EFA GlobalMonitoring Report 2 0 1 2

YOUTH AND SKILLSPutting education to work

United Nations���������� �������� ��

Cultural Organization

UNESCO Publishing

YOUTH AND SKILLSPutting education to work

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For more information about the Report, please contact:

Previous EFA Global Monitoring Reports

ED -2012 / WS / 13

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Notes: The offi cial age for pre-primary education is 3 to 5 in the three countries. In Nigeria, the poorest 40% are shown for urban areas.Source: EFA Global Monitoring Report team calculations (2012) based on Multiple Indicators Cluster Survey data.

0

20

40

60

80

100

Atte

ndan

ce ra

te (%

)

UrbanRural

Poorest 20%

Richest 20%BangladeshRural

Urban

Urban

Urban

Poorest 20%

Richest 20%

Nigeria

Rural

RuralPoorest 20%

Richest 20%

Thailand

Urban

Urban

Urban

Urban Rural

Rural

Rural

Rural

Male

Female

Bangladesh, 2006 Nigeria, 2007 Thailand, 2006

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Num

ber o

f out

-of-s

choo

l chi

ldre

n (m

illio

ns)

0

20

40

60

80

100

120

201020092008200720062005200420032002200120001999

13

17

61

31

108 million

25 million

40 million

42 million

Rest of the world

Sub-Saharan Africa

South and West Asia

14

18

61

29

19

19

74

35

Sources: Annex Statistical Table 5; UIS database.

Number of out-of-school children of primary school age, 1999–2010

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Notes: The size of the bubble is proportional to the number of out-of-school children. The numbers in the bubbles show the number of out-of-school children. The 2001 fi gures for Nigeria are from 2000. The 2010 fi gures for India are from 2008.Source: UIS database.

0

20

10

30

40

50

60

India

Pakistan

Ethiopia

Nigeria

2010200720042001

Out-o

f-sch

ool c

hild

ren

(%)

20.3

5.0

6.9

8.7

8.4

6.6

6.1

5.9

3.2

2.4

5.1

7.5

10.5

4.9

2.3

7.1

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0

20

40

60

80

100

Mal

i

Chad

Gam

bia

Tim

or-L

este

Guin

ea-B

issa

u

Paki

stan

Bang

lade

sh

Nep

al

Côte

d'Iv

oire

C. A

. R.

Mau

ritan

ia

Togo

Papu

a N

. Gui

nea

Ghan

a

Buru

ndi

Suda

n

Mal

awi

Rwan

da

D. R

. Con

go

Cam

bodi

a

Ango

la

Zam

bia

Com

oros

Mad

agas

car

Iraq

Saud

i Ara

bia

Jam

aica

Hond

uras

Swaz

iland

Keny

a

Mau

ritiu

s

S.To

me/

Prin

cipe

Nam

ibia

Leso

tho

Braz

il

Bahr

ain

Boliv

ia, P

. S.

Equa

t. Gu

inea

Mal

aysi

a

Mya

nmar

Adul

t illi

tera

cy ra

te (%

)

1998–2001

Target

In Madagascar, the adult illiteracy rate isprojected to increase from 29% to 35% andin the D. R. Congo from 33% to 34%.

In Chad, the adult illiteracy rate was 74% in 2000...

...and is projected to fall to 61% by 2015...

...well above the target level of 37%.

2015 (projection)

Adult illiteracy rate

Note: The countries shown in the figure are those for which a projection to 2015 was feasible and that had an adult illiteracy rate above 10% in 1998–2001. Sources: Annex, Statistical Table 2; UIS database.

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Source: EFA Global Monitoring Report team analysis (2012) based on Demographic and Health Survey data.

Lite

racy

sta

tus

(%)

Literate

Semi-literate

Illiterate

0

20

40

60

80

100

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Fem

ale

Mal

e

Nigeria Ghana Zambia India Kenya Timor-Leste Cambodia U. R. Tanzania Haiti Nepal

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Notes: Only countries with data for 1990, 2000 and 2010 are plotted. If there was no information for a particular year, information was substituted up to two years before or after. Afghanistan and Oman are excluded because they experienced negative trends.Source: UIS database.

0.40 0.50 0.60 0.70 0.80 0.90 1.00 1.10

C. A. R.

Chad

Pakistan

Côte d'Ivoire

Niger

Guinea

Cameroon

D. R. Congo

Benin

Mali

Papua N. Guinea

Togo

Djibouti

Mozambique

Nigeria

Ethiopia

Comoros

Burkina Faso

Lao PDR

Sierra Leone

Guinea-Bissau

Algeria

Morocco

Cambodia

Guatemala

Egypt

Tunisia

Burundi

Ghana

India

Iran, Isl. Rep.

Uganda

Gambia

Malawi

Mauritania

Senegal

Gender parity index

Gender parity

1990–2000 2000–2010 Below 0.90 represents severe gender disparity.

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0 20 40 60 80 100

Shanghai, China Finland

Rep. of Korea Hong Kong, China

Singapore Macao, China

Canada Estonia

Japan Chinese Taipei

Switzerland Netherlands

New Zealand Australia

Iceland Denmark Norway

Germany Belgium

Poland United Kingdom

Slovenia Ireland

Slovakia Sweden

Latvia Czech Republic

France Hungary

United States Portugal Austria

Luxembourg Spain

Italy Lithuania

Russian Federation Greece Croatia

Malta Israel

Serbia Turkey

Bulgaria Uruguay Romania

Mauritius Mexico

Chile United Arab Emirates

Trinidad and Tobago Thailand

Costa Rica Miranda, Venezuela, B. R.

Montenegro Kazakhstan

Malaysia Rep. of Moldova

Argentina Jordan

Albania Brazil

Georgia Colombia

Qatar Peru

Tunisia Indonesia

Panama Tamil Nadu, India

Kyrgyzstan

15-year-olds scoring at or above level 2 in mathematics (%)

Poor girls Poor boys

Rich girls Rich boys

Notes: Of countries and economies that participated in the 2009 PISA, Azerbaijan, Himachal Pradesh (India) and Liechtenstein are not included. Poor/Rich refers to the bottom/top quartile in the PISA economic, social and cultural status index. Sources: Altinok (2012b), based on 2009 PISA data; Walker (2011).

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Egypt, 2008

Jordan, 2009

Pakistan, 2007

India, 2005

Nepal, 2011

Bangladesh, 2007

Maldives, 2009

Niger, 2006

Poorest100% 0%

Richest

Mali, 2006

Sierra Leone, 2008

Benin, 2006

Guinea, 2005

Madagascar, 2009

Ethiopia, 2011

Ghana, 2008

Nigeria, 2008

Côte d'Ivoire, 2005

Liberia, 2007

Senegal, 2010

U. R. Tanzania, 2010

Malawi, 2010

D. R. Congo, 2007

Uganda, 2006

Zambia, 2007

Rwanda, 2010

Lesotho, 2009

Swaziland, 2006

Congo, 2009

Kenya, 2009

Namibia, 2007

Sao Tome and Principe, 2009

Zimbabwe, 2010

National average

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Poorest Richest

Female Male

Female Male

Niger

EgyptPoorest Richest

Female Male

Female Male

PakistanRichestPoorest

Female Male

MaleFemale

National average100% 0%

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Note: * indicates that a country-specifi c share of aid on budget was estimated from country documents; for the other countries, an average of 60% of aid was assumed.Source: UNESCO (2012b).

Sub-Saharan AfricaSwaziland

AngolaCôte d'Ivoire

* KenyaCameroon

Lesotho* Ghana

ChadTogo

SenegalCape Verde

EthiopiaBenin

D. R. CongoNiger

UgandaMadagascar

GambiaMalawiBurundi

MaliBurkina Faso

Guinea* Rwanda

Eritrea* Mozambique

Zambia

Government and donor education spending (%)

0 20 40 60 80 100

In Mali, aid accounted for 25% of the total education budget over the period 2004–2010.

Source: OECD-DAC (2012b).

Total aid to secondary education

0

2

4

6

8

10

12

14

2002 2009200820072006200520042003 2010

Cons

tant

201

0 US

$ bi

llion

s

Total aid to post-secondary education

Total aid to basic education

0

2

4

6

8

10

12

14

6.9

3.11.0

2.8

8.3

4.1

1.1

3.1

8.6

4.0

1.3

3.4

9.6

4.4

1.2

4.0

10.6

4.8

1.6

4.3

11.6

5.0

1.8

4.8

11.5

4.7

1.9

4.9

13.4

5.3

2.4

5.8

13.5

5.3

2.3

5.8

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Note: Maximizing natural resource revenue is assumed to take place in two steps: (i) an increase in the share of revenue from natural resource exports to 30% for minerals and to 75% for oil; and (ii) the allocation of 20% of this additional revenue to education.Source: EFA Global Monitoring Report team calculations (2012) based on UIS database and IMF Article IV reviews.

US$

billi

ons

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

Burkina Faso

+23%

+49% +42%

+10%

+98%

Lao PDR Niger U. R. Tanzania Uganda

Potential extra funding from natural resource revenue

Total education budget in 2010

In the Niger, extra funding could increase the education budget by 42%.

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Notes: Around two-thirds of the US$15 million annual average from the William and Flora Hewlett Foundation originally came from the Bill & Melinda Gates Foundation. In most cases, the amount of support to education in developing countries had to be estimated using aggregate data from foundations.Sources: Annex, Aid Table 2; Carnegie Corporation of New York (2011); Ford Foundation (2011); MasterCard Foundation (2010); William and Flora Hewlett Foundation (2010); van Fleet (2012).

$61m $13m$21m $15m

United Kingdom United States Netherlands

Switzerland New Zealand Finland Luxembourg

$911m $888m$567m

$61m $59m $52m $36mOpen Society Foundations

FordFoundation

MasterCard Foundation

Williamand Flora Hewlett

Foundation

$9m

CarnegieCorporation of New York

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Pathways to Skills

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Source: UIS (2012a).

10 20 30 40 50 60 70 80 90 1000

Ukraine 2007Kazakhstan 2006

Armenia 2005Kyrgyzstan 2006

Albania 2009Rep. Moldova 2005

Azerbaijan 2006Colombia 2010

Bolivia 2008Maldives 2009Tajikistan 2005

Guyana 2009Brazil 2006

Dominican Rep. 2007Egypt 2008

Indonesia 2007Philippines 2003

Kenya 2009Zimbabwe 2006

Turkey 2004Ghana 2008

Timor-Leste 2010Namibia 2007

India 2006Nigeria 2008

Belize 2006Nepal 2006

Swaziland 2007Congo 2005

D. R. Congo 2010Syrian A. R. 2006Bangladesh 2006

Zambia 2007Cameroon 2006

Pakistan 2007Lesotho 2010

Togo 2006S. Tome/Principe 2009

Cambodia 2010Malawi 2010

Sierra Leone 2008Morocco 2004

Benin 2006Haiti 2006

Mauritania 2007Côte d’Ivoire 2006

U. R. Tanzania 2010Madagascar 2009

Liberia 2007Guinea 2005

Uganda 2006Mali 2006

Ethiopia 2005Senegal 2005C. A. R. 2006

Burkina Faso 2006Mozambique 2003

Niger 2006Rwanda 2005

Youth aged 15 to 19 (%)

No education Dropped out (primary) In primary Dropped out (lower secondary)

In lower secondary Dropped out (upper secondary) In upper secondary or higher

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Note: This fi gure shows only direct aid to education; it excludes aid to education from general budget support.Source: OECD-DAC (2012).

All donors Germany France Japan Canada

US$103m

US$392m

US$79mUS$172m

US$887mUS$923m

US$1 071m

US$2 039m

Shar

e of

disb

urse

men

ts to

dire

ct e

duca

tion

(%)

100

90

80

70

60

50

40

30

20

10

0

ScholarshipsImputed student costsPost-secondarySecondaryBasic Unspecifi ed

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Notes: The rate of progression to upper secondary school is a proxy indicator for progression from lower secondary to upper secondary. It is measured by the proportion of upper secondary to lower secondary gross enrolment ratios. In an ideal system where all lower secondary students continue to upper secondary, the ratio equals 1. Honduras has a lower secondary gross enrolment ratio of 75% and an upper secondary gross enrolment ratio of 71%. The rate of progression is calculated to be 95%, indicating that most of those who have the chance to go to lower secondary are likely to continue to upper secondary. In Egypt, the gross enrolment ratio at lower secondary level is 94%. With a gross enrolment ratio of 51% at the upper secondary level, Egypt’s progression rate from lower to upper secondary is estimated to be about 0.54 (51/94). This suggests that, while most young people have the opportunity to participate in lower secondary education, only around half are able to continue to upper secondary. Source: Annex, Statistical Table 7.

Prog

ress

ion

from

low

er to

upp

er s

econ

dary

enr

olm

ent (

%)

100

90

80

70

60

50

40

30

20

10

010 20 30 40 50 60 70 80 90 100

Lower secondary gross enrolment ratio (%)

Niger

EthiopiaUganda

C. A. R.

PakistanYemen

Nigeria

Mauritania

Swaziland

India

Egypt

Kenya

Syrian A. R.

Ghana

Algeria

Mexico

TunisiaTajikistan

Turkey

Netherlands

United Kingdom

United States

Rep. of Korea

China

Venezuela, B.R.

Bolivia P.S.Ecuador

HondurasRussian Fed.

Group 1:Very low enrolment

Group 3:Medium enrolment,

good progression

Group 2:Medium enrolment,

poor progression

110 120 130 140

Group 4:High enrolment, poor progression

Group 5:High enrolment, good progression

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Rural poorest are at a greater disadvantage than urban poorest

Urban poorest are at a greater disadvantage than rural poorest

Yout

h po

pula

tion

(%)

Rep.

Mol

dova

Tajik

ista

n

Alba

nia

Moz

ambi

que

Azer

baija

n

Egyp

t

Nam

ibia

Bang

lade

sh

Nep

al

Mal

awi

Cam

bodi

a

Syria

n A.

R.

Mau

ritan

ia

Tim

or-L

este

Rwan

da

Sene

gal

Ugan

da

Mor

occo

C. A

. R.

Côte

d’Iv

oire

Libe

ria

Haiti

U. R

. Tan

zani

a

Mad

agas

car

Mal

i

Sier

ra L

eone

S. To

me/

Prin

cipe

Beni

n

Leso

tho

Cam

eroo

n

Paki

stan

Togo

Beliz

e

D. R

. Con

go

Nig

eria

Cong

o

Turk

ey

Ghan

a

Phili

ppin

es

Indo

nesi

a

Braz

il

Guya

na

Colo

mbi

a

Dom

inic

an R

ep.

Rural poorest 40%

Urban poorest 40%Urban richest 20%

0

20

40

60

80

100

Boliv

ia, P

. S.

Source: UIS (2012a).

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Yout

h ag

ed 1

5 to

24

(%)

100

80

60

40

20

0

Females are at a disadvantage Gender parity

Rural male Rural female

Nige

rBu

rkin

a Fa

soM

ozam

biqu

eC.

A. R

.Se

nega

l

Mor

occo

Guin

ea

Mal

iEt

hiop

iaSi

erra

Leon

eCô

te d

’Ivoi

reBe

nin

Liber

ia

Cam

eroo

nUg

anda

U. R

. Tan

zani

aTo

goD.

R. C

ongo

Zam

bia

Pakis

tan

Mal

awi

Cam

bodi

aCo

ngo

Mau

ritan

iaTu

rkey

Nepa

lSy

rian

A. R

.Ni

geria

Ghan

aZi

mba

bwe

Boliv

ia P.

S.Ke

nya

Egyp

tTa

jikist

anAz

erba

ijan

Rwan

da

Mad

agas

car

Haiti

San

Tom

e/Pr

incip

eBa

ngla

desh

Swaz

iland

Timor

-Les

teIn

done

siaAl

bani

aKy

rgyz

stan

Arm

enia

Ukra

ine

Kaza

khst

an

Source: UIS (2012a).

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Males are at a disadvantage

Leso

tho

Beliz

eNa

mib

iaBr

azil

Phili

ppin

esDo

min

ican

Rep.

Colo

mbi

aM

aldi

ves

Guya

naM

oldo

va

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YOUTH AND SKILLSPutting education to work

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