.9
-1.5
17.9
-10.2
0.0
-6.3
-2.2
15.2
-13.9
1.5
-0.9
opportunity to
to improve health systems.
opportunity
systems.
100
-1.4
11.1
-14.3
2.2
2.4
12
12
Total
2011
(%)
100
2005
Change
(% points)
-
health
healthsector.
sector.Internet
Internetbroadband
broadbandpenepenetration
trationhas
hasrisen
risenrapidly,
rapidly,from
fromaameager
meager
0.1%ofofthe
thepopulation
populationinin2000
2000totoan
anestiesti0.1%
mated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverageisis
mated
projectedtotorise
risedramatically
dramaticallytoto99%
99%of
of
projected
theAfrican
Africanpopulation.
population.1010
the
-tion
provides
the
opportunity
to
overcome
tion provides the opportunity to overcome
data.
countries
data.At
Atpresent,
present, 80% of African countries
claim
m-health
claimto
tobe
be using
using telemedicine or m-health
(also
known
as
mobile
health),
although
(also known as
although
the
still in
in
the majority
majority of
of these projects are still
their
infancy.
In
this
respect,
scaling
up
their infancy. In
scaling up
-1.0
12.3
-9.9
1.8
-3.1
technology
technology(ICT)
(ICT)revolution
revolutionin
inAfrica
Africa
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
-0.9
13.5
-13.0
2.7
-2.2
6.8
22.6
26.8
19.3
24.4
5.9
36.1
13.8
22.0
22.2
4.8
63.1
8.2
19.6
4.3
-1.6
23.1
-13.2
1.7
-10.1
13.9
18.3
28.9
12.8
26.2
-2.6
8.1
-14.6
1.5
7.5
15.9
8.1
23.2
10.7
42.1
13.3
16.2
8.6
12.2
49.6
12.3
41.4
15.7
14.5
16.1
-0.7
18.6
-14.9
2.8
-5.6
12.6
18.6
40.2
11.9
16.5
-2.1
5.0
-13.8
1.6
9.3
15.1
7.3
32.4
9.9
35.3
13.0
12.3
18.6
11.5
44.6
12.0
37.2
25.3
14.7
10.9
100
Change
(% points)
2005
Male
2011
(%)
100
Change
(% points)
Female
2011
2005
(%)
100
100
Table 4: Distribution of employed, by gender, occupational activity, youth status and rural-urban location, population aged 15
to 64,
Rwanda,
2005/06byand
2010/11
Table
4. Distribution
of employed,
gender,
occupational activity, youth status and rural-urban location, population aged 15 to 64, Rwanda, 2005/06 and 2010/11
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
In 2010/11, the median monthly salary for men
The EICVs collected data on wages for all employed persons.
rapid
young
will be
be
critical in
in order
order in
in less
less than
than 20
20years.
years.8 8 was RWF 22,000,
rapideconomic
economic growth
growth has
has boosted
boosted the
the
young population
population will
critical
RWF 13,200 for women (Table 5). Moreover,
Wages paid for short durations (for example, daily or weekly) were
amount
African subregions
subregionsare
areexpected
expectedtotogrow
grow
to
potentialcompared
of the
the youth
youthwith
bulge
amountofofresources
resourcesallocated
allocatedto
tohealth
healthinfrainfraAfrican
to harness
harness the
the potential
of
bulge
between
2005/06
and
2010/11,
the
gender
pay
gap
widened—
converted
into
a
monthly
amount.
Median
values
are
presented
structure
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
the
from aAfrica
percentage
difference of about 33% to 67%.
rather than
average
values,
which
vary
widely with
age,
education, though,
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
has
an
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
and work
experience.
ance
aging
In 2010,
2010, people
people aged
aged 60
60 youth
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In
or
older
accounted
for
just
6%
of
Africa’s
increasing
pressure
on
health
systems,
highor older accounted for just 6% of Africa’s
increasing pressure on health systems, highTable 5. Median monthly wages, by gender,
occupation
category,
employment
sector
and
education,
Rwanda,
2005/06
and
2010/11
population,
this is
is expected
expected to
to rise
rise to
to lighting
-lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
population, but
but this
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
services,
maternal
and
child
healthcare,
and
Total
Youth
(15
to
34)
cient, remains high, and in 2010, six of the
(Figure 1). Some
services, maternal and child healthcare, and
2011
2005 such as Liberia
2005
10
countries,
Nigeria, are
are 2011
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
Nigeria,
Averageand
annual
Average annual
% change
% change
RWFhas
RWF
33
ininSub-Saharan
Africa.
While
poverty
expected
to
double
their
population
size
Sub-Saharan Africa. While poverty has
population size
Ibid.
Total
18,000
6,600
34.5
7,200
35.6
8820,000
Ibid.
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Female
13,200
6,600
20.0
15,400
6,600
26.7
Male
22,000
8,800
30.0
22,000
8,800
30.0
6,600
13.3
11,000
6,600
13.3
6,600
13.3
11,000
6,600
13.3
6,600
20.0
13,200
6,600
20.0
17.3
25,000
15,000
meet
the
goal
meet
theMDG
MDG
goalof
of halving
halving poverty
poverty by
by
Occupation
category
Wage farm
11,000
-Female
11,000
ulation
(excluding
ulation
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
Male
13,200
on
or
on$1.25
$1.25
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
Figure 1. Africa’s population
population
will double
double
size15,400
by2050
2050
will
ininsize
by
13.3
26,000
Wage non-farm
27,000
16,200
Female
25,000
13,400
improving
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
health
Male
28,600
rural
dwellersand
andother
othermarginalized
marginalized poppoprural
dwellers
Public
42,000
Female
39,980
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
Male
44,000
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Over
Private (formal)
33,000
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
Female
25,000
continue
at around 5-6% per annum.55 33,000
continue
Maleat around 5-6% per annum.
extent
to
whichthis
this translates
translates into
into better
better
extent
which
Privateto
(informal)
15,000
12,100
healthFemale
outcomesthough
though isis contingent
contingent on
on
health
outcomes
Male of factors, including not only the
17,600
a
number
a number of factors, including not only the
Education
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
Population size in 2010
201010.1
19,000
26,400
13.8
13.3
13.0
23,000
16.5
38,800
22,500
14.5
15,000
33.3
36,725
20,000
16.7
26,000
13.8
39,925
23,000
14.7
15,400
22.9
33,000
15,000
24.0
13,200
17.9
26,400
13,200
20.0
20,000
13.0
33,000
15,000
24.0
6,600
25.5
15,400
6,600
26.7
6,600
16.7
13,200
6,600
20.0
6,600
33.3
19,800
6,600
40.0
None
13,200
6,600
20.0
13,200
6,600
20.0
Primary
16,000
6,600
28.5
17,000
6,600
31.5
27,000
12.6
40,000
22,600
15.4
111,000
19.6
182,000
67,000
34.3
6,600
13.3
11,000
6,600
13.3
6,600
20.0
13,200
6,600
20.0
24,000
12.8
35,500
21,600
12.9
150,000
64,000
26.9
bedeployed
deployed
torespond
respond to
to emerging
emerging chalchalbe
to
Secondary
44,000
lenges.
Equitable
access
and
treatment
for
220,000
lenges.Postsecondary
Equitable access and treatment for
Femalesegments of society is one critical
thepoorest
poorest
the
segments of society is one critical
None
11,000
challenge.
challenge.
Primary
13,200
Secondary
Postsecondary
39,400
170,000
severeMale
healthchallenge.
challenge.African
Africandemogrademograsevere
health
None
Primary
people
living
Predicted population
in
population size
size
in 2050
2050
28.6
Predicted
70,000
15,400
6,600
26.7
17,200
6,600
32.1
20,000
the
8,800
25.5
21,000
8,800
27.7
13.3
44,000
23,000
18.3
22.5
200,000
96,000
21.7
inAfrica
Africatoday,
today, and
and itit isis the
peopleSecondary
living in
50,000
30,000
only
continent
that
is
expected
todouble
double in
in
only continent
that is expected to
Postsecondary
267,900
126,000
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.66 What
What is
is
size
Source:
from EICV2,
more,
theAuthors’
majoritycalculations
of this population
will 2005 and EICV3, 2011
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
18
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
People with postsecondary education
postsecondary education, median wages
received the highest pay, but gender gap
for youth were lower.
was
widest
for
individuals
with
In the public sector, median wages were
postsecondary attainment.
AfDB
AfDB
sector
RWFinfectious
15,000 indiseases
the informal
regions.and
Various
includregions. Various infectious diseases includsector.
Yet even
in the diarrhea,
public sector,
a
ing malaria,
cholera,
dengue
ing malaria, cholera, diarrhea, dengue
gender
wage
gap
was
apparent-in
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
2010/11, the median female monthly
27% higher than those in the private formal
Nonetheless, between 2005/06 and
2010/11, the gender wage gap increased
for all educational attainment groups
except
those
with
postsecondary
education, among whom the difference
narrowed.
The overall widening of the gender wage
gap may be partly explained by men’s
higher educational attainment (Figure 2),
and consequently, better jobs. However,
wage gaps related to gender cannot be
solely attributed to women’s lower
educational attainment. Studies in other
developing
countries
suggest
that
discrimination may be a factor (Appleton
et al., 1999).
technology
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
isis
rapidly
increasing
connectivity
across
rapidly
increasing
across
Youth
wages
were connectivity
relatively high—the
median salary of 15- to 34-year-olds was
health
Internet
penehealth
sector.
Internet
broadband
peneaboutsector.
10%
more
than broadband
that
of the general
tration
has
risen
rapidly,
from
a
meager
tration
has
risen
rapidly,
from
a
meager
population (Table 5). These differences
0.1%
the
2000
an
0.1%
thepopulation
population
infemale
2000to
to
anestiestiwereofof
driven
mainly byin
earnings,
99
mated
7%
in
2010.
By
2060,
coverage
mated
7%
in
2010.
By
2060,
coverage
isis
since the median wages for male youth
projected
torise
risewere
dramatically
to 99%
99%
of
projected
dramatically
of
and men to
overall
the same.toBut
when
theAfrican
Africanpopulation.
population.1010
the
-educational attainment was taken into
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
tion
account, youth wages were, on average,
about 10% less than those of the general
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
population. In the wage-farm category, the
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
monthly median for youth was the same
forexample,
example,can
canexpand
expandservice
servicedelivery
delivery
for
as for the general population—RWF
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
11,000 in 2010/11. However, in this
services
through
error
reduction,
diagservices through error reduction, diagcategory, gender gaps emerged;
in
11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
2005/06, median wages for youth were
alsoincrease
increasethe
thetransparency
transparencyof
ofmedical
medical
also
nearly the same regardless of gender, but
procurementand
anddistribution
distributionoperations.
operations.
procurement
by 2010/11, male youth earned about
20%
more than
did reducing
their female
streamlining
processes,
waitbybystreamlining
processes,
reducing waitcounterparts.
At
lower
levels
ofaccuracy
education,
ing
times,
and
improving
the
of
ing times, and improving the accuracy of
median wages for youth were the same as
9those
Ibid. for the general population, but
9 Ibid.
10
Ibid. people with secondary or
among
10 Ibid.
11
11
formation and communication technologies (ICT)
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
wage
was about
10%of
lower
than the male
geographical
range
vector-borne
disgeographical range of vector-borne diswage.
Thisbeen
maylinked
reflectwith
the relatively
small
eases has
regional warmeases has been linked with regional warming and the
consequent
private informal sector (Figure 6). In
number
of women
withaltered
publiclength
sectorof
ing and the consequent altered length of
seasons. Climate
could increase
the
2010/11, the median monthly wage in the
employment
and change
the tendency
for men to
seasons. Climate change could increase the
populationmost
at riskofof malaria
in Africa by
public sector was RFW 42,000, compared
occupy
the high-paying
population
at risk of
malaria
in Africa by
anadditional
additional
170 million by 2030 and the
with RWF 33,000 in the private formal
managerial
jobs.
an
170 million by 2030 and the
global
population
riskofofdengue
denguefever
fever
global population atatrisk
13
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.13 Furthermore,
by
Figure 6. Average monthly wages, by genderthe
andrapid
typeand
of wage
employment,
unplanned
urbanization
that
the rapid and unplanned urbanization that
Rwanda, 2005/06 and 2010/11 is happening on the continent is fraught
is happening on the continent is fraught
--cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
data. At present,
countries
tivity, nutrition, transportation, water and
claim
m-health sanitation,
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
claim to
to be
be using telemedicine or m-health
1515
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
(also known
although
impact on the burden of diseases.
the
still in
in
the majority
majority of these projects are still
their
scaling up
up
their infancy.
infancy. In this respect, scaling
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
12
12
opportunity
systems.
traditionalinternational
internationaldonors
donorstotodeveldevelopportunity to improve health systems.
traditional
oping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011 datasets
The changing
changing environmental land
play
The
land-play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelopscape threatens
threatens to increase poverty
ment
scape
poverty and
and
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
health problems
problems in Africa. Addressing
African
health
Addressing
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavthe health
health impacts from climate change
ily
reliant
on
international
donor
funding
the
change
ily
reliant
on
international
donor
funding
employment rose in both the formal and
4.3. Informal sector
from
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
informal sectors, the increase was much
employment
which the
the continent is ill-equipped
and
organizations
such
asasthe
Global
which
ill-equipped to
to
and
organizations
such
the
Global
faster in the informal sector, especially for
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
handle.
Increased climate variability and
Fund. In light of the uncertain condition
The informal sector generally has lower
men. As noted above, this appears to be
the
expected
temperature
warming
will
of
the expected temperature warming will
of the
the global
globaleconomy,
economy,African
Africancountries
countries
productivity than the formal sector (World
driven by construction.
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
Bank, 2012). Table 6 disaggregates wage
human aspects,
aspects, mediating
mediating health
human
health outcomes
outcomes with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
employment into agricultural and nonIn 2010/11, close to a third (32%) of male
across
the
continent,
through
both
direct
partners
and
possibly
look
more
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
agricultural and into public, private-formal
workers were in private informal wage
and
indirect
channels.
Climate
change
will
South
and
private–public
partnerships.
and indirect channels. Climate change will
South and private–public partnerships.
and private-informal.
employment, compared with 18% of
exacerbate
food and
and water
water insecurity
exacerbate
food
insecurity and
and
female workers.
The share of male
workers
threaten the
the livelihoods
livelihoods and
threaten
and health
health of
of many
many domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
An
estimated
1.25
million
Rwandans
were
in
informal
wage
employment
rose
by 11
African populations.
populations. Droughts
the
African
Droughts are
are likely
likely
the involvement
involvementofofnew
newinternational
internationalaid
aid
employed
in the
informalboth
sector
in
percentage points between 2005/06 and
to
become
more
prevalent,
in
freplayers.
to become more prevalent, both in freplayers.
2010/11—an
increase
of farm
about
6
2010/11, compared with an increase of
quency
and
severity,
reducing
yields
quency and severity, reducing farm yields
percentage
points
overand
2005/06.
And while
less than 2 percentage-points for women.
and
increasing
hunger
starvation,
parand increasing hunger and starvation, par13 AfDB, A Strategic Framework for Improving
13 AfDB, A Strategic Framework for Improving
ticularly in Southern Africa and the Sahel
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
Health in Africa (2012); WHO Fact Sheet No. 266,
sector and more than double those in the
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
19
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
Table 6. Distribution of employed, by wage/non-wage, gender, industry and sector, population aged 15 to 64, Rwanda,
8
rapid
growth
has
young
will be
be critical
critical in
in order
order
rapideconomic
economic
growth
has boosted
boosted the
the
young population
population will
2005/06
and 2010/11
amount
of
resources
allocated
to
health
infrato
harness
the
potential
of
the
youth
bulge
amount of resources allocated to health infra-% to harness the potential of the youth bulge
structure
and
so-calledChange
‘demographicdivdivstructureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
‘demographic
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
though,
Africa
has
an
services. In spite of this, issues of govern-2010/11
idend.’ Concurrently
Africa has an
2005/06 though,
(% points)
ance
and
aging
In 2010,
2010, people
people aged
aged 60
60
National
ance
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In
Wage
34.7
25.3
9.4
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
Agricultural
12.1
13.4
-1.3
population,
this is
is expected
expected to
to rise
rise to
to
-population, but
but this
Non-agricultural
22.5
11.9
10.6
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
cient, remains high, and in 2010, six of the
(Figure 1). Some
10
unequal
countries
worldwide
were
countries,
such
Nigeria,
are
10most
most
unequal
countries
worldwide
were
as
Liberia
and Nigeria,
Public
4.0
3.2
0.8are
33
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
Private-Formal
6.0
3.2
Sub-Saharan
Africa. While poverty has
population2.7
size
Private-Informal
24.7
18.8
5.8
declined
by
declined
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Non-wage
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
Self-employment
-Family worker
ulation
(excluding
ulation
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
Female
Wage
on
or
on$1.25
$1.25
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
Agricultural
Non-agricultural
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
ruraldwellers
dwellers
and
other
marginalized
poprural
and
other
marginalized
popPublic
ulations
bearingaadisproportionate
disproportionateburden.
burden.
ulations
bearing
Private-Formal
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Private-Informal
Over
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
Non-wage
continue
around5-6%
5-6% per
per annum.
annum.55
continue
atataround
Self-employment
extentto
towhich
whichthis
this translates into better
extent
Family
worker translates into better
health
outcomesthough
though isis contingent
contingent on
on
health
Maleoutcomes
a
number
of
factors,
including
not
only
the
Wage
a number
of factors, including not only the
Agricultural
level
of
budgetary
allocations to
to the
the sector
sector
level of budgetary allocations
Non-agricultural
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
Public
lenges.
Equitable
access
and
treatment
for
lenges.Private-Formal
Equitable access and treatment for
thepoorest
poorest
segmentsof
ofsociety
societyisisone
onecritical
critical
Private-Informal
the
segments
challenge.
challenge.
Non-wage
Self-employment
Family worker
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
Youth (15 to
34)
Wage
people
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
peopleAgricultural
living
only
continent
that
is
expected
to
double
in
Non-agricultural
only continent that is expected to double in
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.66 What
What is
is
size
Public
more, the majority of this population will
more,Private-Formal
the majority of this population will
belong to the youth cohort. Africa is the
belongPrivate-Informal
to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have
the largest workforce in the world
Non-wage
to have
the
largest workforce in the world
7
Self-employment
by 2040.
7 Ensuring the good health of this
by 2040. Ensuring the good health of this
Family worker
Female
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
Wage
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
Agricultural
45 WHO,
Atlas
of
Statistics
(2011b).
AfDB,
Africa inHealth
50 Years’
Time (2011a).
Non-agricultural
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Public
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
Private-Formal
7 AfDB,
Africa in 50 Years’ Time (2011a).
Private-Informal
in less
less than
than 20
20years.
years.8
in
African
subregions
areexpected
expectedtotogrow
grow
African
subregions are
Thousands
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
Change
2010/11
2005/06
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
youth
1,769
1,440
329
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, high618
763 family planning
-145
lightingthe
the
needtotoaddress
address
lighting
need
family planning
1,151
677
474
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
services,
206
304
Ibid.
88 Ibid.
1,259
162
167
1,111
44
137
148
3,335
1,865
1,470
3,590
2,298
1,293
-256
-433
177
650by
3.0will
Figure 21.2
population
will double
doubleininsize
size
by2050
2050578
1. Africa’s population
65.4
36.5
28.8
74.7
47.8
26.9
-9.3
-11.3
1.9
24.2
12.5
11.8
14.3
6.9
-1.9
4.9
182
387
390
188
72
-208
199
2.7
3.1
18.3
2.2
2.2
16.8
0.5
0.9
1.5
74
84
492
54
56
467
20
28
25
75.8
32.6
43.2
78.8
43.4
35.3
-3.0
-10.8
7.9
2,036
877
1,159
2,029
1,117
909
7
-241
250
47.3
11.7
35.6
30.1
12.3
17.8
17.2
-0.6
17.8
1,092
269
823
862
352
510
230
-83
313
5.6
9.4
32.4
4.5
4.5
21.2
1.1
4.9
11.2
129
216
747
128
128
607
2
88
140
1,218
953
265
1,562
1,186
375
-344
-234
-110
Population size in 2010
2010
52.7
69.9
-17.2
41.2Predicted
53.1
-11.9
population
2050
Predicted
population size
size in
in-5.3
2050
11.5
16.8
43.8
14.0
29.8
25.9
15.9
10.0
17.9
-1.9
19.8
568
182
379
232
189
-50
3.0
6.1
34.7
1.9
2.2
21.8
1.0
3.9
13.0
38
79
451
28
33
318
10
47
132
56.2
17.3
38.9
73.5
27.7
46.4
-17.3
-10.4
-7.5
728
224
504
1,052
396
664
-324
-172
-160
34.6
23.1
11.5
236
205
31
-2.9
14.4
93
142
147
58
-54
85
1.0
2.3
8.2
17
30
188
15
19
171
3
11
17
13.7Source: AfDB
16.6(2011a).
20.9Source: AfDB
6.5 (2011a).
2.6
4.4
27.6
1.6
2.1
19.4
20
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
Private-Informal
27.6
19.4
8.2
65.4
16.4
49.1
76.9
26.3
50.6
-11.5
-9.9
-1.5
54.1
14.4
39.7
29.5
15.2
14.1
24.7
-0.8
25.6
Public
Private-Formal
Private-Informal
3.4
8.0
42.7
2.3
2.4
24.7
1.1
5.7
17.9
Non-wage
Self-employment
Family worker
45.9
17.4
28.5
70.6
29.3
41.3
-24.7
-11.9
-12.8
Non-wage
Self-employment
Family worker
Male
Wage
Agricultural
Non-agricultural
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011 datasets
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011 datasets
Although the estimated number of
This was driven by a decline in the
women in wage employment increased
number of workers in agriculture and an
from 580,000 in 2005/06 to 650,000 in
increase
2010/11, the male-female gap widened.
employment, especially among men.
Women’s wage employment increased by
Youth made up the bulk of male unpaid
in
informal
sector
wage
3 percentage points (from 21% to 24%),
family workers—in 2005/06, 62% of all
compared with 17 percentage points for
data.
At
present,
80%
of African
countries
data.
Atmale
present,
unpaid
family
workers
werecountries
aged 15
claim
be
using telemedicine
m-health
claim
toby
be2010/11,
or m-health
to 24;to
the figure had
risen to
(also
known
as
mobile
health),
although
(also
66%.known
By contrast, most femalealthough
unpaid
the
majority
of
these
still
in
the
majority
projects
are
in
family workers (72%) were aged still
25 or
their
infancy.
In
this
respect,
scaling
up
their
scaling up
older.infancy.
technology
(ICT)
revolution
in
technology
(ICT)
revolution
in Africa
Africa
men (from 30%
to 47%).
In 2010/11,
76%
isis
rapidly
increasing
connectivity
across
connectivity
across
ofrapidly
femaleincreasing
workers were
in non-wage
employment, compared with 53% of male
health
sector.
Internet
broadband
penehealth
sector.
Internetthe
broadband
peneworkers.
Moreover,
percentage
of
tration
has
risen
rapidly,
from
a
meager
tration
has
risen
rapidly,
from
a
meager
employed women who were unpaid
0.1%
ofofworkers
the
inin35%
2000
to
an
0.1%
thepopulation
population
2000in
to2005/06
anestiestifamily
rose from
99
mated
7%
in
2010.
By
2060,
coverage
mated
7%
in
2010.
By
2060,
coverage
isis
to 43% in 2010/11; the figure for men
projected
torise
rise
dramatically
to 99% of
projected
dramatically
dropped to
from
17%
to 12%. to 99% of
theAfrican
Africanpopulation.
population.1010
the
-tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
tion
At the same time, the number of women
in the public sector increased from 54,000
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
to 73,600, while the number of men
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
remained fairly constant at 129,000 (Table
forexample,
example,can
canexpand
expandservice
servicedelivery
delivery
for
6). As a result, the female share of public
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
sector workers rose from 30% to 36%.
services
through
error
reduction,
diagservices through error reduction, diagNonetheless, the estimated number
of
11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
unpaid family workers increased from 1.3
alsoincrease
increasethe
thetransparency
transparencyof
ofmedical
medical
also
to 1.4 million because of growing numbers
procurementand
anddistribution
distributionoperations.
operations.
procurement
of women among the unpaid ranks7. The
female
share ofprocesses,
unpaid family
workers
streamlining
reducing
waitbybystreamlining
processes, reducing
waitincreased
by
more
than
10
percentage
ing
times,
and
improving
the
accuracy
of
ing times, and improving the accuracy of
points to 81 % in 2010/11.
9 Ibid.
9 Ibid.
10 Ibid.
estimated number of people in non10The
Ibid.
11
11wage employment fell from 2.3 million information and communication technologies (ICT)
formation and communication technologies (ICT)
for
health. Examples
treatingbypatients,
con2005/06
to aboutinclude
1.9 million
2010/11.
for health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
opportunity
to improve
systems.1212
opportunity
health
systems.
4.4. Skill
status of
wage
employees
The changing
changing environmental land
The
land-scape threatens
threatens to increase poverty
and
scape
poverty
and
The 2010/11 EICV3 categorized responhealth problems
problems in Africa. Addressing
health
dents in wage employment
byAddressing
major octhe health
health impacts from climate change
the
change
cupation group: managerial/professional,
skilled labor8, and unskilled labor. A third
which the
the continent is ill-equipped
which
ill-equipped to
to
of Rwandans were in wage employment
handle.
Increased
climate
variability
and
handle.
Increased climate variability and
in 2010/11, the majority of whom (53%)
the
expected
temperature warming
the expected temperature
warming will
will
were unskilled.
human aspects,
aspects, mediating
mediating health
human
health outcomes
outcomes
Although the percentage of employed
across
the
continent,
through
across the continent, through both
both direct
direct
men who were unskilled was higher than
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
the percentage
of women
(59% versus
exacerbate
food and
and
water insecurity
exacerbate
food
water
insecurity and
and
37%), this
should
be and
interpretedofinmany
the
threaten
the livelihoods
livelihoods
threaten
the
and health
health of many
context
of
greater
male
representation
in
African populations.
populations. Droughts
African
Droughts are
are likely
likely
wage
employment.
The share
of menfrein
to
become
more prevalent,
prevalent,
both
to
become
more
both in
in frewage employment
nearly double
that
quency
and severity,
severity,was
reducing
farm
quency
and
reducing
farm yields
yields
of
women
(47%
compared
with
24%
in
and increasing hunger and starvation, parand increasing hunger and starvation, par2010/11).inASouthern
lower percentage
of employed
ticularly
Africa and
the Sahel
ticularly in Southern Africa and the Sahel
men than women had managerial/pro-
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
188 infectious
171 diseases includ17
regions. Various
regions. Various infectious diseases including malaria,
cholera,
diarrhea, dengue
445cholera,
656
-211
ing malaria,
diarrhea, dengue
fever, meningitis,
and224
schistosomiasis
112
-113are
fever, meningitis,
and 432
schistosomiasis-98
are
334
geographical
range of vector-borne110
dis332range of223
geographical
vector-borne diseases has been
linked
with
regional
warm88
115
-27
eases has been
linked with
regional warm244
107altered length
138 of
ing and the
consequent
ing and the consequent altered length of
seasons. Climate change could increase the
21 change18
3
seasons. Climate
could increase the
population49
at risk of malaria
in Africa by
18
population at
risk of malaria
in Africa31
by
262 170 million
187 by 2030 and
75
an additional
the
an additional 170 million by 2030 and the
global
population
at
risk
of
dengue
fever
global population
at risk
fever
283
396of dengue -113
13
by
2
billion
by
the
2080s.
13 Furthermore,
107
164
-57
by 2 billion by the 2080s. Furthermore,
176unplanned
231urbanization
-56
the
rapid
and
that
the rapid and unplanned urbanization that
happeningon
onthe
thecontinent
continentisisfraught
fraught
isis happening
-fessional (7% compared with 14%) or- cient
orjobs
contaminated
drinkingwith
water,
poor
skilled
(34% compared
49%).
cient
or
contaminated
drinking
water,
poor
sanitation
and
sewagesystems,
systems,
industrial
The higherand
percentage
of
managerial/prosanitation
sewage
industrial
waste,
and
stress
associated
withpoverty
poverty
fessional
and
skilled
jobs among
women
waste,
and
stress
associated
with
1414 Sustainable policies
and
unemployment.
and
Sustainable
policies
mayunemployment.
be a reflection of
the relatively
few
for
household
energy,
agricultural
producfor
household
energy,
agricultural
producwomen
in paid
employment,
rather
than
tivity,
nutrition,
transportation,
wateremand
tivity,
nutrition,
and
women
having transportation,
better
skills. In water
fact,
sanitation,
could
havehighly
large
andpositive
positive
sanitation,
could
have
aalarge
and
ployed women
were
concentrated
1515
impact
on
the
burden
of
diseases.
impact
on family
the burden
diseases.
in unpaid
work of
(49%
in 2010/11).
A relatively high percentage of youth in
are
likely
todecline.
decline.
Foreignaid
aidfrom
from
are
likely
to
Foreign
wage
employment,
particularly
women,
traditional
international
donorsto
develtraditional
international
donors
were skilled.
Among women
intodevelwage
oping
countries
is
declining
and
will
likely
oping
countries
is
declining
and
will
employment, 64% of youth (ages 15likely
to
play
a
reduced
role
in
African
developplay
a
reduced
role
in
African
develop34) were skilled, compared with 49%
ment
over
the
next
years.
InInthe
ment
over
thethan
nexta50
50
years.
thepast,
past,
overall.
More
third
of all
youth
in
African
healthcare
systems
have
been
heavAfrican
healthcare
systems
have
been
heavwage employment were women,
ily
reliant
ily
relianton
oninternational
internationaldonor
donorfunding
funding
whereas just 27% of all people in paid
from
development
from
developmentbanks,
banks,UN
UNagencies,
agencies,
employment were women. This suggests
and
organizations
such
asasthe
Global
and
organizations
such
the
Global
that the higher education of young
Fund.
In
light
of
the
uncertain
condition
Fund.
In light of the uncertain condition
women may be helping them to obtain
of
the
global
of the globaleconomy,
economy,African
Africancountries
countries
wage employment.
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
South
and
private–public
partnerships.
South
andand
private–public
7
The EICV2
EICV3 asked all partnerships.
employed respondents their occupation category: (i) wage
domestic
ownership
systems
and
farm; (ii) wage
non-farm;of
(iv)health
independent
farmer;
domestic
ownership
of
health
systems
and
the
involvement
of
new
international
(iv)
in
dependent
non-farmer;
(vii)
unpaid
worker.
the involvement of new internationalaid
aid
For this study, unpaid family workers could be
players.
players.
farm or non-farm.
Skilled labour includes office clerks and people
involved
in commerce
sales; unskilled
labour
13
AfDB,
A Strategic and
Framework
for Improving
13 AfDB, A Strategic Framework for Improving
Health
in Africa
(2012);
Fact Sheet
No. 266,
includes
artisans,
and WHO
agricultural
and fisheries
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct.
2012.
workers.
Oct.
2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
8
21
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
AfDB
AfDB
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
employment rate among youth with higher
rapid
growth
boosted
young
population
will be
be critical
critical in
in order
order
rapideconomic
economic
growth has
has distribution
boosted the
theof paid
young
population
Figure
7. Occupational
workers
aged 15 will
to 64,
by
gender,
amount
of
resources
allocated
to
health
infrato
harness
the
potential
of
the
youth
bulge
amount of resources
allocated
to health infrato harness the potential of the youth bulge
Rwanda,
2010/2011
structure
and
so-called ‘demographic
‘demographicdivdivstructureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
though,
Africa
has
an
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
ance
aging
In 2010,
2010, people
people aged
aged 60
60
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
population,
this is
is expected
expected to
to rise
rise to
to
-population, but
but this
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
cient, remains high, and in 2010, six of the
(Figure 1). Some
10
countries, such as Liberia and Nigeria,
Nigeria, are
are
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
33
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
Sub-Saharan Africa. While poverty has
population size
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
in less
less than
than 20
20years.
years.8 8
in
education (about 30%) is testament to this
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
fact.
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
-ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
education.
reflect high demand for and scarcity of
highly skilled workers. In 2010/11, just
Ibid.of individuals (1.6% of women and
882.3%
Ibid.
3.1%
men)
had
postsecondary
(26%in
orsize
women
and 17% of men) had no
Figure 1. Africa’s population
population will
will double
double
in
sizeby
by2050
2050
education; the percentage is down from
26% in 2005/06 (Table 7). Another two-
Population size in 2010
2010
thirds had primary education, and the
primary
education
were
employed,
remaining
13%
compared with 55% and 65% of people
postsecondary
with
secondary
and
had
secondary
education.
or
Between
postsecondary
2005/06 and 2010/11, the percentage of
education, respectively. As noted earlier,
employed women and men with at least
those with higher education tend to stay
secondary education increased from 27%
in school longer and to engage in a more
to 32% in urban areas and from 6% to
selective job search. The very low
10% in rural areas.
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
of
In 2010/11, 22% of employed Rwandans
Source: Authors’ calculations from EICV3, 2011 dataset
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulations
bearing
disproportionate
burden.
4.5. bearing
Education
and
ulations
aadisproportionate
burden.
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Over
employment
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
55
continue
around
5-6%
perhigh
annum.
continue
atataround
per
annum.
Employment
rates5-6%
were
among
extent
which
this
translates
into
better
extent
totowhich
translates
better
Rwandans
withthis
little
or no into
education
health
outcomes
though
contingent
on
health
though
isis contingent
(Table outcomes
7).
In 2010/11,
more
than 96% on
of
a
number
of
factors,
including
not
only
the
athose
number
of factors,
including
onlywith
the
with
no education
andnot
85%
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
Nonetheless,
employment
rates will
among
youth
bulgeand
and
populationaging
aging
exert
youth
bulge
population
will exert
individuals
with
postsecondary
education
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highwere higher
than
those among
people
lighting
theneed
need
address
familyplanning
planning
lighting
the
totoaddress
family
with
only
secondary
education.
This
may
services,maternal
maternaland
andchild
childhealthcare,
healthcare,
and
services,
and
Source: AfDB (2011a).
Source: AfDB (2011a).
22
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table 7. Employment rates and distribution of employed, by educational attainment, gender and
rural-urban
location,
regions.
Various
infectious diseases includregions.
Various
infectious diseases includpopulation aged 15 to 64, Rwanda, 2005/06 and 2010/11
ing malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis,
and schistosomiasis
are
Percentage
distribution
Employment-to-population ratio
Educational attainment, gender,
rural-urban location
2011
2005
Change
(%)
(% points)
Total employment
81.6
82.4
-0.8
National
None
2.8
95.9
93.1
Primary
84.9
84.1
0.8
Secondary
54.9
55.7
-0.8
Postsecondary
66.4
65.3
1.1
Female
None
96.7
94.9
1.8
Primary
86.1
84.8
1.3
Secondary
51.6
54.5
-2.9
Postsecondary
62.7
61
1.7
Male
None
94.3
90.2
4.1
Primary
83.5
83.4
0.1
Secondary
Postsecondary
technology
(ICT)
technology
(ICT)revolution
revolutionin
in Africa
Africa
Youth
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
None
Primary
health
sector.
healthSecondary
sector.Internet
Internetbroadband
broadband penepenetration
has
trationPostsecondary
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
0.1%
the
0.1%ofof
thepopulation
populationinin2000
2000to
toan
anestiestiFemale
None
mated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage isis
mated
Primary
projected
risedramatically
dramaticallyto
to 99%
99% of
of
projected
totorise
Secondary
theAfrican
Africanpopulation.
population.1010
the
-Postsecondary
tionprovides
provides
the opportunity to overcome
tion
Male the opportunity to overcome
None
humanPrimary
resources,and
andininthe
theprovision
provisionof
of
human
resources,
Secondary
high-quality
healthcareservices.
services.E-Health,
E-Health,
high-quality
healthcare
Postsecondary
forexample,
example,
canexpand
expandservice
servicedelivery
delivery
for
can
Urban
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
None
services
through
error
reduction,
diagservicesPrimary
through error reduction, diag11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
Secondary
also
increase
the
transparency
of
medical
Postsecondary
also increase
the transparency of medical
Female
procurement
anddistribution
distributionoperations.
operations.
procurement and
None
Primary
streamliningprocesses,
processes,reducing
reducingwaitwaitbybystreamlining
Secondary
ing
times,
and
improving
the
accuracy
of
ing times,
and improving the accuracy of
Postsecondary
Male
9 Ibid.None
9 Ibid.
10 Ibid.
10 Ibid.Primary
11
Secondary
11
formation and communication technologies (ICT)
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
data.
countries
58.1 At
56.8 80% of African
1.3countries
data.
At present,
present,
69 to
67.6 telemedicine1.4
claim
m-health
claim
to be
be using
or m-health
(also
known
as
mobile
health),
although
(also known
although
90.6
87.2
3.4
the
still in
in
the majority
majority of these projects are still
67.2
71.7
-4.5
their
infancy.
In
this
respect,
scaling
up
their
infancy.
scaling up
28.4
24.2
4.2
29.3
25.7
3.6
opportunity
systems.1212
opportunity to improve health systems.
89.2
88.2
69.1 changing
72.8
The
changing
The
1
-3.7
environmental
land
land-26.4
23.9
2.5
scape threatens
threatens to increase poverty
scape
poverty and
and
30.8
24.7
6.1
health problems
problems in Africa. Addressing
health
Addressing
the
health
climate
the
health
impacts
from
change
92.2
86
6.2 change
65.1
70.4
-5.3
30.6 the
24.3
6.3
which
the continent
is ill-equipped
to
which
ill-equipped
to
28.1
26.7 climate variability
1.4
handle.
Increased
and
handle. Increased climate variability and
the expected
expected temperature
temperature warming
will
the
warming
will
90.6
83.4
7.2
83.8
78.4
5.4
human
aspects,
mediating health
human
mediating
health
outcomes
58.3 aspects,
58.3
0 outcomes
across
the
continent,
through
both
70.8 the continent,
67.7
across
through3.1
both direct
direct
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
89.3
81.9 and water insecurity
7.4
exacerbate
food
exacerbate
food
and water insecurity and
and
81.8
5.2
threaten
the 76.6
livelihoods and
of many
threaten
the
livelihoods
and health
health
52.6
53.1
-0.5 of many
African
populations.
Droughts
are
likely
African
populations.
Droughts
67
63.9
3.1are likely
to become
become more
more prevalent,
prevalent, both
to
both in
in frefrequency
and
severity,
reducing
farm
yields
92.9
85.6
7.3
quency and severity, reducing farm yields
86.1increasing
80.3
5.8
and
hunger and starvation,
parand increasing hunger and starvation, par64
64.2
-0.2the Sahel
ticularly
in Southern
Africa and
ticularly in Southern Africa and the Sahel
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and
alteredChange
length of
2011the consequent
2005
seasons. Climate change could increase the
seasons. Climate change could increase the
points)by
population at risk of malaria(%
in Africa
population(%)
at risk of malaria in Africa by
an additional170
170million
millionby
by2030
2030and
and the
an additional
100
100
0 the
global
population
at
risk
of
dengue
fever
global population at risk of dengue fever
13
Furthermore,
by 2221.9
billionby
bythe
the2080s.
2080s.13 Furthermore,
26.5
-4.6
by
billion
65.2 and unplanned
64.1
1.1 that
the
rapid
urbanization
the rapid and unplanned urbanization that
10.7
8.7
2
happeningon
onthe
the continent isfraught
fraught
isis happening
2.3
0.8 continent is 1.5
-25.6
30.5
-4.9
-cient
or
contaminated
drinking
water,
poor
61.6 drinking water,
2 poor
cient63.6
or contaminated
9.2
7.5
1.7
sanitation
and
sewage
systems,
industrial
sanitation and sewage systems, industrial
1.6and stress
0.5
waste,
associatedwith
with1.2
poverty
waste,
and stress associated
poverty
14
14 Sustainable policies
and
unemployment.
and unemployment.
policies
17.4
21.6 Sustainable-4.2
forhousehold
household
energy,
agricultural
producfor
energy,
agricultural
produc67.1
67.2
-0.1
tivity,
nutrition,
transportation,
water
and
2.4 and
tivity,12.5
nutrition, 10.1
transportation, water
3.1 could
sanitation,
could1.2
haveaalarge
largeand
and1.9
positive
sanitation,
have
positive
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
D e v e l o p m e n t
D e v e l o p m e n t
16.8
-6.3
76.8
77.5
-0.7
11.7
5.5
6.2
are likely
likely
todecline.
decline.
Foreignaid
aid
from
are
to
Foreign
1
0.2
0.8from
traditionalinternational
internationaldonors
donorstotodeveldeveltraditional
10.3
-6.6
oping
countries
isisdeclining
oping
countries16.8
decliningand
andwill
willlikely
likely
78.1
78.1
0
play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelop10.8
4.9
5.9
ment
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
0.9
0.2
0.7
African
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavily
on
international
donor
funding
ilyreliant
reliant
on
international
donor
funding
10.8
16.8
-6.1
from
development
75.4
76.8banks,
-1.4
from
development
banks,UN
UNagencies,
agencies,
6.2 such
and
organizations
Global
and12.7
organizations
such asasthe
the6.5
Global
1.1
0.2
0.9
Fund.
In
light
of
the
uncertain
condition
Fund. In light of the uncertain condition
of
global
African
of the
the
globaleconomy,
economy,
Africancountries
countries
11.8
15.6
-3.8
will
need
to
reevaluate
their
relationships
will56.2
need to reevaluate
their
relationships
58.5
-2.3
with
international
aid
with22.6
international
aidagencies
agenciesand
andbilateral
21.6
1bilateral
partners
South–
9.4 and
4.2 look
5.2
partners
andpossibly
possibly
lookmore
moretoto
South–
South
and
private–public
partnerships.
South and private–public partnerships.
14.5
18.3
57.5
58.2
9
12.8
-3.8
-0.8
domestic
ownership ofofhealth
and
domestic
healthsystems
systems
20.3 ownership
20.4
-0.1 and
the
involvement
of
new
international
aid
the involvement
of new international
7.8
3.1
4.7 aid
players.
players.
-3.8
54.9
58.8
-3.9
13 AfDB, A Strategic Framework for Improving
22.9 Framework for2.1
13 25.1
AfDB, A Strategic
Improving
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
23
A f r i c a n
A f r i c a n
10.5
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
Postsecondary
73.9
70.1
rapid
young
will be
be 3.8
critical in
in order
order
rapideconomic
economic growth
growth has
has boosted
boosted the
the
young population
population will
critical
Rural
amount
of
resources
allocated
to
health
infrato
harness
the
potential
of
the
youth
bulge
amount
the potential of the
Noneof resources allocated to health infra- 96.3to harness
94.3
2 youth bulge
structure
and
so-called ‘demographic
‘demographic
divstructure
andto
tosurvival-enhancing
survival-enhancing social
social 85and
and capture
capture
the so-called
divPrimary
85.2the
-0.2
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
though,
Africa
has
an
Secondary
53.5
54.2
-0.7
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
Postsecondary
60.3
52.6
7.7
ance
aging
In 2010,
2010, people
people aged
aged 60
60
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
aging population.
population. In
Female
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
None
97.4
96.4
1
population,
but
this is
is expected
expected to
to rise
rise to
to
-population,
but this
Primary
86.7
86.3
0.4
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
cient,
remains high, and in 2010, six of the 51.2
(Figure 1). Some
Secondary
55.6
-4.4
10
such as Liberia37.6
Nigeria, are
are
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were 55.4countries,
and Nigeria,
Postsecondary
17.8
33
Male
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
Sub-Saharan Africa. While poverty has
population size
None by
90.8
3.7
declined
declined
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this 94.5
Primary
83.1
83.9
-0.8
Secondary
55.7
52.9
2.8
5.4
5.6
in11less
less than
than 20
20years.
years.8 8
in
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
23.6
28.5
-4.9
the fastest,
fastest,tripling
tripling
theirpopulations
populations
over
the
over
66.7
65.2 their
1.6
8.6
6.2
2.4
1 bulge
0.1 population
0.9 will
youth
bulgeand
and
populationaging
aging
willexert
exert
youth
increasingpressure
pressureon
onhealth
healthsystems,
systems,highhighincreasing
27.4
32.6
-5.1
lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
lighting
64.6
62.2
2.4
services,
maternal
and
child
healthcare,
and
services,
maternal
and
7.4
5.3 and child healthcare,
2.1
0.6
Ibid.
8819Ibid.
69.4
10.1
1.5
0
0.6
23.4
-4.4
68.9
0.5
7.5
2.6
meet
the
meet
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by 63.2
Postsecondary
58.4
4.8
0.3
-Source:(excluding
Authors’ calculations
fromstill
EICV2,
2005 and EICV3, 2011 datasets
ulation
North
subsists
ulation
(excluding
NorthAfrica)
Africa)
still
subsists
44
on
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted). As
As
Aimproving
relatively health
low
percentage
employed
improving
health
outcomes,of
with
women,
toto
outcomes,
with
women,
rural
dwellersand
andother
other
marginalized
popno marginalized
education.
Noneyouth—10%—had
rural
dwellers
populations
bearing
disproportionate
burden.
theless,bearing
about 75%
had only primary
eduulations
aadisproportionate
burden.
Over
theanext
next
50years,
years,
projected
that
Over
the
50
isis projected
that
cation,
situation
thatititmay
affect their
the
continent’s
economic
growth
rate will
will
the
continent’s
economic
growth
rate
chances
of securing
wage
employment,
55
continue
5-6%
performal
annum.
continue
atataround
5-6%
per
annum.
particularly
inaround
the public
and
sectors.
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
health
outcomes
though isis contingent
contingent
on
health
though
4.6. outcomes
Unemployment
and on
a
number
of
factors,
including
not
only
the
a number of
factors, including not only the
underemployment
level
of
budgetary
allocations to
to the
the sector
sector
level of budgetary allocations
4.6.1.
Unemployment
be
deployed torespond
respond
to emerging
emerging
chalbe
to
In deployed
this study,tothe
unemployment
rate ischaldelenges.
Equitable
access
and
treatment
for
lenges.
Equitable
access
and
treatment
for
fined as the percentage of the labour force
thepoorest
poorest segmentsof
ofsociety
societyisisone
onecritical
critical
the
aged 15 tosegments
64 who were
not employed
in
challenge.
challenge.
the reference period (12 months in the
EICVs) and
who were
looking
for work.
size
in 2010
Population
2010
unemployment fell from 5.7% to 4.2%.
Unemployment is a challenge in urban
Most of the reduction was attributable to
areas, where, in 2010/11, 14% of women
job creation in urban areas, especially jobs
and 6% of men classified as unemployed;
for men. In urban areas, the male
Kigali had the highest rate—almost 12%
unemployment rate decreased by about a
(Table 8).
third, compared with a marginal increase of
0.5 percentage points in the female rate.
Youth unemployment rates were similar for
men in urban and rural areas, but slightly
The largest decline in unemployment was
higher for women in urban areas. People
among
with postsecondary education and those in
education, notably men, whose rate
the highest and lowest expenditure quintiles
dropped from 17% to 4%. This suggests
had relatively high unemployment rates.
that most of the new jobs went to men, and
people
with
postsecondary
it is partly linked to the nature of the jobs
Between 2005/06 and 2010/11, overall
created—physical jobs that favoured men.
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
1.3
Source: AfDB (2011a).
Source: AfDB (2011a).
24
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table 8. Unemployment rates, by gender, rural-urban location, youth status, educational attainment,
region
and infectious
expenditurediseases
quintile,
regions.
Various
includregions.
Various
infectious
diseases
includpopulation aged 15 to 64, Rwanda, 2005/06 and 2010/11
ing malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
Group
Unemploymentfever,
rate by
group (%)
meningitis,
and schistosomiasis are
2010/2011
2005
Change
geographical
range of vector-borne
dis4.2geographical
5.7 range of vector-borne
-1.5
Total
diseases
has
been
linked
with
regional
warmFemale
3.9eases has4.3
been linked with-0.4
regional warming
and
the
consequent-2.8
altered length of
Male
4.5ing and the
7.3 consequent
altered length of
seasons.
Climate change-5.8
could increase the
10.0seasons.
15.8
Urban
Climate change could
increase the
population
at risk of malaria
Africa by
Female
14.1population
13.6at
0.5 ininAfrica
risk of malaria
by
anadditional
additional
170million
million
by
2030
and
the
Male
5.8an
18.0 170
-12.2
by 2030 and the
at
risk
of
dengue
fever
3.1global population
3.6
-0.5
Rural
global population at risk of dengue fever
13
Female
2.2by 2 billion
2.5 by the 2080s.
13 Furthermore,
by 2 billion
by the 2080s.-0.3
Furthermore,
Male
4.3the rapid5.1
-0.8
andunplanned
unplannedurbanization
urbanizationthat
that
the rapid and
4.6is happening
5.5 on the continent
-0.9
Youth
fraught
is happening on the continent isisfraught
Female
5.3
4.6
0.7
-Male
3.9
6.4
-2.5
-11.7 cient or15.3
-3.6 water, poor
Urban
contaminated
drinking
cient or contaminated drinking water, poor
Female
17.7 sanitation
16.9and sewage systems,
0.8
industrial
sanitation and
sewage systems, industrial
Male
5.7
13.8
-8.1
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
3.1
3.1
0.0
Rural
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
Female
2.7
2.4
0.3
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
Male
3.5
3.9
-0.4
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
data. At present,
countries
tivity, nutrition, transportation, water and
Education
technology
claim
m-health sanitation,
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine or m-health
None
4.3
8.4
-4.1
1515
isisrapidly
increasing
connectivity
across
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
rapidly increasing connectivity across Primary
(also known
although 3.5impact on
the burden of -1.0
diseases.
4.5
the
majority
of these projects are still
still in
in
the
majority
Secondary
7.6
13.2
-5.6
health
their
scaling up
up 4.9
healthsector.
sector.Internet
Internetbroadband
broadband penepene- Postsecondary
their infancy.
infancy. In this respect, scaling
16.5
-11.6
tration
from
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
trationhas
hasrisen
risenrapidly,
rapidly,
from aa meager
meager
are
Female
12
12
0.1%
opportunity
systems. 3.3traditional
traditional
international-0.2
donorstotodeveldevel0.1%ofofthe
thepopulation
populationinin2000
2000to
toan
anestiesti- None
opportunity to improve health systems.
donors
3.5international
mated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage isis Primary
oping
countries
is
declining
and
will
likely
mated
oping
countries
is
declining
and
will
likely
3.1
3.2
-0.1
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of Secondary
The changing
changing environmental land
projected
The
land--10.4play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelop13.2
-2.8
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
the
next
50
years.
In
the
the
-- Postsecondary
scape
poverty and
and 6.9ment
ment over
over
the
next
50
years.
In
thepast,
past,
15.3
-8.4
tionprovides
providesthe
theopportunity
opportunity
toovercome
overcome
health problems
problems in Africa. Addressing
African
tion
to
health
Addressing
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavMale
the health
health impacts from climate change
on
donor
None
8.2
-2.3
the
change 5.9ily
ilyreliant
reliant
oninternational
international
donorfunding
funding
humanresources,
resources,and
andininthe
theprovision
provisionof
of Primary
banks,
UN
4.1from
5.9
-1.8
human
from development
development
banks,
UNagencies,
agencies,
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health, Secondary
which the
the continent is ill-equipped
such
asasthe
13.4
-8.2
high-quality
which
ill-equipped to
to 5.2and
and organizations
organizations
such
theGlobal
Global
for
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
Postsecondary
3.8
16.9
-13.1
for example, can expand service delivery
handle. Increased climate variability and
Fund. In light of the uncertain condition
and
ensure
greater
accountability
in
health
the
expected
temperature
warming
will
of
Region
and ensure greater accountability in health
the expected temperature warming will
of the
the global
globaleconomy,
economy,African
Africancountries
countries
Kigali
City
12.3
16.1
-3.8
services
through
error
reduction,
diagwill
need
to
reevaluate
their
services through error reduction, diagwill need to reevaluate theirrelationships
relationships
Regionmediating
5.7
-1.8 and
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can Southern
human aspects,
aspects,
mediating health
aid
nostic
human
health outcomes
outcomes 3.9with
withinternational
international
aidagencies
agencies
andbilateral
bilateral
Western
Region
3.4partners 4.7
-1.3
also
increase
the
transparency
of
medical
across
the
continent,
through
both
direct
and
possibly
look
more
also increase the transparency of medical
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
Northern
Region
2.9South and
3.1private–public
-0.2partnerships.
procurement
and
distribution
operations.
and
indirect
channels.
Climate
change
will
procurement and distribution operations.
and indirect channels. Climate change will
South and private–public partnerships.
Eastern
Region
2.8
3.8
-1.0
exacerbate
food and
and water
water insecurity
exacerbate
food
insecurity and
and
Poverty Status
streamliningprocesses,
processes,reducing
reducingwaitwaitthreaten the
the livelihoods
livelihoods and
ownership
systems
bybystreamlining
threaten
and health
health of
of many
many 5.0 domestic
domestic
ownershipofofhealth
health
systemsand
and
Poorest
6.5
-1.5
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
of
new
international
aid
ing times, and improving the accuracy of 2nd
African populations. Droughts are likely 3.3 the involvement
of
new
international
aid
5.2
-1.9
to
become
more
prevalent,
both
in
freplayers.
to become more prevalent, both in fre- 2.8 players.3.3
3rd
-0.5
quency
and
severity,
reducing
farm
yields
9 Ibid.
quency and severity, reducing farm yields 2.8
4th
4.6
-1.8
9 Ibid.
10 Ibid.
and increasing hunger and starvation, par10 Ibid.
-1.6 for Improving
and increasing hunger and starvation, par- 6.6 13 AfDB,8.2
11
- Richest
A Strategic Framework
11
13 AfDB, A Strategic Framework for Improving
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health
in
Africa
(2012);
WHO
Fact Sheet No. 266,
ticularly
Southern
and the Sahel
formation
communication
technologies
Health in Africa (2012); WHO Fact Sheet No. 266,
Source:and
Authors’
calculations
from (ICT)
EICV2, 2005
andin
EICV3,
2011Africa
datasets
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
25
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
unemployment rates decline
with age, but
people with lower educational attainment,
young
will be
be critical
critical in
in order
order in
in
less than
than 20
20years.
years.8 8
young population
population will
less
rise sharply after age 50 (Table 9). Between
especially women, to be employed in
African
subregionsare
areexpected
expectedtotogrow
grow
to
potential of
of the
the youth
youth bulge
bulge African
subregions
to harness
harness the
the potential
2005/06
and
2010/11,
the
rates
declined
subsistence
agriculture
or
unpaid
family
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
and capture
capture the
the so-called
the
substantially among men while young
work.’ Concurrently though, Africa has an
idend.
idend.’ Concurrently though, Africa has an
women
registered
increases
urban
aging
In 2010,
2010, people
people aged
aged 60
60 youth
youth
bulge
andpopulation
population
aginginwill
will
exert
aging population.
population. In
bulge
and
aging
exert
unemployment
rates.
The
high
unemployment
in
urban
areas
secondary education was especially high.
or
older
accounted
for
just
6%
of
Africa’s
increasing
pressure
on
health
systems,
highor older accounted for just 6% of Africa’s
increasing pressure on health systems, highmerits more detailed
analysis.to Urban
These results may reflect the tendency forpopulation,
this is
is expected
expected
rise to
to lighting
lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
population, but
but this
to rise
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
50
years
(Figure
1).
Some
services,
maternal
and
child
healthcare,
and
cient, remains high, and in 2010, six of the
(Figure 1). Some
services, maternal and child healthcare, and
Table
9.
Urban
unemployment,
by
gender,
age
group
and
educational
attainment,
population
aged
15
to
64,
10
countries, such as Liberia and Nigeria,
Nigeria, are
are
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
Rwanda, 2005/06
and 2010/11
33
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
Sub-Saharan Africa. While poverty has
population size
Ibid.
88 Ibid.
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Females
Males
Unemployment rates were highest among
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
people with secondary education—8% in
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infra2010/11, compared
with 5% among
structure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
people
with
post-secondary
education
services.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of govern(Table 8).
The rate among
women with
ance
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
Education Level
2011
2005
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
Total
28.6 -ulation
North
Africa)
still
subsists
ulation(excluding
(excluding
North
Africa)
still
subsists
None
31.7
44
on
or
on$1.25
$1.25
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).
As
Primary
15.1As
Secondary
46.5
6.9
bedeployed
deployed
torespond
respond to
to emerging
emerging10.3
chalSecondary
be
to
challenges.
Equitable
access
and
treatment
for
Postsecondary
4.5
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
Total
11.2
challenge.
None
Primary
2005
% Change
10.8
12.5
27.6
- 15.1
14.4
9.0
17.3
13.2
2 9.9
- 16.7
Figure 1.6.1
population7.2
will double
double23ininsize
sizeby
by2050
2050
Africa’s population
will
- 15.8
…
5.7
Population…size in 2010
2010
19.1
36.6
- 17.5
…
…
…
21 - 30 years
17.8
2.9
6.5
16.1
- 9.6
11.3
3.2
0
9.9
- 9.9
13.2
1.2
2.6
12.1
- 9.5
28 .9
4.0
12.6
23.2
- 10.6
11.6
5.3
9.2
27.7
- 18.5
31 - 50 years
9.6
- 2.3
4.2
15.9
- 11.7
9.6
- 3.7
10.6
35.6
- 25.0
7.5
- 0.6
4.3
12.6
- 8.3
12.4
- 2.1
2.7
12.9
- 10.2
1 8.8
- 14.3
2.5
11.2
- 8.7
- 18.6
51 - 64 years
21.5
- 10.3
10.3
28.9
13.3
16.1
- 2.8
10.1
10.6
- 0.5
7.7
24.3
Predicted- 16.6
population
7.1
Predicted
population size
size in
in 2050
2050
34.4
- 27.3
Secondary
16.4
severehealth
health
challenge.African
Africandemogrademograsevere
challenge.
Postsecondary
2011
15 - 20 years
17.8
40.8
improving
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
health
Postsecondary
…
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulationsTotal
bearingaadisproportionate
disproportionateburden.
burden.
ulations
bearing
20.7
Overthe
the
next50
50years,
years, itit isis projected
projected
that
Over
next
that
None
14.5
thecontinent’s
continent’s
economic growth
growth rate
rate
will
the
will
Primary economic
14.4
55
continue
around5-6%
5-6% per
per annum.
annum.
Secondary
32.9
continue
atataround
extentto
to
whichthis
this translates
translates into
into16.9
better
Postsecondary
extent
which
better
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
a
number
of
factors,
including
not
only
the
Total
7.3the
a number
of factors, including not only
level
of
budgetary
allocations
to
the
sector
None
5.9
level of budgetary allocations to the sector
Primary
% Change
0.0
26.4
- 10.0
15.9
40.4
- 24.5
79.2
- 79.2
14.1
11.7
2.4
people
living
inAfrica
Africa
today, and
and
the 2005 and EICV3, 2011 datasets
Source:
Authors’
calculations
from
people
living
in
today,
itit isisEICV2,
the
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by 2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
4.6.2. 2020,
up from 46% in 2005/06 (Table 10). But almore,
theUnderemployment
majority of this population will
more,
the
majority
of
this
population
will
Although
ratesAfrica
in Rwanda
though more people may have been working
belong
to unemployment
the youth cohort.
is the
belong
to the low,
youth
cohort. Africa isrates
the
below their potential, Rwanda’s underemare
relatively
underemployment
world’s youngest region and is expected
world’s youngest region and is expected
arehave
high.the
The
underemployment
is the
ployment rates are similar to those in other
to
largest
workforce in rate
the world
to have the
largest workforce in the world
7
percentage
of
people
aged
15
to
64
who
African countries. For instance, the World
by 2040. Ensuring the good health of this
by 2040.7 Ensuring the good health of this
condary education (7 percentage points).
And while the rate rose by 19 percentage
points in the Northern region, it declined
about 16 percentage points in the Southern
region. As expected, employed people had
are seeking additional or new employment.
Bank (2009) reported underemployment
substantially higher underemployment rates
is important
low-income
3This
AfDB,
“A Strategicin Framework
for countries
Improving
3Health
AfDB,
“A Strategic
Framework for Improving
ina Africa”
(2012).
where
majority
of
workers
may
be
in nonHealth
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45wage
WHO,
Atlas
Statistics
(2011b).
employment.
AfDB,
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Half (48%)
of 15- to
64-year-olds reported
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 that
AfDB,
Africa
in
50
Years’
Time
(2011a).
they sought additional
work
in 2010/11,
rates as high as 60% in countries such as
than did the general population in 2010/11:
Mauritania.
58% versus 48%. Underemployment rose
an average of 4 percentage points among
Source: AfDB (2011a).
Source: AfDB (2011a).
Trends in underemployment varied consi-
all classes of workers except self-employed
derably for different groups. The increase
farmers, among whom the rate increased
was greatest among people with postse-
by less than 2 percentage points.
26
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
69.1
60.9
66.4
59.1
61.8
70.8
64.2
75.1
60.1
61.4
59.9
56.3
60.4
56.7
52.4
70.4
56.8
59.7
65.7
59.7
63.8
59.3
63.5
57.9
55.7
70.6
61.9
69.1
62.9
60.1
68.6
57.3
59.6
57.3
61.5
68.0
61.3
63.9
56.7
59.8
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditionalinternational
internationaldonors
donorstotodeveldeveltraditional
oping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelopment
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
African
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavily
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
from
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
and
and organizations
organizations such
such asasthe
theGlobal
Global
Fund.
In
light
of
the
uncertain
condition
Fund. In light of the uncertain condition
of
of the
the global
globaleconomy,
economy,African
Africancountries
countries
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
South
and
private–public
partnerships.
South and private–public partnerships.
D e v e l o p m e n t
D e v e l o p m e n t
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011 datasets
domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
the
involvement
of
new
international
the involvement of new internationalaid
aid
players.
players.
13 AfDB, A Strategic Framework for Improving
13 AfDB, A Strategic Framework for Improving
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
27
A f r i c a n
A f r i c a n
Source: Authors’ calculations from EICV2, 2005 and EICV3, 2011 datasets
53.8
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and the consequent altered length of
seasons. Climate change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
global population
populationatatrisk
riskofofdengue
denguefever
fever
global
13
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.13 Furthermore,
by
the
rapid
and
unplanned
urbanization
that
the rapid and unplanned urbanization that
happeningon
onthe
thecontinent
continentisisfraught
fraught
isis happening
--cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
tivity,
nutrition,
transportation,
water
and
tivity, nutrition, transportation, water and
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
57.5
54.1
Total
Occupational activity
Wage farm
65.1
60.9
Wage non-farm
59.7
55.7
Independent farmer
55.0
53.4
Independent non-farmer
58.5
54.4
Unpaid family worker
53.9
50.6
Note: Underemployment rate is share of people seeking additional or new employment.
human aspects,
aspects, mediating
mediating health
human
health outcomes
outcomes
across
the
continent,
through
across the continent, through both
both direct
direct
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
threaten the
the livelihoods
livelihoods and
threaten
and health
health of
of many
many
African
populations.
Droughts
are
African populations. Droughts are likely
likely
to become
become more
more prevalent,
prevalent, both
to
both in
in frefrequency
and
severity,
reducing
farm
yields
quency and severity, reducing farm yields
and increasing hunger and starvation, parand increasing hunger and starvation, particularly in Southern Africa and the Sahel
ticularly in Southern Africa and the Sahel
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
regions. Various infectious diseases includregions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
55.5
52.3
47.0
51.5
46.4
61.9
48.9
48.1
47.4
54.2
57.9
46.3
41.8
53.7
41.9
33.2
38.4
42.3
58.4
45.7
36.1
41.1
46.7
42.8
53.7
55.0
43.4
45.5
38.8
53.4
52.4
40.9
45.8
48.4
34.6
34.2
which the
the continent is ill-equipped
which
ill-equipped to
to
handle.
Increased
climate
variability
and
handle. Increased climate variability and
the expected
expected temperature
temperature warming
the
warming will
will
Total
Urban
Rural
Educational attainment
None
Primary
Secondary
Postsecondary
Region
Kigali City
Southern region
Western region
Northern region
Eastern region
9 Ibid.
9 Ibid.
10 Ibid.
10 Ibid.
11
11
formation and communication technologies (ICT)
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12
12
AfDB
AfDB
62.8
55.6
44.9
60.6
52.7
63.6
65.7
63.4
59.6
61.4
56.2
43.3
62.7
48.9
37.1
43.2
47.2
46.6
52.2
56.6
44.1
45.4
40.7
54.3
55.2
41.9
42.7
59.3
47.1
36.6
41.8
46.3
43.5
53.3
55.8
43.0
42.9
64.2
50.0
39.5
44.2
Employed
60.4
58.1
53.7
25.2
39.4
54.3
48.7
29.6
35.4
60.8
54.5
26.3
42.0
53.6
52.3
34.0
35.3
42.2
56.4
45.4
36.3
40.6
56.6
51.7
27.8
38.1
64.5
55.4
27.4
44.2
streamliningprocesses,
processes,reducing
reducingwaitwaitbybystreamlining
ing
times,
and
improving
the
accuracy
of
ing times, and improving the accuracy of
49.3
53.2
31.4
41.0
2010/11
48.2
46.3
48.5
Total
2005
45.9
49.0
45.2
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
forexample,
example,can
canexpand
expandservice
servicedelivery
delivery
for
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
services
through
error
reduction,
diagservices through error reduction, diag11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
also
increase
the
transparency
of
medical
also increase the transparency of medical
procurementand
anddistribution
distributionoperations.
operations.
procurement
Rural-urban location, educational attainment,
region, occupational activity
57.4
55.2
32.6
43.5
The changing
changing environmental land
The
land-scape threatens
threatens to increase poverty
scape
poverty and
and
health problems
problems in Africa. Addressing
health
Addressing
the health
health impacts from climate change
the
change
44.5
51.4
30.2
37.3
2005
42.6
47.3
41.7
opportunity
systems.
opportunity to improve health systems.
2010/11
46.0
45.5
46.1
Population aged 15 to 64
Female
health
healthsector.
sector.Internet
Internetbroadband
broadband penepenetration
trationhas
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
0.1%
0.1%ofofthe
thepopulation
populationinin2000
2000to
toan
anestiestimated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage isis
mated
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
projected
theAfrican
Africanpopulation.
population.1010
the
-tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
tion
data.
countries
data. At
At present,
present, 80% of African countries
claim
m-health
claim to
to be
be using telemedicine or m-health
(also
known
as
mobile
health),
although
(also known
although
the
still in
in
the majority
majority of these projects are still
their
infancy.
In
this
respect,
scaling
up
their infancy.
scaling up
41.0
44.9
35.4
32.0
2010/11
50.7
47.2
51.4
Male
technology
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
52.5
46.2
31.6
31.1
2005
48.3
49.5
48.1
2010/11
49.2
46.1
49.8
2005
45.1
48.3
44.4
2005
49.6
51.0
49.4
2010/11
48.3
45.5
48.9
2005
45.1
48.3
44.4
2010/11
47.6
44.9
48.2
Male
Youth (population aged 15 to 34)
Female
Total
Table
rate, by labour
force status, gender, rural-urban location, educational attainment , region and occupational activity, population aged 15 to 64, Rwanda,
aged10.
15 Underemployment
to 64, Rwanda, 2005/06
and 2010/11
2005/06 and 2010/11
Table 10: Underemployment rate, by labour force status, gender, rural-urban location, educational attainment , region and occupational activity, population
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
In 2010/11, women’s underemployment
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
rate was lower than men’s: 46% versus
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infra51%. However,
between 2005/06 and
structure
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
2010/11,
women’s
rate rose
more
than 4
services.
In
spite
of
this,
issues
of
governservices. In spite of this, issues of governpercentage
points, compared
with an inance
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
crease of less than 1 percentage point
among men. Gender differences were also-
apparent
by high,
occupational
activity.
Rates
cient,
remains
and
in
2010,
six
of
the
cient, remains high, and in 2010, six of the
increased
among
women worldwide
who
were wage
10
most
countries
were
10
mostunequal
unequal
countries
worldwide
were
33
farm
workers
or
unpaid
family
workers,
inin
Sub-Saharan
Africa.
While
poverty
Sub-Saharan Africa. While poverty has
has
but
among
men
these
occupational
declined
by
over
past
declined
by9%
9%
overinthe
the
past 20
20 years,
years, this
this
effects and corresponding z-statistic in
young
will be
be critical
critical in
in order
order
young population
population will
brackets. The marginal effect is the
to
harness
the
potential
of
the
youth
bulge
to harness the potential of the youth bulge
average
change
in
the
probability
that
an
and
so-called ‘demographic
‘demographicdivdivand capture
capture the
the so-called
individual finds himself/herself
idend.
though, Africa
Africain
hasan
an
idend.’’ Concurrently
Concurrently though,
has
an
employment
category
as
a
result
of
a
unit
aging
In 2010,
2010, people
people aged
aged 60
60
aging population.
population. In
change
in
the independent
variables.
For
or
older
accounted
for
just
6%
of
Africa’s
or older accounted for just 6% of Africa’s
example, the coefficient
of 0.252
population,
this is
is expected
expected
to rise
risefor
to
population, but
but this
to
to
secondary
education
in
urban
13% over the next 50 years (Figure
(Figure 1).
1).areas
Some
Some
indicates such
that asthe
probability
of are
an
countries,
Nigeria,
are
Liberia
and Nigeria,
individual to
with
secondary
being
expected
double
their education
population
size
population size
likelihood of informal self-employment.
in less
less than
than 20
20years.
years.8 8
in
The presence of women aged 15 to 64 in
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
the
household
was
negatively
associated
the fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
the
with employment in agriculture and
positively
withaging
formal
and
youth
bulgeassociated
andpopulation
population
willexert
exert
youth
bulge
and
aging will
informal
self-employment
in
both
rural
and
increasing
pressure
on
health
systems,
highincreasing pressure on health systems, highurban areas.
suggests
the
lighting
theneed
needThis
address
familythat
planning
lighting
the
totoaddress
family
planning
presence
of
adult
women
to
take
care
of
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
services,
agricultural food production is necessary
before an individual can seek other
in formal employment was about 25%
Ibid.
88employment
Ibid.
classes, underemployment declined slightly.
higher than of an individual with no
household labour enables individuals,
However,
in thegoal
independent
farmer
class,
meet
the
of
poverty
by
meet
theMDG
MDG
goal
of halving
halving
poverty
by
underemployment among women fell 2-percentage
points,
but Africa)
rose
4 percentage
ulation
(excluding
North
still
ulation
(excluding
North
Africa)
stillsubsists
subsists
points
among
men.
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
education. On the other hand, the negative
especially men, to find more lucrative non-
coefficient of 0.112 for the female dummy
farm employment.
opportunities.
Female
variable indicates that the probability of
women engaging
formal population
employmentwill
is double
A number
of other
findings are noteworthy.
Figure 1.inAfrica’s
population
will
double
size
by2050
2050
ininsize
by
about 10% lower than that of men.
People
aged
15 tooutcomes,
34 had much
higher
improving
health
outcomes,
withwomen,
women,
toto
improving
health
with
rural
dwellersand
andother
other
marginalized
popunderemployment
rates
than did popthe
rural
dwellers
marginalized
ulations
bearing
disproportionate
burden.
population
aged
15 to 64 overall:
63%
ulations
bearing
aadisproportionate
burden.
Over
thenext
next50
50
years,
projected
that
Over
the
itit isis projected
that
versus
58%
inyears,
2010/11.
The gaps
the
continent’s
economic
growth
rate will
will
the
continent’s
growth
rate
between
youtheconomic
and the general
population
55
continue
at
around
5-6%
per
annum.
continue
at
around
5-6%
per
annum.
were much wider for women (almost 8
extent
which
thisthan
translates
into
better
extent
totowhich
this
translates
into
better
percentage
points)
for men
(close
to
health
outcomes
though
is
contingent
on
health
outcomes
though
is
contingent
on
4 percentage points). Trends in youth
numberofoffactors,
factors,mirrored
includingthose
not only
only
the
aaunderemployment
number
including
not
of the
level
budgetary
allocations to
to the
the sector
sector
level
ofofbudgetary
allocations
general
population.
be
deployed
torespond
respond to
to emerging
emerging chalchal4.7
Determinants
of
be
deployed
to
lenges.
Equitable
access
and
treatment
for
lenges. Equitable
access and treatment for
employment
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
•
Population size in 2010
2010
Gender was important. In both rural and
urban areas, women had a 15% lower
Residents of the Northern region were
less likely to have formal employment.
•
In urban areas, migrants were more
chance of engaging in informal self-
likely to work in the informal sector and
employment. As well, women in urban
less likely to be unemployed, while in
areas were much less likely (11%) than
rural areas, migrants were in both the
those in rural areas (6%) to engage in
formal and informal sectors.
formal employment.
•
In
the
Eastern
region,
where
agriculture dominated, the likelihood of
Education was also significant. Higher
formal and informal self-employment
attainment was positively associated with
was low in both rural and urban areas.
formal
employment,
and
negatively
•
As people aged, they were less likely
associated with agriculture and informal
to
employment.
employment, and more likely to be in
The
positive
effect
of
engage
in
informal
self-
What factors are related to whether an
education on formal employment was
individual ends up in formal, informal, or
strongest in urban areas. Nonetheless, in
agricultural employment? To answer this
Predictedsecondary
populationand
size inhigher
2050
urban areas,
credit were, as expected, more likely
education area were associated with
to be engaged in formal and informal
unemployment among women. This may
employment.
severehealth
health challenge.African
Africandemogrademograsevere
question, a challenge.
multinomial logit model
for
employment in 2010/11 was estimated.
peopleliving
livingin
inAfrica
Africatoday,
today, and itit isis the
the
people
Because residents
of rural andand
urban areas
only
continent
that
is
expected
to
double
in
only
is expected
to double
in
facecontinent
different that
labour
markets,
separate
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
models were estimated by rural-urban
more,
the majority of this population will
more,
the majority
of thisThe
population
will
locationtoand
gender.
employment
belong
theby
youth
cohort. Africa
is the
belong
to
the
youth
cohort.
Africa
is
the
categories
considered
were:
formal,
world’s
youngest
region and
is expected
world’s youngest region and is expected
informal,
and notinemployed
to
have theagriculture
largest workforce
the world
to have the
largest
9 workforce in the world
7
.
The
results
for people
(base
category)
by 2040.7 Ensuring the good
health
of this
by 2040. Ensuring the good health of this
10
Predicted population size in 2050
be due to the scarcity of and slow growth
agriculture and formal employment.
•
•
Residents of households that obtained
Accumulation of household assets
in employment opportunities, compared
was
with the number of graduates. Hence,
employment, more than with other
unemployment rates are higher among
employment outcomes.
associated
with
agricultural
well-educated women.
The
presence
of
young
children
aged 15 to 64 are presented in Table 11 .
constrained formal employment in urban
columns
show the
estimated
3TheAfDB,
“A Strategic
Framework
for marginal
Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Atlas
of
Statistics
(2011b).
AfDB, Africa inHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
areas; in rural areas, it increased the
Agricultural employment includes those who
are self-employed in agriculture and unpaid family workers.
10
This includes all categories of the labour
force including those in self-employment.
9
Source: AfDB (2011a).
Source: AfDB (2011a).
28
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table
11. Determinants
of formal/informal/agriculture
employment and notemployment
employed, by rural-urban
aged
15 toinclud64,
Table
11: Determinants
of formal/informal/agriculture
andregions.
notlocation,
employed,
by rural-urban
Variouspopulation
infectious
diseases
regions.
Various
infectious
diseases
includlocation,
population
Rwanda,
2010/11aged 15 to 64, Rwanda, 2010/11
ing malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
Multinomial logit (marginal effects)
Sample: Individuals (aged 15 to 64)
geographical Rural
range of vector-borne disgeographical range
of vector-borne diseases
has
been
with regional warmFormal
Informal
Agriculture
Not
Formal
Informal linked
Agriculture
eases has been linked with regionalNot
warming and the consequent altered length of
employed
ing and the consequent alteredemployed
length of
seasons.
Climate change
increase the
Female=1
-0.112***
-0.147***
0.194***
0.065***
-0.062***
-0.161***
0.222***could 0.001
seasons.
Climate change
could increase the
at risk of malaria in
Africa by
(-8.827)
(-10.535)
(17.103)
(6.962)
(-16.673)population
(-31.295)
population
at risk(41.929)
of malaria in(0.574)
Africa by
Age in years
0.003***
-0.009***
0.007***
-0.002***
-0.000* an additional
-0.003*** 1700.004***
-0.000***
million by 2030and
and the
million by 2030
(5.800)
(-12.974)
(14.452)
(-3.419)
(-2.079)an additional
(-15.411) 170 (16.370)
(-4.472) the
global
population
at
risk
of
dengue
fever
Migrant
0.007
0.111***
-0.092***
-0.027**
0.015***
0.002 fever
global0.022***
population-0.039***
at risk of dengue
13
(0.499)
(7.111)
(-7.762)
(-2.596)
(4.401) by 2 (5.282)
(-7.809)
(1.569)
Furthermore,
billionby
bythe
the2080s.
2080s.13 Furthermore,
by 2 billion
Education dummies
the
rapid
and
unplanned
urbanization
that
Some primary
0.042
-0.055*
0.006
0.007
0.030***
-0.001
-0.034***
0.005 that
the rapid
and unplanned
urbanization
(1.452)
(-2.250)
(0.322)
(0.314)
(5.205) is happening
(-0.183) on (-4.736)
(1.638)
thecontinent
continent
fraught
is happening
on the
isisfraught
Completed primary
0.102***
-0.067**
-0.052**
0.016
0.049***
0.006
-0.062***
0.008*
-(3.608)
(-2.662)
(-2.676)
(0.687)
(7.912)
(0.920)
(-7.788)
(2.369)
Secondary
0.252***
-0.209***
-0.111***
0.069**
0.134***
0.023**
-0.174***
0.016*** - (9.606)
(-8.604)
(-5.672)
(3.232)
(21.644)
(3.039)
(-19.246)
(5.182)
cient
or
contaminated
drinking
water,poor
poor
cient or
contaminated
drinking water,
Postsecondary
0.471***
-0.344***
-0.197***
0.070**
0.285***
0.038
-0.347***
0.024***
sanitation
andsewage
sewage
systems,
industrial
(16.538)
(-8.729)
(-5.884)
(3.057)
(21.052)sanitation
(1.164)
(-9.077)
(6.116)
and
systems,
industrial
Obtained credit
0.098***
-0.028
-0.015
-0.054***
0.029***waste,
-0.001
-0.019***
-0.009***
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,(-0.129)
and
(7.418)
(-1.776)
(-1.157)
(-4.559)
(7.933)
(-3.557)
(-4.317)
1414 Sustainable policies
and
unemployment.
Sustainable
policies
Log of non-agricultural income
0.001
0.003***
-0.004***
-0.001
0.000 and unemployment.
0.001***
-0.001***
0.000
(1.047)
(3.615)
(-4.224)
(-1.186)
(1.395) for
(3.331) energy,
(-3.747)
(0.073)
forhousehold
household
energy,
agricultural
producagricultural
producLog of value of agricultural
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
-0.012***
-0.006**
0.024***
-0.007***countries
-0.006***
0.022***
-0.001***
assets
data. At present,
tivity, -0.015***
nutrition, transportation,
water and
(-6.551)
(-2.953)
(10.932)
(-5.757)
(-4.669)
(-10.458)
(11.504)
(-5.503)
technology
claim
m-health sanitation,
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine or m-health
Household structure
1515
isisrapidly
increasing
connectivity
across
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
rapidly increasing
across
(also known
although
impact on the burden of diseases.
Number
of children connectivity
younger
-0.019**
0.006
0.010
0.003
0.006**
-0.005
0.001
than 7
the
majority
of these projects
still -0.002
in
the
majority
are
still
in
(-3.012)
(0.921)
(1.653)
(0.705)
(-0.908)
(2.582)
(-1.914)
(1.879)
health
sector.
Internet
broadband
penetheir
In this respect,
scaling up
up
health
sector.
Internet
broadband
pene- 0.003
their infancy.
infancy.
Number
of children
7 to 14
-0.010
0.009
-0.002 scaling
-0.001
-0.003
0.004
0.000
(1.806)
(-0.458)
(-0.831)are
(-1.598)
(1.807)Foreign
(0.573)
tration
are likely
likely
todecline.
decline.
Foreign
aidfrom
from
trationhas
hasrisen
risenrapidly,
rapidly,from
from a(-1.812)
a meager
meager (0.512)
to
aid
Number of males 15 to 64
0.006
-0.013*
-0.006
0.014***
-0.000
0.000
-0.001
0.001*
12
12
0.1%
an
opportunity
to improve (4.399)
systems.(-0.169)traditional
traditional
international
donors
devel0.1%ofofthe
thepopulation
populationinin2000
2000to
to
anestiesti- (-2.346)
opportunity(-1.231)
health systems.
totodevel(1.224)
(0.114)international
(-0.364) donors
(2.213)
Number
males
659 9or
older
-0.105**is
0.023
0.068***
0.008 oping
0.001
mated
7%ofinin
2010.
By
2060,coverage
coverage
is 0.014
countries
declining
will
mated
7%
2010.
By
2060,
oping-0.015
countriesisis0.006
decliningand
and
willlikely
likely
(-2.733)
(0.371)
(0.755)
(3.732)
(0.923)
(-1.431)
(0.495)
(0.666)
projected
risedramatically
dramatically
to
99% of
of 0.029***
The changing
changing
land
-play
ininAfrican
developprojected
totofemales
rise
to
99%
The
environmental
land0.012***
play a0.009***
a reduced
reducedrole
role
African
developNumber of
15 to 64
0.014**
-0.043***
0.000
-0.021***
0.001
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens
poverty
over
50
(2.581) -(4.835)
(-7.537)
(0.008)
(6.674) ment
(-8.014)
(1.220)
the
scape
to increase
poverty and
and
ment(3.995)
overthe
thenext
next
50years.
years.In
Inthe
thepast,
past,
Number of females 65 or older
-0.022
0.024
-0.006
0.005
0.009
0.027**
-0.040***
0.004**
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
African
healthcare
systems
been
tion
health
Addressing
African
healthcare(-3.872)
systemshave
have(2.649)
beenheavheav(-0.832)
(0.829)
(-0.258)
(0.282)
(1.212)
(3.180)
the health
health impacts from climate change
ily
the
change
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
Regional dummies
Southern
-0.005 of
-0.078***
0.179***
-0.095***
-0.035**
0.082***
-0.010***
human
resources,and
andininthe
theprovision
provision
from
development
banks,
agencies,
human
resources,
of
from-0.037*
development
banks,UN
UN
agencies,
(-0.278)
(-4.091)
(13.662)
(-5.178)
(-2.885)
(-2.476)
(4.409)
(-3.957)
high-quality
healthcare
services.
E-Health,
which
the
is
ill-equipped
to
and
organizations
such
as
the
Global
high-quality
healthcare
services.
E-Health,
which
the
continent
ill-equipped
to
and
organizations
such
as
the
Global
Western
0.012
-0.094***
0.111***
-0.029
-0.030*
-0.025
0.061**
-0.007**
(0.482)
(-3.489)
(5.662)
(-1.450)
(-2.475)
(-1.644)
(3.287)
(-2.912)
for
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
for example, can expand service delivery
handle. Increased climate variability and
Fund. In light of the uncertain condition
Northern
-0.077*
-0.045
0.177***
-0.055*
-0.025*
0.082***
and
ensure
greater
accountability
in
health
the
expected
temperature
warming
will
of
the-0.046**
global
African-0.011***
countries
and ensure greater accountability (-2.486)
in health
the expected
temperature
warming will
globaleconomy,
economy,
countries
(-1.489)
(8.341)
(-2.285)
(-2.085) of the(-3.037)
(4.359) African
(-4.036)
services
through
error
reduction,
diagwill
need
to
reevaluate
their
relationships
Easternthrough error reduction,
-0.074*
-0.073*
0.224***
-0.077*
-0.045***
-0.070***
0.123***
-0.008**
services
diagwill need
to reevaluate
their relationships
11
(-2.329)
(11.003)
(-3.706)with international
(-4.623)
(6.553)
(-3.266)
11 It can
nosticaccuracy
accuracyand
andtreatment.
treatment.(-2.369)
human aspects,
aspects,
mediating(-2.512)
health
aid
nostic
It can
human
mediating
health outcomes
outcomes
with international
aidagencies
agenciesand
andbilateral
bilateral
Observations
3,892
3,892
3,892
3,892
22,144
22,144
22,144
22,144
also
increase
the
transparency
of
medical
across
the
continent,
through
both
direct
partners
and
possibly
look
more
also increase the transparency of medical
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
Notes: z-statistics
in parentheses
; *** p<0.001,
** p<0.01,
* p<0.05 Climate change will
procurement
and
distribution
operations.
and
indirect
channels.
South
and
private–public
partnerships.
procurement and distribution operations.
and indirect channels. Climate change will
South and private–public partnerships.
exacerbate food
food and
and water
water insecurity
and
exacerbate
insecurity
and
Source: EICV3, 2011.
streamliningprocesses,
processes,reducing
reducingwaitwaitthreaten the
the livelihoods
livelihoods and
bybystreamlining
threaten
and health
health of
of many
many domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
of
new
international
ing times, and improving the accuracy of
African populations. Droughts are likely
the involvement of new internationalaid
aid
Table 12 examines wage versus non-wage
of become
formal sector
employment
wasin11%
was associated with higher education; in
to
more
prevalent,
both
freplayers.
to become more prevalent, both in freplayers.
non-agricultural wage; nonlower than
that
of men
in urbanfarm
areas
and
urban areas, the importance of higher
quency
and
severity,
reducing
yields
9employment:
Ibid.
quency and severity, reducing farm yields
9 Ibid.
10
Ibid.
agricultural
informal
self-employment;
6%
lower
in
rural
areas.
In
urban
areas,
education was attenuated. In rural areas,
and increasing hunger and starvation, par10 Ibid.
and increasing hunger and starvation, par11
13 AfDB, A Strategic Framework for Improving
11agriculture; and not employed. The13
AfDB, A Strategic
Framework
for Improving
migrationinwas
positively
associated
with
secondary
education
increased
the
ticularly
Southern
Africa
and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
Urban
for
health. Examples
include wage
treatingemployment
patients, conprobability
of non-farm
for health. Examples include treating patients, conducting research, educating the health workforce,
was 20%
lower
for women
thanworkforce,
men in
ducting
research,
educating
the health
tracking diseases and monitoring public health.”
tracking
diseases
and
monitoring
public
health.
”
rural and urban areas. Women’s probability
non-farm wage employment.
12 Economist Intelligence Unit (2011).
12
Economist
(2011).
In rural
areas,Intelligence
non-farmUnit
wage
employment
Oct.
2012. of non-farm wage employment
probability
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
by 15%,
postsecondary
by
14
AfDB,and
A Strategic
Framework,education,
” op. cit.
15 Ibid.
15
Ibid.
41%.M
29
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
Table 1: Determinants of wage/non-wage employment, by rural-urban location, population aged 15 to 64,
Rwanda,
2010/11 of wage/non-wage employment, by rural-urban location, population aged 15 to 64, Rwanda, 2010/11
Table
12. Determinants
8
rapid
young
will be
be critical
critical in
in order
order in
in less
less than
than 20
20years.
years.8
rapideconomic
economic growth
growth has
has boosted
boosted the
the
young population
population will
Multinomial
logit (marginal
effects)
amount
of
resources
allocated
to
health
infraAfrican
subregions
areexpected
expectedtotogrow
grow
to
harness
the
potential
of
the
youth
bulge
amount of resources allocated to health infraAfrican subregions are
to harness the potential of the youth bulge
Sample:
Individuals
(aged
15
to
64)
structure
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
the
Urban
Rural
services.
In
spite
of
this,
issues
of
governidend.
’
Concurrently
though,
Africa
has
an
services. In spite of this, issues
of govern- Informal
idend.’ Concurrently
though,
Africa hasFormal
an
Wage
Agriculture
Not
Informal
Agriculture
Not
ance
hampered
aging
population.
In 2010,
2010, people
people aged
aged 60
60 youth
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
anceand
andincome
incomeinequality
inequalityhave
have
hampered
aging
population.
In
(non-agric)
(non-agric)
employed
employed
or
older
accounted
for
just
6%
of
Africa’s
increasing
pressure
on
health
systems,
highor older accounted
for0.081***
just 6% of Africa’s
pressure-0.063***
on health systems,
highFemale=1
-0.208***
0.142***
-0.015**
-0.197***increasing
0.207***
0.053***
population,
but
this
is
expected
to
rise
to
lighting
the
need
to
address
family
planning
population,
but
this
is
expected
to
rise
to
lighting
the
need
to
address
family
planning
(-15.282)
(11.816)
(-2.898)
(7.904)
(-34.560)
(32.752)
(-15.668)
(11.710)
Age remains
(years)
-0.004***
-0.004***
-0.002***services,
0.003***
-0.000
-0.001***
cient,
six
13% over0.000
the next 50 years
(Figure 1).
1).Some
Some
services,
maternaland
andchild
childhealthcare,
healthcare,
and
cient,
remainshigh,
high,and
andin
in 2010,
2010,
six of
of the
the 0.007***
(Figure
maternal
and
(-6.280)
(13.568)
(1.675)
(-6.966)
(-8.761)
(11.666)
(-1.838)
(-4.192)
10
most
were
countries,-0.010
such as Liberia
Nigeria,0.035***
are
10Migrant
mostunequal
unequalcountries
countriesworldwide
worldwide
and Nigeria,
are
0.154*** were -0.068***
-0.077***
-0.005
-0.003
-0.028***
33
ininSub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
(10.009)
(-4.991)
(-1.902)
(-7.327)
(6.650)
(-0.731)
(-0.889)
(-5.771)
Sub-Saharan Africa. While poverty has
population size
Ibid.
88 Ibid.
Education dummies
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
Some primary
0.039
(1.534)
Completed
primary
0.049
meet
the
goal
poverty
meet
theMDG
MDG
goalof
of halving
halving
poverty by
by
(1.867)
-Secondary
0.027
(1.040)
ulation
still
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)
stillsubsists
subsists
Postsecondary
0.216*** 44
on
As
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).
As
(6.918)
Obtained credit
0.051**
(3.146)
improving
health
outcomes,with
withwomen,
women,
totoimproving
outcomes,
Log
of health
non-agricultural
-0.016***popincome
rural
dwellersand
andother
othermarginalized
marginalized
poprural
dwellers
(-19.783)
ulations
bearingaadisproportionate
disproportionate
burden.
ulations
burden.
Log of bearing
value of agric
assets
-0.008***
Overthe
thenext
next50
50years,
years, itit isis projected
projected
that
(-3.907) that
Over
Household structure
the
continent’s
economic
growth rate
rate will
will
the
continent’s
economic
growth
Number
of children
younger
-0.006
than 7 at
continue
ataround
around5-6%
5-6% per
per annum.
annum.55
continue
(-0.811)
extent
which
this
translates
into better
better
extent
totowhich
this
translates
into
Number
of
children
aged
7 to
14
-0.002
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
(-0.418)
a
number
of
factors,
including
not
only
the
a number
of males
factors,
including
not only the
Number of
aged
15 to
64 of budgetary allocations 0.012*
level
to
the sector
sector
level of budgetary allocations (2.167)
to the
Number of males aged 65 or
-0.041
older
be
deployedto
torespond
respond to
to emerging
emerging
chalbe deployed
(-0.993) challenges.
Equitable
access
and
treatment
for
Number
of
females
aged
15
lenges. Equitable access and treatment for
0.052***
to 64
thepoorest
poorestsegments
segmentsof
ofsociety
society(8.668)
onecritical
critical
the
isisone
Number of females aged 65
challenge.
challenge.
0.011
or older
(0.342)
Regional dummies
Southern
-0.033
severe
healthchallenge.
challenge.African
African
demograsevere
health
demogra(-1.617)
Western
0.007
(0.253)
people
living
in
Africa
today,
and itit isis the
the
people
living in Africa today,-0.039
and
Northern
only
continent
that
is
expected
to
double
in
only continent that is expected(-1.190)
to double in
6
Eastern
-0.018
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
(-0.470)
more,
the
majority
of
this
population
will
Observations
4,709
more,
the majority of this population
will
0.023
(1.118)
-0.006
(-0.298)
-0.076***
(-3.517)
-0.198***
(-6.837)
0.074***
(5.787)
0.020
(1.957)
0.027*
(2.571)
0.014
(1.241)
0.015
(1.125)
-0.004
(-0.682)
-0.082***
(-4.460)
-0.070***
(-3.607)
0.036*
(2.049)
-0.032
(-1.480)
-0.121***
(-8.637)
0.027***
(3.647)
0.052***
(6.223)
0.151***
(16.750)
0.415***
(15.002)
0.030***
(5.428)
-0.037***
(-4.462)
-0.102***
(-10.680)
-0.302***
(-27.516)
-0.538***
(-10.526)
0.079***
(11.479)
0.006
(1.539)
0.018***
(3.970)
0.020***
(3.787)
0.031
(1.862)
0.001
(0.397)
0.003
(0.519)
0.031***
(4.177)
0.131***
(17.173)
0.092**
(2.971)
-0.110***
(-19.015)
0.023***
(32.434)
-0.000
(-0.097)
-0.001***
(-4.330)
0.002
(1.919)
-0.005***
(-8.709)
0.006***
(4.649)
-0.005***
(-14.031)
-0.012***
(-6.715)
0.015***
(34.358)
-0.010***
(-3.786)
-0.002***
(-8.727)
0.004**
(2.917)
-0.008***
(-22.063)
0.018***
(8.206)
0.006
(1.033)
-0.002
(-0.795)
0.001
(0.297)
0.005
(1.867)
0.005
(1.555)
0.001
(0.377)
-0.011***
(-4.345)
-0.005
(-1.058)
-0.000
(-0.022)
0.008
(1.941)
-0.007**
(-2.966)
0.004
(1.442)
-0.000
(-0.265)
0.003
(1.631)
-0.018***
(-3.470)
-0.001
(-0.310)
0.007
(1.689)
0.009**
(3.252)
-0.034***
(-10.270)
-0.000
(-0.114)
0.025***
(11.271)
0.002
(0.041)
0.001
(0.050)
0.038
(1.750)
0.001
(0.064)
-0.014
(-0.906)
-0.012
(-1.570)
0.025**
(2.630)
-0.057***
(-10.189)
0.001
(0.517)
0.003
(0.770)
0.024***
(8.556)
-0.047***
(-14.207)
0.005**
(3.142)
0.018***
(8.251)
-0.028
(-0.878)
-0.015
(-1.132)
0.031
(1.734)
0.039***
(3.529)
-0.053***
(-3.888)
0.011
(1.907)
0.002
(0.258)
0.175***
(7.565)
0.191***
(8.232)
0.254***
(10.785)
0.210***
(9.064)
21,310
-0.018
(-1.799)
-0.018
(-1.745)
-0.008
(-0.821)
-0.016
(-1.559)
21,310
-0.112***
(-8.157)
-0.146***
(-10.517)
-0.233***
(-15.789)
-0.102***
(-7.431)
21,310
0.163***
(10.226)
0.119***
(5.610)
0.155***
(5.877)
0.219***
(8.454)
4,709
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
Population size in 2010
2010
Predicted population
Predicted
population size
size in
in 2050
2050
0.010
(1.512)
0.009
(1.046)
-0.010
(-0.738)
0.030***
(3.718)
4,709
-0.140***
(-8.796)
-0.136***
(-5.831)
-0.107***
(-4.402)
-0.230***
(-5.457)
4,709
-0.045*
(-2.411)
-0.027
(-1.472)
-0.013
(-0.686)
-0.092***
(-4.918)
21,310
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
Notes: z-statistics
in parentheses
; *** p<0.001, ** p<0.01, * p<0.05
world’s
youngest region
and is expected
world’s youngest region and is expected
to have the largest workforce in the world
EICV3,
2011.
toSource:
have the
largest
workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
30
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Table 13. Determinants of youth employment outcomes, population aged 15 to 34, Rwanda, 2010/11
regions. Various infectious diseases includMultinomial logit (marginal effects)
Sample: Individuals (aged 15 to 34)
Urban
Female=1
Age group (years)
19 to 22
23 to 26
27 to 30
31 to34
Migrant
Rural
School
only
-0.007
(-0.545)
Work
only
-0.071***
(-4.800)
Work
and
school
0.005
(.)
-0.155***
(-13.624)
-0.251***
(-19.277)
-0.404***
(-17.416)
-0.438***
(-11.443)
-0.028*
(-2.305)
0.181***
(10.327)
0.253***
(14.146)
0.379***
(17.368)
0.417***
(13.471)
0.018
(1.182)
-0.061
(.)
-0.049
(.)
-0.018
(.)
-0.008
(.)
0.007
(.)
Nothing
0.072***
(7.253)
regions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
School
Work
Work and
Nothing
only
only
school
geographical
range
of vector-borne disof vector-borne
-0.007 geographical
0.022*** range
-0.014***
-0.001 diseases has been linked
with regional
warm(-1.290)eases (4.035)
(-3.419)
(-0.338)
has been linked with regional
warm-
ing and the consequent altered length of
Education dummies
Some primary
-0.321
(-0.009)
Completed primary
-0.248
(-0.007)
Secondary
-0.131
(-0.004)
Postsecondary
-0.071
(-0.002)
Obtained credit
-0.087***
(-3.297)
Log of non-agricultural income
-0.002*
(-2.570)
Log of value of agric assets
-0.001
technology
(ICT) revolution in (-0.695)
Africa
technology
Africa
parent_hh (ICT) revolution in0.145***
(13.093)
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
hhh_age21
0.188
(0.012)
Household
Structure
health
sector.
Internet
broadband
penehealth
sector.
Internet
broadband
peneNumber of children younger than
7
-0.024***
tration
has
tration
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
(-3.971)
0.1%
ofofthe
population
inin72000
0.1%
the
population
2000
toan
anestiestiNumber
of
children aged
to
14 to
0.005
(1.105)is
mated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage
is
mated
Number of males aged 15 to 64
0.010*
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
projected
(2.515)
Number of males aged 65
the
Africanpopulation.
population.1010or older 0.045* -the
African
(2.055)
tion
provides
theopportunity
opportunity
toovercome
overcome
Number
of females
aged 15 to 64
0.016***
tion
provides
the
to
(3.516)
Number of females aged 65 or
0.041*
older
human
resources,and
andininthe
theprovision
provision
of
human
resources,
of
(2.157)
high-quality
healthcareservices.
services.E-Health,
E-Health,
Regional Dummies
high-quality
healthcare
-0.015
forSouthern
example,can
canexpand
expandservice
servicedelivery
delivery
for
example,
(-0.976)
Western
and
ensuregreater
greateraccountability
accountabilityin
in-0.006
health
and
ensure
health
(-0.278)
services
through
error
reduction,
diagservices
through error reduction,-0.043
diagNorthern
11(-1.824)
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
Eastern
0.005
also
increase
the
transparency
of
medical
(0.193)
also increase the transparency of medical
0.035**
(2.856)
0.047***
(3.892)
0.043***
(3.331)
0.029
(1.824)
0.003
(0.339)
ing and
the consequent
altered
length of
-0.171***
0.225***
-0.047***
-0.006**
Climate change
could(-2.659)
increase the
(-35.870)seasons.
(46.655)
(-11.928)
seasons. Climate change could increase the
-0.281***
0.335***
population
at risk-0.052***
of malaria -0.002
in Africa by
population
at risk(-9.802)
of malaria in
Africa by
(-42.507)
(61.888)
(-0.774)
an
additional
million
by
2030
and the
-0.401***
0.446*** 170-0.051***
0.007*
an additional
170 (-5.337)
million by 2030
and the
(-23.943)
(38.728)
(2.377)
global
population
at
risk
of
dengue
fever
-0.535***
0.022***
global0.535***
population-0.021
at risk of dengue
fever
13 (5.095)
(-11.024)by 2 (16.801)
(-1.147)
Furthermore,
billionby
bythe
the2080s.
2080s.13 Furthermore,
by 2 billion
-0.006
0.010*
-0.006
0.002
the
rapid
and
unplanned
urbanization
that
(-1.180)the rapid
(2.075)
(-1.653)urbanization
(0.907) that
and unplanned
is happening on the continent is fraught
continent-0.011
is fraught
-0.668
1.037
-0.048
0.185**is happening
-0.250***on the
0.076
(-0.012)
(.)
(-0.007)
(2.907)
(-5.469)
(1.319)
(-1.224)
--0.715
1.030
-0.067
0.219***
-0.304***
0.098
-0.013
-(-0.013)
(.)
(-0.010)
(3.449)
(-6.673)
(1.712)
(-1.447)
-0.881
1.080
-0.069
0.377***
-0.485***
0.122*
-0.013
cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
(-0.016)
(.)
(-0.011)
(5.944)
(-10.700)
(2.133)
(-1.484)
sanitation
andsewage
sewage
systems,
industrial
sanitation
and
systems,
industrial
-0.956
1.140
-0.113
0.448***
-0.616***
0.178**
-0.009
(-0.017)
(.)
(-0.017)
(6.987) waste,
(-13.307)
(3.097)
(-0.974)
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,0.176***
and
0.077***
0.047
-0.037**
-0.198***
0.040***
-0.018***
1414 Sustainable policies
and
unemployment.
(3.466)
(.)
(-3.002)
(-12.426)
(14.863)
(5.312)
(-3.625)
and unemployment.
Sustainable
policies
0.003***
0.001
-0.002***
-0.003***
0.002*** energy,
0.002***
-0.000*
forhousehold
household
agricultural
producfor
energy,
agricultural
produc(3.627)
(.)
(-3.832)
(-8.801)
(4.770)
(6.434)
(-2.001)
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
0.005**
-0.000
-0.004***
0.006**
0.000
-0.003*
-0.003***
data. At present,
countries
tivity, nutrition, transportation, water and
(2.785)
(.)
(-3.391)
(3.260)
(0.200)
(-2.408)
(-5.987)
claim
to
telemedicine
m-health
sanitation,
couldhave
haveaalarge
largeand
andpositive
positive
claim
to be
be using
sanitation,
could
-0.200***
0.038
0.017 or m-health
0.062***
-0.082***
0.021***
-0.000
1515
(-13.572)
(.)
(1.764)
(10.670)
(-14.725)
(4.661)
(-0.085)
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
(also known
although
impact on the burden of diseases.
0.549
0.143
-0.880
-0.033
0.010
0.037*
-0.015
the
majority
of
these
still
in
the
majority
projects
are
still
in
(0.011)
(.)
(-0.013)
(-1.019)
(0.371)
(2.230)
(-0.811)
their
scaling up
up
their infancy.
infancy. In this respect, scaling
0.016*
-0.005
0.013**
-0.006* are
0.008**
-0.002Foreign
-0.000
are likely
likely
todecline.
decline.
Foreign
aidfrom
from
to
aid
(2.363)
(.)
(3.269)
(-2.295)
(3.073)
(-1.009)
(-0.027)
12
12
opportunity
to
improve0.002
systems.0.006**traditional
traditional
international
donors
developportunity
health systems.
international
totodevel-0.002
-0.004
-0.009***
0.000 donors
0.003**
(-0.419)
(.)
(0.480)
(3.048) oping
(3.221)
countries
declining
will
oping(-4.405)
countriesisis(0.169)
decliningand
and
willlikely
likely
-0.023***
0.002
0.010**
0.005*
0.001
-0.008***
0.002*
The
changing
land
-play
ininAfrican
developThe
changing
land
play a(0.559)
a reduced
reducedrole
role
African
develop(-4.390)
(.) environmental
(3.077)
(2.116)
(-4.741)
(2.473)
-0.013
-0.057
0.024
-0.001
-0.001
-0.002
0.004
scape
threatens
poverty
and
ment
over
the
next
50
years.
In
the
scape
threatens
to
increase
poverty
and
ment
over
the
next
50
years.
In
thepast,
past,
(-0.416)
(.)
(1.341)
(-0.161)
(-0.133)
(-0.246)
(1.111)
health
problems
African
healthcare
systems
been
-0.009 problems
-0.006 in Africa.
-0.001 Addressing
0.010***
-0.004
0.003**
health
Addressing
African
healthcare-0.009***
systemshave
have
beenheavheav(-1.635)
(.)
(-0.290)
(4.338)
(-1.540)
(-4.880)
(2.648)
the health
health impacts from climate change
the
change
-0.041
(-1.630)
0.001
(.)
-0.001
(-0.042)
ily
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
0.035***
0.013*
0.001
from
development
banks,
agencies,
from-0.049***
development
banks,UN
UN
agencies,
(4.140)
(-5.814)
(2.084)
(0.265)
which the
the continent is ill-equipped
and
which
ill-equipped to
to
and organizations
organizations such
such asasthe
theGlobal
Global
0.076***
0.020
-0.080***
0.016
-0.030
0.027
-0.012*
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
handle.
climate
variability and
In light of (1.478)
the uncertain
condition
(4.036) Increased
(.)
(-5.615)
(0.733) Fund.
(-1.477)
(-2.078)
0.097***
-0.052
-0.039*
0.018
-0.020
0.022
-0.020***
the
expected
temperature
warming
will
of
the
global
economy,
African
countries
the expected temperature warming will
of the global economy, African countries
(3.692)
(.)
(-2.419)
(0.833)
(-0.954)
(1.193)
(-3.308)
will need
to reevaluate
their
theirrelationships
relationships
0.098***
-0.000
-0.055**
-0.062**will need
0.018to reevaluate
0.065***
-0.022***
(3.347) aspects,
(.) mediating
(-2.638)
(-2.875)with international
(0.860)
(3.558)
human
health
outcomes
aid
agencies
and
human
aspects,
mediating
health outcomes
with international
aid agencies(-3.430)
andbilateral
bilateral
0.113**
0.027
-0.145***
0.020
-0.018
0.013
-0.016**
across
the
continent,
through
both
direct
partners
and
possibly
look
more
totoSouth–
(3.007)the continent,
(.)
(-3.372)both direct
(0.961) partners
(-0.859)
(0.703)
(-2.628)
across
through
and possibly
look more
South–
procurement
and
distribution
operations.
and
indirect
channels.
Climate
change
will
South
and
private–public
partnerships.
procurement
and distribution operations.
and
indirect channels.
Climate
change will
South19,367
and private–public
partnerships.
Observations
4,331
4,331
4,331
4,331
19,367
19,367
19,367
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
streamlining
processes,
reducing
waitthreaten
the livelihoods
livelihoods
Notes:
z-statistics
in parentheses
; ***
p<0.001,
** p<0.01,
* p<0.05 and
byby
streamlining
processes,
reducing
waitthreaten
the
and health
health of
of many
many domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
of
new
international
aid
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
of
new
international
aid
Source: EICV3, 2011.
to
become
more
prevalent,
both
in
freplayers.
to become more prevalent, both in freplayers.
quency
and
severity,
reducing
farm
yields
9 Ibid.
quency and severity, reducing farm yields
9 Ibid.
10 Ibid.
and increasing hunger and starvation, par10 Ibid.
and increasing hunger and starvation, par11
13 AfDB, A Strategic Framework for Improving
11
13 AfDB, A Strategic Framework for Improving
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
31
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
population
will be critical in order
5. Conclusions and young
policy
implications
to harness the potential of the youth bulge
rapid
rapideconomic
economic growth
growth has
has boosted
boosted the
the
amount
of
resources
allocated
to
health
infraamount of resources allocated to health infrastructure
and
to
social
structure
tosurvival-enhancing
survival-enhancing
social
The main and
objective
of this analysis was
to
services.
In
spite
of
this,
issues
of
governservices.
spite understanding
of this, issues of
provide aInbetter
of governgender
ance
anceand
andincome
incomeinequality
inequalityhave
havehampered
hampered
and youth employment outcomes in
Rwanda. In addition, the study sought to
examine whether statistical evidencecient,
remains
high,
and
in
2010,
six
of
the
cient,
remains
and in 2010,
of the
suggests
thehigh,
existence
of sixgender
10
most
unequal
countries
worldwide
were
10
most
unequal
countries
worldwide
were
discrimination in the3 Rwandan labour
3 While poverty has
ininSub-Saharan
Africa.
Sub-Saharan Africa. While poverty has
market.
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
While overall employment rates remained
meet
meetthe
theMDG
MDGgoal
goalof
of halving
halving poverty
poverty by
by
the same between 2005/06 and 2010/11,
-substantial shifts occurred in the labour
ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
market. The percentage of women44 in
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted). As
As
young population will be critical in order
to harness the potential of the youth bulge
and
capture
so-called
‘demographic
divand
capture the
theInso-called
‘demographic
divconsiderable.
2010/11,
median monthly
idend.
’
Concurrently
though,
Africa
has
an
idend.
’ Concurrently
though, for
Africa
hasand
an
salaries
were RWF 22,000
men
aging
population. In
In 2010,
2010, people
people aged
aged 60
60
aging
RWF population.
13,200 for women.
And although
or
older
accounted
for
just
6%
of
Africa’s
or
older accounted
just 6% ofbetween
Africa’s
median
wages for
increased
population,
but
this is
is expected
expected to
to rise
rise to
to
population,
but
this
2005/06 and 2010/11, the gender pay gap
13% over the next 50 years (Figure
(Figure 1).
1).Some
Some
widened—from a difference of 33% to
countries, such as Liberia and Nigeria,
Nigeria, are
are
67%. The gap was widest among people
expected to double their population
population size
size
in less
less than
than 20
20years.
years.8 8
in
African subregions
subregionsare
areexpected
expectedtotogrow
grow
African
the
fastest,tripling
tripling
their
populations
over
the
fastest,
populations
education
will be their
required
to tap over
the
with only primary school education.
is substantial; men have a greater
Ibid.
88pay
Ibid.
Earnings were highest for people with
tendency to be employed in both the
postsecondary education.
formal
likely to have wage employment. The
percentage of women who work without
and
informal
sectors
where
earnings are relatively high. Among youth,
Among those in wage employment, 47%
men and women have nearly similar farm-
of youth were unskilled workers, compared
wage earnings, but men fare better than
Figure 1. Africa’s population
population will
will double
double
sizeby
by2050
2050
ininsize
agricultural self-employment declined,
with 53% overall. Furthermore, among
while the percentage who were unpaid
youth in wage employment, 64% of the
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
family workers increased. Among men, the
rural
dwellersand
andother
othermarginalized
marginalized poppoprural
dwellers
percentage
in
the
agriculture
and
unpaid
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
familythe
work
categories
the share
Over
next
50years,
years, itfell,
it isis and
projected
that
Over
the
next
50
projected
that
in
non-farm
wage
employment
rose.
The
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
estimated
number
of people
with 55noncontinue
around5-6%
5-6%
per annum.
annum.
continue
atataround
per
wage to
employment
declined into
frombetter
2.3
extent
to
whichthis
this translates
translates
into
better
extent
which
million
to
1.9
million.
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
Migration
into the
Kigali to
region
was
level
budgetary
allocations
to the
the sector
sector
level
ofofbudgetary
allocations
potential of the youth bulge in urban areas.
youthbulge
bulgeand
andpopulation
populationaging
agingwill
willexert
exert
youth
increasing
pressure
on
health
systems,
highincreasing
pressure
systems,
More than
half on
thehealth
people
whohighare
lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
lighting
employed are women, but men are more
services,maternal
maternaland
andchild
childhealthcare,
healthcare,and
and
services,
Population size in 2010
2010
women in every other wage category.
women were skilled workers, compared
Women’s concentration in unpaid family
with
work suggests that cultural factors (for
49%
of
all
women
in
wage
employment.
instance,
norms
about
domestic
responsibilities) are important in labour
Unemployment was lower for youth than
market decisions. Consequently, even if
for the labour force overall; for example, in
more
urban areas in 2010/11, the rates were
available, women’s access to such
13% and 22%, respectively.
opportunities may not equal that of men.
wage
employment
becomes
Land rights legislation implemented over
substantial, especially from the Southern
The multivariate analysis demonstrated
the past 15 years that favoured women
region.
However,
the overall
employment
be
deployed
torespond
respond
to emerging
emerging
chalbe
deployed
to
to
challenges.
Equitable
access
and
treatment
for
rate
was
much
lower
in
urban
than
lenges. Equitable access and treatmentrural
for
the
poorestsegments
segments
of
society
onecritical
critical
areas—76%
versusof
83%
in 2010/11.
By
the
poorest
society
isisone
challenge.
age group, employment rates follow an
challenge.
that education is a key determinant of
was a step toward reducing cultural
formal employment for women—especially
constraints that limit women’s labour
in urban areas. However, the presence of
market opportunities. And if the reduction
young children in the household was
in fertility is sustained, it will free up time for
inverted u-shape-rates are lowest among
negatively related to formal employment
women to engage in high-paying labour
youth and people aged 60 or older. The
Predicted population
among women.
Predicted
population size
size in
in 2050
2050
market activities.
severe
healthemployment
challenge.African
African
demograagricultural
rate is demograseasonal,
severe
health
challenge.
Rwanda has substantially reduced the
Rwanda’s public works initiative, the Vision
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
Trends
in youth
only
continent
that employment
is expected toparalleled
double in
6
size
by2020,
2020,
toreach
reach2.7
2.7for
billion.
6 What is
trends
in employment
the Rwandan
size
by
to
billion.
What is
more,
the
majority
of
this
population
will
population
overall.
Between
2005/06
more, the majority of this population and
will
belong to the youth cohort. Africa is the
belong
to the
is the
2010/11,
the youth
share cohort.
of 15-toAfrica
34-year-old
world’s youngest region and is expected
world’s
regionemployment
and is expected
workersyoungest
in non-farm
rose
to have the largest workforce in the world
tofrom
have10%
the
largest
workforce
in
the
world
to
30%,
while
the
share
in
by 2040.77 Ensuring the good health of this
byagricultural
2040. Ensuring
the good health
this
self-employment
fell fromof18%
percentage of its population without
2020 Umurenge Programme (VUP), could
education, particularly among youth.
address some of the employment needs
However, the strong association between
of women. The VUP could offer child care
higher education and better-quality jobs
to mothers selected to engage in public
suggests that continued investment in
works by making it possible for them to
education is needed. Specifically, it is
hire
necessary to ensure that young people
Evidence from Rwanda’s neighbours
attain some postsecondary education,
shows that such gender-focused public
to 6%. The movement of youth toward
which appears to be a prerequisite for non-
works can relieve the child care constraints
farm wage employment. Investment in
faced by working mothers, especially in
skills
rural areas (World Bank, 2009b).
dipping during July and August.
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“Awage
Strategic
Frameworkwas
for Improving
non-farm
employment
primarily
in Africa”
(2012).
Health
in Africa”
(2012).
4intoWHO,
Atlas
of
Health
Statistics
(2011b).
domestic services, followed by
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56construction.
AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
differences
in (2011a).
wages are
7 Gender
AfDB, Africa
in 50 Years’ Time
development
is also
Source: AfDB (2011a).
needed,
elderly
women
as
babysitters.
Source: AfDB (2011a).
especially for women, to make them more
employable and to reduce the male-female
Improvement of the business environment
wage gap. In addition, investment in
is a necessary precursor to further expan-
32
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
sion of the private sector, which would, in
ministration, the availability and cost of
turn, provide more employment opportu-
electricity, and high transport costs due to
nities for youth and women. According to
inadequate infrastructure. Removing bar-
the Rwanda Private Sector Foundation,
riers to small and micro-enterprises would
regions. Various infectious diseases includregions.
Various
diseases
includare better
than infectious
in agriculture.
Employers
ing malaria, cholera, diarrhea, dengue
ing
malaria,
diarrhea,
dengue
could
also be cholera,
encouraged
to offer apprenfever, meningitis, and schistosomiasis are
fever,
meningitis,
and
schistosomiasis
tice opportunities to youth through tax are
re-
informal sector, where earnings prospects
entrepreneurs face challenges with tax ad-
enable them grow and create jobs in the
bates and wage subsidies.
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and the consequent altered length of
seasons. Climate change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
global
population
riskTotal
dengue
fever
African Development Bank (2012), African Economic Outlook
McKay, A. (2000), “Should
thepopulation
Survey Measure
Household
global
atatrisk
ofofdengue
fever
13
by
billion
bythe
the2080s.
2080s.
2012: Promoting Youth Employment. Tunis: African Development
Income?” in Grosh, by
M. 22and
Glewwe,
P. (eds.),
Designing
13 Furthermore,
billion
by
Furthermore,
the
rapid
and
unplanned
urbanization
that
Bank.
Household Survey Questionnaires
for
Developing
Countries:
the rapid and unplanned urbanization that
happening
onStandard
thecontinent
continent
fraught
Lessons from Fifteen isis
Years
of Living
Measurement
happening
on
the
isisfraught
Ali, D.A., K. Deininger, and M. Goldstein (2011), Environmental
Study. Washington D.C.: The World Bank, pp. 83-104.
-and Gender Impacts of Land Tenure Regularization in Africa: Pilot
-cient
or
contaminated
drinking
water,
poor
Evidence from Rwanda, World Bank Policy Research Working
Ministry of Local Government
(2009), Vision
2020 water,
Umurenge
cient or contaminated
drinking
poor
sanitation
and
sewage
systems,
industrial
Paper No. 5765. Washington DC: The World Bank.
Programme (VUP). Public
Works
Operational
Framework
and
sanitation and sewage systems, industrial
waste,
andstress
stress
associated
withpoverty
poverty
Procedure Manual. Kigali:
Ministry
of
Local
Government.
waste,
and
associated
with
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
Appleton, S. et al. (1999), “The Gender Wage Gap in Three African
forhousehold
household
energy,agricultural
agricultural
producfor
producCountries,” Economic Development and Cultural Change, vol. 47,
Morrison, A. R., S. Sabarwal
and M. energy,
Sjoblom
(2008), “The
State
data.
At
present,
80%
of
African
countries
tivity,
nutrition,
transportation,
water
and
data. At present,
tivity, nutrition,
transportation,
water
and
no. 2, pp. 289-312.
of World countries
Progress” in Buvinic,
M., A. R.
Morrison., A.W.
Ofosutechnology
claim
m-health
sanitation,
couldhave
have
large
and
positive
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
claim to
to be
be using telemedicine
sanitation,
could
aalarge
and
positive
Amaahoretm-health
al. (eds.), Equality
for Women:
Where
do we
stand
on
1515
isisBlackden,
rapidly
increasing
connectivity
across
(also
known
as
mobile
health),
although
impact
on
the
burden
of
diseases.
rapidly increasing
connectivity
across and (also
known(2007),
although
impact
burden of diseases.
M., S. Canagarajah,
S. Klasen,
D. Lawson
Millennium?
Development
Goalon3?the
Washington
D.C.: The World
the
majority
of
these
still
in
the
majority
projects
are
still
in
“Gender and Growth in Africa: Evidence and Issues” in G.
Bank.
health
sector.
broadband
penetheir
In this respect, scaling
scaling up
up
health
sector.
Internet
broadband
penetheir infancy.
infancy.Core
Mavrotas
andInternet
A.
Shorrocks
(eds.), Advancing
Development:
tration
has
from
meager
are likely
likelyofto
toRwanda
decline.(2012),
Foreign
aidThird
from
tration
has
risenrapidly,
rapidly,
from aaHelsinki:
meager WIDER.
are
decline.
Foreign
aid
from
Themes
inrisen
Global
Development.
National Institute of Statistics
The
12
12
0.1%
opportunity
systems.
traditional
international
donors
devel0.1%ofofthe
thepopulation
populationinin2000
2000to
toan
anestiestiopportunity to improveIntegrated
health systems.
international
donors
totodevelHousehold traditional
Living Conditions
Survey
(EICV3):
Main
99
mated
7%
in
2010.
By
2060,
coverage
is
oping
countries
is
declining
and
will
likely
mated
7%
in
2010.
By
2060,
coverage
is
oping
countries
is
declining
and
will
likely
Chant, S and G. A. Jones (2005), “Youth, Gender and Livelihoods
Indicators Report. Kigali: National Institute of Statistics of Rwanda.
projected
torise
risedramatically
dramatically to
99%
of and
The The
changing
play
projected
99%
of
The
changing
environmental land
land-play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelopin West to
Africa:
Perspectives to
from
Ghana
Gambia”.
theAfrican
Africanpopulation.
population.1010
scape threatens
threatens to increase poverty
and
ment
over
the
next
50
years.
InInthe
the
scape
poverty
and
ment
over
the
next
50
years.
thepast,
past,
Children’s Geographies, Vol. 3, No. 2, pp. 185-199.
National Institute of Statistics of Rwanda (2012), EICV3 Thematic
tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
health problems
problems in Africa. Addressing
African healthcare
systems
tion
health
healthcare
systemshave
havebeen
beenheavheavReport:Addressing
Gender. Kigali: African
Government
of Rwanda.
the health
health impacts from climate change
ily
reliant
on
international
donor
funding
the
change
ily
reliant
on
international
donor
funding
Cook, S. (1998), “Who Gets What Jobs in China’s Countryside?
humanresources,
resources,and
andininthe
theprovision
provisionof
of
from
human
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
A Multinomial Logit Analysis,” Oxford Development Studies, vol.
National Institute of Statistics of Rwanda (2006), Preliminary
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
which the
the continent is ill-equipped
to
and
organizations
such
asasthe
Global
high-quality
which
ill-equipped
to
and
organizations
such
the
Global
26, no. 2, pp. 171-190.
Poverty Update Report. Kigali:
for
example,
can
expand
service
delivery
handle.
Increased
climate
variability
and
Fund.
In
light
of
the
uncertain
condition
for example, can expand service delivery
handle. Increased climate
variability and
Fund. In light of the uncertain condition
Government of Rwanda.
and
ensure
greater
accountability
in
health
the
expected
temperature
warming
will
of
and ensure greater accountability in health
the expected temperature warming will
of the
the global
globaleconomy,
economy,African
Africancountries
countries
Finnoff, K. (2012), “Intimate Partner Violence, Female Employment
services
through
error
reduction,
diagwill
need
to
reevaluate
their
services through error reduction, diagwill need to reevaluate theirrelationships
relationships
and Male Backlash in Rwanda,” Economics
of Peace and Security
National Institute of Statistics of Rwanda (NISR), Ministry of Health
nosticaccuracy
accuracyand
andtreatment.
treatment.1111 ItIt can
can
human aspects,
aspects, mediating
mediating health
nostic
human
health outcomes
outcomes with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
Journal, vol 7. no. 2, pp. 14-24.
(MOH) [Rwanda], ICF International (2012), Rwanda Demographic
also
increase
the
transparency
of
medical
across
the
continent,
through
both
direct
partners
and
possibly
look
more
also increase the transparency of medical
across the continent, through both direct
partners and possibly look moretotoSouth–
South–
and Health Survey 2010. Calverton, Maryland, U.S.A.: NISR,
procurement
and
distribution
operations.
and
indirect
channels.
Climate
change
will
South
and
private–public
partnerships.
procurement and distribution operations.
and indirect channels. Climate change will
South and private–public partnerships.
IFAD (2010), Rwanda: Smallholder Cash and
Export food
Crops
MOH,
and ICF International.
exacerbate
and water
water
insecurity
exacerbate
food and
insecurity and
and
Development
Project
(PDCRE)
Gender
and Youth
in the
and
streamlining
processes,
reducing
waitthreaten
theTea
livelihoods
and
bybystreamlining
processes,
reducing
waitthreaten
the
livelihoods
and health
health of
of many
many domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
Coffee
Value
Chains.
Rome:
IFAD.
Quisumbing,
A. and J.A.
Maluccio
(2003),of“Resources
at marriage
ing
times,
and
improving
the
accuracy
of
African
populations.
Droughts
are
likely
the
involvement
new
international
ing times, and improving the accuracy of
African populations. Droughts are likely
the involvement of new internationalaid
aid
and intra-household
allocation: Evidence from Bangladesh,
to
become
more
prevalent,
both
in
freplayers.
to become more prevalent, both in freplayers.
Labour Office (2000), “Resolution
Concerning
Ethiopia,
Indonesia,
and South Africa,” Oxford Bulletin of
quency
and
severity,
reducing
farm
yields
9International
Ibid.
quency and severity, reducing farm yields
9 Ibid.
10 Ibid. of Employment in the Informal Sector,
by hunger
the
Economics
and
Statistics, vol. 65, no. 3, pp. 283-328.
andAdopted
increasing
and
starvation,
par10Statistics
Ibid.
and increasing hunger and starvation, par11
13 AfDB, A Strategic Framework for Improving
11Fifteenth International Conference of Labour
- Statisticians
13 AfDB, A Strategic Framework for Improving
ticularly in(January
Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
ticularly in Southern Africa and the Sahel
formation and communication technologies (ICT)
Health in Africa (2012); WHO Fact Sheet No. 266,
References
for
health. Examples
treating patients,
conOct. 2012.
1993),”
Current include
International
Recommendations
on Labour
Sommers, M (2012), Stuck:
Rwandan Youth and the Struggle for
for health. Examples include treating patients, conOct. 2012.
ducting research, educating the health workforce,
14 AfDB, A Strategic Framework,” op. cit.
Statistics,
2000
Edition.
International Labour Office.
Adulthood. Studies in 14
Security
International
Affairs
ducting
research,
educating
theGeneva:
health workforce,
AfDB,and
A Strategic
Framework,
” op. cit.Series.
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
15 Ibid.
tracking diseases and monitoring public health.”
12 Economist Intelligence Unit (2011).
15 Ibid.
33
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
AfDB
AfDB
Analysis
Analysisof
ofGender
Genderand
and
Youth
YouthEmployment
Employmentin
inRwanda
Rwanda
AfricanDevelopment
DevelopmentBank
Bank
African
World Bank (2010), Global Monitoring Report
Athens, Georgia, U.S.A.: University of Georgia Press and Institute
rapid
young
will be
be
critical in
in order
order in
in less
less than
than 20
20years.
years.8 8 2010: The MDGs
rapideconomic
economic growth
growth has
has boosted
boosted the
the
young population
population will
critical
Crisis. Washington, D.C.: The World Bank.
of Peace Press.
amount
African subregions
subregionsare
areexpected
expectedtotogrow
grow
to
potentialafter
of the
thethe
youth
bulge African
amountofofresources
resourcesallocated
allocatedto
tohealth
healthinfrainfrato harness
harness the
the potential
of
youth
bulge
structure
and
so-called ‘demographic
‘demographicdivdivthe fastest,
fastest,tripling
triplingtheir
theirpopulations
populationsover
over
structureand
andto
tosurvival-enhancing
survival-enhancing social
social
and capture
capture the
the so-called
the
WorldAfrica
Bank (2009),
Africa Development Indicators 2008/09, Youth
UNCTADIn(2012),
The
Least
Developed
Countries
Report
2012: though,
services.
spite
of
this,
issues
of
governidend.
’
Concurrently
has
an
services. In spite of this, issues of governidend.’ Concurrently though, Africa has an
andpeople
Employment
The and
Potential,
the Problem,
the
Harnessing
Remittances have
and Diaspora Knowledge
to BuildIn 2010,
ance
aging
aged 60
60 in Africa:
youthbulge
bulge
population
agingwill
willexert
exert
anceand
andincome
incomeinequality
inequality havehampered
hampered
aging population.
population. In
2010, people
aged
youth
and population
aging
Promise.
Washington,
D.C.:
The
World
Bank.
Productive Capacities. Geneva: UNCTAD.
or
for just
just 6%
6% of
of Africa’s
Africa’s increasing
increasingpressure
pressureon
onhealth
healthsystems,
systems,highhighor older
older accounted
accounted for
population,
this is
is expected
expected to
to rise
rise to
to lighting
-lightingthe
theneed
needtotoaddress
addressfamily
familyplanning
planning
population, but
but this
World
Bank
(2009b),
Project
Appraisal
Document
forhealthcare,
the Northern
UNESCO
(2008),
International
Literacy
Statistics:
A Review
of50 years
cient,
remains
high,
and
in
2010,
six
of
the
13%
over
the
next
(Figure
1).
Some
services,
maternal
and
child
and
cient, remains high, and in 2010, six of the
(Figure 1). Some
services, maternal and child healthcare, and
Uganda
Social
Action
Fund
(NUSAF)
II
Project.
Washington,
D.C.:
Concepts,
Methodology
and
Current
Data.
Montreal:
UNESCO
10
countries, such as Liberia and Nigeria,
Nigeria, are
are
10most
mostunequal
unequalcountries
countriesworldwide
worldwide were
were
33
The
World
Bank.
Institute
for
Statistics.
inin
Sub-Saharan
Africa.
While
poverty
has
expected
to
double
their
population
size
Sub-Saharan Africa. While poverty has
population size
Ibid.
88 Ibid.
declined
declinedby
by9%
9%over
overthe
the past
past 20
20 years,
years, this
this
World Bank (2007), The 2007 Global Monitoring Report:
World Bank (2012), World Development Report 2013: Jobs.
Washington,
D.C.:
World Bank.
meet
the
goal
of
poverty
meet
theMDG
MDG
goalThe
of halving
halving
poverty by
by
-ulation
ulation(excluding
(excludingNorth
NorthAfrica)
Africa)still
stillsubsists
subsists
on
on$1.25
$1.25or
orless
lessaaday
day (PPP
(PPP adjusted).
adjusted).44 As
As
improvinghealth
healthoutcomes,
outcomes,with
withwomen,
women,
totoimproving
ruraldwellers
dwellersand
andother
othermarginalized
marginalized poppoprural
ulationsbearing
bearingaadisproportionate
disproportionateburden.
burden.
ulations
Overthe
thenext
next50
50years,
years, itit isis projected
projected that
that
Over
thecontinent’s
continent’seconomic
economic growth
growth rate
rate will
will
the
continueatataround
around5-6%
5-6% per
per annum.
annum.55
continue
extentto
towhich
whichthis
this translates
translates into
into better
better
extent
healthoutcomes
outcomesthough
though isis contingent
contingent on
on
health
a
number
of
factors,
including
not
only
the
a number of factors, including not only the
levelofofbudgetary
budgetaryallocations
allocations to
to the
the sector
sector
level
Confronting the Challenges of Gender Equality and Fragile States.
Washington, D.C.: The World Bank.
Figure 1. Africa’s population
population will
will double
doubleininsize
sizeby
by2050
2050
Population size in 2010
2010
bedeployed
deployedto
torespond
respond to
to emerging
emerging chalchalbe
lenges.
Equitable
access
and
treatment
for
lenges. Equitable access and treatment for
thepoorest
poorestsegments
segmentsof
ofsociety
societyisisone
onecritical
critical
the
challenge.
challenge.
Predicted population
Predicted
population size
size in
in 2050
2050
severehealth
healthchallenge.
challenge.African
Africandemogrademograsevere
peopleliving
livingin
inAfrica
Africatoday,
today, and
and itit isis the
the
people
only
continent
that
is
expected
to
double
in
only continent that is expected to double in
6
sizeby
by2020,
2020,to
toreach
reach2.7
2.7billion.
billion.6 What
What is
is
size
more, the majority of this population will
more, the majority of this population will
belong to the youth cohort. Africa is the
belong to the youth cohort. Africa is the
world’s youngest region and is expected
world’s youngest region and is expected
to have the largest workforce in the world
to have the
largest workforce in the world
by 2040.77 Ensuring the good health of this
by 2040. Ensuring the good health of this
3 AfDB, “A Strategic Framework for Improving
3Health
AfDB,
“A Strategic
in Africa”
(2012).Framework for Improving
Health
in Africa”
(2012).
4 WHO,
Atlas of
Health Statistics (2011b).
45 WHO,
Statistics
(2011b).
AfDB,Atlas
AfricaofinHealth
50 Years’
Time (2011a).
56 AfDB, Africa in 50 Years’ Time (2011a).
6Miracle or Malthus?” (2011b).
Miracle
or Malthus?”
7 AfDB,
Africa in 50(2011b).
Years’ Time (2011a).
7 AfDB, Africa in 50 Years’ Time (2011a).
Source: AfDB (2011a).
Source: AfDB (2011a).
34
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
Analysis of Gender and
Analysis of Gender
and
Youth Employment
in Rwanda
Youth Employment in Rwanda
ESTA & RWFO. March 2014
ESTA & RWFO. March 2014
AfDB
AfDB
Appendix 1. Age-sex structure of the population, by rural-urban location, Rwanda, 2005/06 and
2010/11
regions.
Various infectious diseases includ-
regions. Various infectious diseases including malaria, cholera, diarrhea, dengue
ing malaria, cholera, diarrhea, dengue
fever, meningitis, and schistosomiasis are
fever, meningitis, and schistosomiasis are
technology
technology(ICT)
(ICT)revolution
revolutionin
in Africa
Africa
isisrapidly
increasing
connectivity
across
rapidly increasing connectivity across
health
healthsector.
sector.Internet
Internetbroadband
broadband penepenetration
trationhas
hasrisen
risenrapidly,
rapidly,from
from aa meager
meager
0.1%
0.1%ofofthe
thepopulation
populationinin2000
2000to
toan
anestiestimated7%
7%inin2010.
2010.9 9By
By2060,
2060,coverage
coverage isis
mated
projectedtotorise
risedramatically
dramaticallyto
to 99%
99% of
of
projected
theAfrican
Africanpopulation.
population.1010
the
-tionprovides
providesthe
theopportunity
opportunityto
toovercome
overcome
tion
humanresources,
resources,and
andininthe
theprovision
provisionof
of
human
high-qualityhealthcare
healthcareservices.
services.E-Health,
E-Health,
high-quality
forexample,
example,can
canexpand
expandservice
servicedelivery
delivery
for
andensure
ensuregreater
greateraccountability
accountabilityin
inhealth
health
and
services
through
error
reduction,
diagservices through error reduction, diag11
nosticaccuracy
accuracyand
andtreatment.
treatment.11 ItIt can
can
nostic
also
increase
the
transparency
of
medical
also increase the transparency of medical
procurementand
anddistribution
distributionoperations.
operations.
procurement
streamliningprocesses,
processes,reducing
reducingwaitwaitbybystreamlining
ing
times,
and
improving
the
accuracy
of
ing times, and improving the accuracy of
9 Ibid.
9 Ibid.
10 Ibid.
10 Ibid.
11
11
formation and communication technologies (ICT)
formation and communication technologies (ICT)
for health. Examples include treating patients, confor health. Examples include treating patients, conducting research, educating the health workforce,
ducting
research, educating the health workforce,
tracking diseases and monitoring public health.”
tracking diseases and monitoring public health.”
data.
countries
data. At
At present,
present, 80% of African countries
claim
m-health
claim to
to be
be using telemedicine or m-health
(also
known
as
mobile
health),
although
(also known
although
the
still in
in
the majority
majority of these projects are still
their
infancy.
In
this
respect,
scaling
up
their infancy.
scaling up
12
12
opportunity
systems.
opportunity to improve health systems.
The changing
changing environmental land
The
land-scape threatens
threatens to increase poverty
scape
poverty and
and
health problems
problems in Africa. Addressing
health
Addressing
the health
health impacts from climate change
the
change
which the
the continent is ill-equipped
which
ill-equipped to
to
handle.
Increased
climate
variability
and
handle. Increased climate variability and
the expected
expected temperature
temperature warming
the
warming will
will
human aspects,
aspects, mediating
mediating health
human
health outcomes
outcomes
across
the
continent,
through
across the continent, through both
both direct
direct
and
indirect
channels.
Climate
change
and indirect channels. Climate change will
will
exacerbate food
food and
and water
water insecurity
exacerbate
insecurity and
and
threaten the
the livelihoods
livelihoods and
threaten
and health
health of
of many
many
African
populations.
Droughts
are
African populations. Droughts are likely
likely
to become
become more
more prevalent,
prevalent, both
to
both in
in frefrequency
and
severity,
reducing
farm
yields
quency and severity, reducing farm yields
and increasing hunger and starvation, parand increasing hunger and starvation, particularly in Southern Africa and the Sahel
ticularly in Southern Africa and the Sahel
12 Economist Intelligence Unit (2011).
12 Economist Intelligence Unit (2011).
geographical range of vector-borne disgeographical range of vector-borne diseases has been linked with regional warmeases has been linked with regional warming and the consequent altered length of
ing and the consequent altered length of
seasons. Climate change could increase the
seasons. Climate change could increase the
population at risk of malaria in Africa by
population at risk of malaria in Africa by
an additional 170 million by 2030 and the
an additional 170 million by 2030 and the
global population
populationatatrisk
riskofofdengue
denguefever
fever
global
13
Furthermore,
by 22 billion
billionby
bythe
the2080s.
2080s.13 Furthermore,
by
the
rapid
and
unplanned
urbanization
that
the rapid and unplanned urbanization that
happeningon
onthe
thecontinent
continentisisfraught
fraught
isis happening
--cient
or
contaminated
drinking
water,
poor
cient or contaminated drinking water, poor
sanitationand
andsewage
sewagesystems,
systems,industrial
industrial
sanitation
waste, and
andstress
stressassociated
associatedwith
withpoverty
poverty
waste,
1414 Sustainable policies
and
unemployment.
and unemployment. Sustainable policies
forhousehold
householdenergy,
energy,agricultural
agriculturalproducproducfor
tivity,
nutrition,
transportation,
water
and
tivity, nutrition, transportation, water and
sanitation,could
couldhave
haveaalarge
largeand
andpositive
positive
sanitation,
1515
impact
on
the
burden
of
diseases.
impact on the burden of diseases.
are likely
likely to
todecline.
decline.Foreign
Foreignaid
aidfrom
from
are
traditionalinternational
internationaldonors
donorstotodeveldeveltraditional
oping
opingcountries
countriesisisdeclining
decliningand
andwill
willlikely
likely
play
play aa reduced
reducedrole
roleininAfrican
Africandevelopdevelopment
ment over
overthe
thenext
next50
50years.
years.InInthe
thepast,
past,
African
Africanhealthcare
healthcaresystems
systemshave
havebeen
beenheavheavily
ilyreliant
relianton
oninternational
internationaldonor
donorfunding
funding
from
from development
developmentbanks,
banks,UN
UNagencies,
agencies,
and
and organizations
organizations such
such asasthe
theGlobal
Global
Fund.
In
light
of
the
uncertain
condition
Fund. In light of the uncertain condition
of
of the
the global
globaleconomy,
economy,African
Africancountries
countries
will
need
to
reevaluate
their
will need to reevaluate theirrelationships
relationships
with
withinternational
internationalaid
aidagencies
agenciesand
andbilateral
bilateral
partners
and
possibly
look
more
partners and possibly look moretotoSouth–
South–
South
and
private–public
partnerships.
South and private–public partnerships.
domestic
domesticownership
ownershipofofhealth
healthsystems
systemsand
and
the
involvement
of
new
international
the involvement of new internationalaid
aid
players.
players.
13 AfDB, A Strategic Framework for Improving
13 AfDB, A Strategic Framework for Improving
Health in Africa (2012); WHO Fact Sheet No. 266,
Health in Africa (2012); WHO Fact Sheet No. 266,
Oct. 2012.
Oct. 2012.
14 AfDB, A Strategic Framework,” op. cit.
14 AfDB, A Strategic Framework,” op. cit.
15 Ibid.
15 Ibid.
35
A f r i c a n
A f r i c a n
D e v e l o p m e n t
D e v e l o p m e n t
B a n k
B a n k
50 ANS AU SERVICE DE L’AFRIQUE
50 YEARS SERVING AFRICA
African Development Bank Group
Statistics Department
Temporary Relocation Agency
BP 323, 1002 Tunis, Belvédère
Tunis, Tunisia/Tunisie
Tel.: (216) 71 10 36 54
Fax: (216) 71 10 37 43
E-mail: [email protected];
www.afdb.org