The State of Education Series
March 2013

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This presentation includes analysis of gender/income/location disparities in:
Net Enrollment Rates (NER) for primary and secondary
Net Attendance Rates (NAR) for primary and secondary
Out of School Children (OOS)
Repetition Rates
Primary/Secondary Completion Rates
Learning Outcomes
Gross Enrollment/Attendance Rates (GER/GAR) for tertiary
Youth and Adult Literacy Rates

Acronym Name
EAP
ECA
LAC
MNA
SAS
SSA
WLD
GER
NER
OOS
NAR
GAR
GPI
East Asia and Pacific
Europe and Central Asia
Latin American and the Caribbean
Middle East and North Africa
South Asia
Sub-Saharan Africa
World (Global Aggregate)
Gross Enrollment Rate
Net Enrollment Rate
Out of School
Net Attendance Rate
Gross Attendance Ratio
Gender Parity Index (female value/male value)

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Gender parity indices
(GPIs) are calculated by dividing the female value for an indicator by the male value, so perfect gender parity equals 1 .
A value below 1 indicates a bias toward males. A value above 1 indicates a bias toward females.
Globally, the GPI has been increasing from .98 in 2000 to perfect gender parity (1.0) in 2010.
Most regions are very close to gender parity (+/-
0.02) in 2010. Only MNA lags behind.
4 of 6 regions have a slight female bias.
1,05
Gender parity in pre-primary enrolments (1.0) has been achieved globally and in most regions.
Female Bias
1,00
0,99
1,00
0,99
0,99
0,99
0,98
Male Bias
0,95
0,90
0,85
0,80
0,75
WLD
2000
EAP
2002
ECA
2004
LAC
2006
MNA
2008
SAS
2010
SSA
Source: UNESCO Institute for Statistics in EdStats, November 2012

% of 3 to 4 year olds attending any type of pre –primary education program
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

% of 3 to 4 year olds attending any type of pre
–primary education program
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

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More Females are Out of Primary School than Males
120
In 1999, there were almost 62 million females out-of-school compared to 45.5 million males. 58% of the world’s out-ofschool children were female.
In 2010, around 32 million girls were out of school compared to
28.6 million boys.
52.5% of out-of-school children were female.
The gap between male and female totals decreased from 16.5 million to 3.6 million between 1999 and
2010.
100
80
60
40
20
0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Males Out-of-School Females Out-of-School
Source: UNESCO Institute for Statistics in EdStats, September 2012

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Over half of the world’s out of school girls are in SSA, and just under 1/4 are in
South Asia.
South Asia has decreased its total number of females out-of-school by 17.7 million since 1999.
The region’s total dropped from 25 million to 7 million.
SSA has also decreased its total from 24.3 million in
1999 to 17.5 million in
2010.
3 out of every 4 Out-of-School Girls are in either Sub-Saharan Africa or South Asia
40
35
30
25
20
15
10
5
65
60
55
50
45
0
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
LAC ECA MNA EAP SAS SSA
Source: UNESCO Institute for Statistics in EdStats, October 2012

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Around half of the world’s out-of-school females live in these 10 countries.
36% of the world’s out-ofschool females live in the
Top 4 countries.
Nigeria, Pakistan, and
India all have more ourof-school females that the sum of all females out-ofschool in LAC and ECA.
Half of the countries are in SSA and three are in
South Asia.
10 Countries with the Most Female
Out-of School Children
(2008-2011)
1 Nigeria
2 Pakistan
5,487,901
3,241,203
3 India
4 Ethiopia
5 Cote d'Ivoire
1,407,495
1,367,141
663,809
6 Philippines
7 Bangladesh
8 Niger
9 Yemen, Rep.
661,551
591,325
568,884
567,702
10 Burkina Faso 530,731
Source: UNESCO Institute for Statistics in EdStats, October, 2012;
Notes: Data displayed is the most current year available; Orange is
2008;Blue is 2009; Blue is 2010; Black is 2011; Data were not available for
61 of 213 countries.

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In all regions, more low income students are
OOS than high income students. SAS has the largest income disparity at 29 percentage points difference between the top and bottom quintiles.
SSA follows closely behind with 24 points.
A higher % of boys are
OOS in EAP, ECA, and
LAC, but a higher % of girls are OOS in SAS and SSA.
In all regions except for
ECA, a higher % of rural students are OOS. This disparity is highest in
SSA at 15 percentage points.
2
Low income is the greatest source of disparity in percentages of OOS children across regions.
-8
-10
-12
-14
-16
2
0
-2
-4
-6
-18
-20
-22
-24
-26
-28
-30
Gender disparity
Location disparity
Income disparity
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007

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Gender parity indices
(GPIs) are calculated by dividing the female value for an indicator by the male value, so perfect gender parity equals 1 .
A value below 1 indicates a bias toward males. A value above 1 indicates a bias toward females.
Globally, the GPI has been increasing from .93 in 1999 to .98 in 2010.
Most regions are very close to gender parity (+/-
0.03). Only MNA and
SSA lag behind.
EAP, ECA, and LAC have achieved gender parity in primary (+/- 0.02).
All regions except MNA and SSA are within 0.03 of gender parity in primary enrollments.
1,02
Female Bias
1,00
0,98
0,98
0,98
0,97
0,97 0,97
0,96
0,96
0,97
0,94
0,92
0,93
0,93
0,94 0,94
Male Bias
0,90
0,88
0,86
0,84
0,82
0,80
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
WLD EAP ECA LAC MNA SAS SSA
Source: UNESCO Institute for Statistics in EdStats, November 2012

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Half of countries with data have already achieved gender parity
(+/- .02).
78% of countries with data are within 0.05 of gender parity.
Many more countries have a bias toward males in primary enrolments (GPI<1).
Afghanistan has the largest male bias at .69 followed by Central
African Rep. and Chad at .73.
San Marino has the highest female bias at
1.134.
78% of countries are within 0.05 of gender parity in primary enrollments.
1,15
1,10
1,05
1,00
0,95
0,90
0,85
0,80
0,75
0,70
0,65
Male Bias
Female
Bias
Source: UNESCO Institute for Statistics in EdStats, September, 2012
Note: Data points are the most recent year with data available (2008-
2011)

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The male primary gross enrolment rate in these countries is much higher than the female gross enrolment rate.
7 of 10 countries are in SSA. 2 are in
South Asia and 1 is in MNA.
Of the 20 countries with the lowest GPIs
(GPI<0.9),14 are in
SSA, 2 are in SAS, 2 are in EAP (Togo and
PNG), and 1 is in
LAC (Dominican
Republic).
10 Countries with the Largest Gender
Disparities in Primary Enrollment Rates
(2008-2011)
1 Afghanistan
2 Central African Republic
3 Chad
0.694
0.725
0.729
4 Angola
5 Yemen, Rep.
6 Pakistan
7 Cote d'Ivoire
8 Niger
0.813
0.817
0.818
0.833
0.837
9 Guinea 0.838
10 Eritrea 0.838
Source: UNESCO Institute for Statistics in EdStats, September 2012;
Notes: Data is GPI for Primary Gross Enrolment Rate; Black figures are 2011 data;
Blue=2010; Data were not available for 71 of 214 countries.

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These countries have moved from 0.14 to
0.25 percentage points closer to gender parity (1) between 2000/2001 and the most recent data year.
6 of the 10 countries are in SSA; 2 are in
MNA and 2 in South
Asia.
Senegal now has higher female enrollment rates than male enrollment rates
(1.06).
Burundi and India have reached gender parity.
10 Countries with the Most Improvement
Toward Gender Parity in Primary
Enrollments
Percentage
Points
Improved
2000 or
2001
GPI
Most current
GPI
%
Improved
1 Sierra Leone
2 Ethiopia
3 Burkina Faso
4 Benin
5 Yemen, Rep.
0.25
0.67
0.93
37.53
0.22
0.69
0.91
32.73
0.20
0.73
0.93
27.50
0.20
0.67
0.87
29.66
0.19
0.63
0.82
30.55
6 Burundi
7 Senegal
8 India
9 Pakistan
0.19
0.80
0.99
23.64
0.17
0.89
1.06
19.31
0.15
0.85
1.00
17.61
0.15
0.67
0.82
21.79
10 Djibouti 0.14
0.76
0.90
18.84
Source: UNESCO Institute for Statistics in EdStats, Sept. 2012;
Notes: Most current GPI is the most recent data point for 2008-2011;
Data were not available for 54 of 213 countries .

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EAP, ECA, LAC, and
MNA do not have large disparities in primary net attendance rates (NAR) between genders, rural/urban locations, or top/bottom income quintiles.
The largest disparities in most regions are associated with income.
In SSA and SAS, there is a 20 percentage point difference between the top/bottom income quintiles.
Rural students in SSA also have NARs that are
12 percentage points lower than urban students.
2
Gender, income and location disparities are small in all regions except except SAS and SSA.
20
18
Gender disparity
Location disparity
Income disparity
16
4
2
0
8
6
14
12
10
-2
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007

Percentage of 7 to16 year olds who has never been to school.
Percentage of the population in the official age range of lower secondary education not in school
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

Do income disparities exist in educational access in SAS and EAP?
South Asia (SAS)
Percentage of 7 to16 year olds who has never been to school.
East Asia and the Pacific (EAP)
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

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Males repeat more than females in all regions except ECA.
Globally, there is less than half a percentage point difference between male/female repetition rates. Males repeat slightly more than females.
Males also repeat more than females in all regions except for
ECA.
The greatest gender disparity is in MNA at
2.5 percentage points.
In SSA, there is almost no difference in repetition rates between males and females.
10
9
8
7
6
5
4
3
2
1
0
Male Female
EAP ECA LAC MNA SAS SSA WLD
Source: UNESCO Institute for Statistics in EdStats, March 2013
Notes: SAS data is 2009; All other data is for 2011.

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Globally, more males are completing primary school than females.
The difference between male/female PCRs has shrunk from 6 percentage points in
1999 to 1.8 in 2011.
In most regions, more males complete primary than females, but in
LAC and EAP, the reverse is true.
EAP's female PCR was
2.4 percentage points higher than the male
PCR. LAC’s was 0.7 percentage points higher for females.
(continued on next slide)
105
Globally and in most regions, more males complete primary school than females.
Male Female
100
95
90
85
80
75
70
65
60
EAP ECA LAC MNA SAS SSA WLD
Source: UNESCO Institute for Statistics in EdStats, March 2013
Note: All data are for 2011 except EAP and SAS (2010).

(continued)
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SSA has the largest gender disparity in
PCRs with 74% of boys completing vs. 67% of girls in 2011.
MNA also has a large gender disparity at 6 percentage points difference between the genders.
SAS had a large gender disparity in 1999 (15 percentage points) but decreased the difference to 2.7 percentage points in
2010.
105
Globally and in most regions, more males complete primary school than females.
Male Female
100
95
90
85
80
75
70
65
60
EAP ECA LAC MNA SAS SSA WLD
Source: UNESCO Institute for Statistics in EdStats, March 2013
Note: All data are for 2011 except EAP and SAS (2010).

(2006-2012)
Source: UNESCO Institute for Statistics in EdStats, 2013
Note: Data displayed is for the most recent available year
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.

(2006-2012)
Male
Bias
Gender
Parity
Female
Bias
Source: UNESCO Institute for Statistics in EdStats, 2013
Note: Data displayed is for the most recent available year
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.

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Gender disparities exist in all regions in PCRs, but they are surpassed by income disparities in all regions except for
ECA.
The greatest disparities exist in SSA, where there is a 55 percentage point difference between the PCRs of top and bottom quintile students.
This compares to a 33 point difference between urban and rural, and 9 point between genders.
In EAP and ECA, more rural students complete primary school than urban students.
2
Low income is the greatest source of disparity in primary completion rates in all regions except ECA.
60
55
50
Gender disparity
Location disparity
Income disparity
30
25
20
15
10
45
40
35
5
0
-5
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007

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El Salvador, Nicaragua,
Costa Rica, Peru,
Guatemala, and
Colombia are within 5 percentage points of gender parity. Female scores are higher than male scores in these countries.
Uruguay has the largest difference between male/female reading scores with a 19.6 percentage point male bias.
Panama (15.9), Brazil
(15.7), Cuba (15.2), and the Dominican Rep.
(15.1) also have large male biases.
Difference between Male/Female Mean Scores on the 6 th Grade Reading Assessment (2006)
Source: Latin American Laboratory for Assessment of the Quality of
Education (LLECE SERCE) in StatPlanet, August 2011

th
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In all countries, mean scores for rural students are lower than for urban students.
The greatest location disparity is in Peru (79) followed by Mexico (58).
Cuba has the smallest disparity between rural/urban areas (13) followed by Nicaragua
(21).
The scale of disparity between urban/rural scores is much higher than the disparity between male/female scores.
Difference between Urban/Rural Mean Scores on the 6 th Grade Reading Assessment (2006)
Source: Latin American Laboratory for Assessment of the Quality of
Education (LLECE SERCE) in StatPlanet, August 2011

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In all SACMEQ countries, students from the lowest income quintile have lower reading scores than students in the highest income quintile, but the scale of income disparity varies greatly.
South Africa has the largest disparity between richest and poorest followed by
Namibia.
Lesotho, Mozambique, and Malawi seem to have the less of a disparity between income groups in reading scores.
Poorer students have lower mean reading scores in all Anglophone African countries.
625
600
575
550
525
500
475
450
425
400
Richest quintile of students
Average score
Poorest quintile of students
Source: Filmer using Southern and Eastern Africa Consortium for
Monitoring Educational Quality (SACMEQ) 2000 database

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Tanzania, Seychelles, and Mauritius had the highest reading scores in
2007.
Mauritius and Tanzania both improved their scores, but Seychelles’ score was lower than in
2000.
Some countries have large disparities between genders, but in these cases, females have higher scores than males (Seychelles,
Mauritius and
Botswana).
Malawi and Zambia have had the lowest scores over time.
500
480
460
440
420
580
560
540
520
620
Mean reading scores of 6 th grade students vary greatly between Anglophone African countries.
600
2000 Total Male 2007 Female 2007 Total 2007
Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality
(SACMEQ) in EdStats, August 2011; Note: Zimbabwe 2000 is 1995 figure.

Gender disparities in secondary enrollments vary greatly across regions.
1,10
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Globally, the gender parity index (GPI) for secondary net enrollment rate (NER) has been increasing from
0.92 in 2000 to 0.96 in
2010.
ECA is the only region within +/- 0.05 of gender parity (1.0).
LAC has consistently had higher female NERs.
EAP has reversed from a male bias (0.96) in 2000 to a female bias (1.06) in
2010.
SAS has greatly decreased gender disparity over time.
SSA has maintained a male bias 0.80 since 2000.
1,05
1,00
0,95
0,90
0,92
0,85
0,80
0,94
0,95
0,96
Female Bias
Male Bias
0,96 0,96
0,75
WLD
2000
EAP
2002
ECA
2004
LAC
2006
MNA
2008
SAS
2010
SSA
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012; No data available for SSA and MNA for 2010. SSA 2008 data is from 2007.

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Just over half (52%) of countries with data are within 0.05 of gender parity in secondary enrollments.
Unlike primary enrollments, more countries have a female bias in secondary enrolments. 85 countries have GPIs higher than 1 while 71 countries have GPIs less than 1.
6 countries have perfect gender parity
(1.0): Slovenia,
Mauritius, Swaziland,
Japan, Indonesia, and
Cyprus.
More countries have higher female secondary GERs than male secondary GERs.
1,40
1,30
1,20
1,10
1,00
0,90
0,80
0,70
0,60
0,50
0,40
Male Bias
Female Bias
Source: UNESCO Institute for Statistics in EdStats, October 2012:
Data points are the most recent year with data available (2008-2011)

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In 9 of 10 countries, the male GER is much higher than the female GER.
In Lesotho – the female GER is higher than the male rate.
8 of 10 countries are in SSA. 1 is in
South Asia and 1 is in MNA.
Of the 20 countries with the greatest gender disparity, 5 have a female bias.
14 of the top 20 are in SSA.
10 Countries with the Largest Gender
Disparities in Secondary Enrolments
(2008-2011)
GPI
Absolute value from 1
1 Chad
2 Afghanistan
3 Central African Republic
4 Congo, Dem. Rep.
5 Guinea
6 Lesotho
7 Yemen, Rep.
0.42
0.51
0.55
0.58
0.59
1.38
0.62
0.58
0.49
0.45
0.42
0.41
0.38
0.38
8 Niger
9 Angola
0.66
0.69
0.34
0.31
10 Mali 0.71
0.29
Source: UNESCO Institute for Statistics in EdStats, October 2012; Notes: Data are 2010
GPIs for Secondary Gross Enrolment Rates except Guinea (2009), CAR (2011), and Mali
(2011); Data were not available for 52 of 213 countries.

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These countries have moved from 0.19 to
0.34 percentage points closer to gender parity (1) over time.
Sweden and St. Lucia improved from a large female bias (1.26) toward gender parity.
The other countries have improved from a male bias (0.40 to
0.85) toward gender parity.
3 of 10 countries are within 0.05 of gender parity in the most recent year.
10 Countries with the Most
Improvement Toward Gender
Parity in Secondary Enrollments
Percentage
Points
Improved
2000/
2001
GPI
Most current
GPI
1 Cambodia
2 Sweden
3 St. Lucia
4 Mozambique
5 Senegal
0.34
0.27
0.27
0.23
0.21
0.57
0.90
1.26
0.99
1.26
0.99
0.64
0.87
0.66
0.88
6 Yemen, Rep.
7 India
8 Bhutan
0.21
0.20
0.19
0.41
0.62
0.72
0.92
0.85
1.04
9 Guinea 0.19
0.40
0.59
10 Turkey 0.19
0.73
0.91
Source: UNESCO Institute for Statistics in EdStats, October. 2012;
Notes: Most current GPI data for most countries is from 2010;
Guinea and Turkey are 2009; Mozambique data is 2011.

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Large gender disparities in secondary attendance rates do not exist in any region except SAS. In
LAC, ECA, and MNA, slightly more females attend secondary than males.
Rural/urban location disparities exist in most regions. In LAC and
SSA, location disparities are 20/23 percentage points.
The largest disparities in all regions are associated with income:
There is a 35+ percentage point difference between the top/bottom quintiles in
LAC, SAS, and SSA.
2
40
The largest disparities in net secondary attendance rates are associated with income.
35
Gender disparity
Location disparity
Income disparity
30
25
20
15
10
5
0
-5
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007

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Low income is the greatest source of disparity in secondary completion rates in all regions. The disparity is greatest in SAS (60 percentage points), LAC
(44), and SSA (40).
Rural residence is a source of disparity in
SAS (29 percentage point disparity), LAC
(25), and SSA (22).
A slightly higher percentage of females complete secondary in
ECA and LAC, but the opposite is true in other regions.
2
Income is the greatest source of disparity in secondary completion rates in all regions.
60
55
50
45
40
35
30
25
20
15
10
5
0
-5
Gender disparity
Location disparity
Income disparity
-10
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007

Do income disparities exist in lower secondary enrolment rates in SAS and MNA?
South Asia (SAS)
% of the population in the official age range of lower secondary education not in school
Middle East and North Africa (MNA)
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

% of the population in the official age range of lower secondary education not in school
Percentage of the population in the official age range of lower secondary education not in school
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

% of the population in the official age range of lower secondary education not in school
Source: Demographic and Health Surveys and Multiple Indicator Cluster Surveys In World Inequality Database on Education (WIDE), Nov. 2012

50
30
10
90
70
-10
-30
Richer students have higher scores in all but 3 countries – Iceland, Norway, and
Azerbaijan. The greatest income disparities are in 5 Latin American countries –
Brazil, Argentina, Chile, Uruguay, and Colombia.
110
Source: Porta and Mcdonald based on Programme for International Student Assessment (PISA 2009) data, 2010

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In 2000, the world gender parity index (GPI) for tertiary enrollments was
1.0 – perfect gender parity. Since then, female
GERs have been higher than male GERs, and the
GPI has been moving above 1.0.
MNA is the only region within +/- 0.05 of gender parity in 2010. LAC and
ECA have consistently had higher female GERs, and EAP has reversed from a male bias to a female bias.
SAS and SSA have maintained a strong male bias in tertiary enrolments over time.
Gender disparities in tertiary enrolment rates vary greatly across regions.
1,30
1,25
1,20
1,15
1,10
1,06
1,07 1,08
1,05
1,00
0,95
0,90
0,85
0,80
1,00
1,02
1,04
Female Bias
Male Bias
0,75
0,70
0,65
0,60
WLD
2000
EAP
2002
ECA
2004
LAC
2006
MNA
2008
SAS
2010
SSA
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012

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Only 9 countries are within +/-0.05 of gender parity in tertiary enrollments.
63% of countries have a female bias in tertiary enrolments vs. 37% with higher male enrolment rates.
One country –
Vietnam – has perfect gender parity (1.0).
In 10 countries, the female GER more than doubles the male GER. These countries are island nations in LAC and
Qatar (see next slide).
The majority of countries have higher female enrolment rates than male enrolment rates in tertiary education.
5,50
5,00
4,50
4,00
3,50
3,00
2,50
2,00
1,50
1,00
0,50
0,00
Male Bias
Female
Bias
Source: UNESCO Institute for Statistics in EdStats, Nov. 2012
Note: Data points are the most recent year with data available (2008-2011)

10 Countries with the Largest Female
Bias in Tertiary Enrolments
(2008-2011)
1 Qatar
2 Dominica
5.38
3.35
3 Antigua and Barbuda
4 St. Lucia
5 Guyana
6 Barbados
7 Jamaica
2.58
2.57
2.52
2.38
2.28
8 Cayman Islands
9 Bermuda
10 St. Kitts and Nevis
2.24
2.12
2.10
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012;
Notes: Black = 2010; Blue = 2008; Data were not available for 73 of
213 countries.
10 Countries with the Largest Male Bias in Tertiary Enrolments
(2008-2011)
1 Chad
2 Congo, Rep.
0.17
0.21
3 Afghanistan
4 Congo, Dem. Rep.
5 Central African Republic
6 Eritrea
7 Guinea
8 Ethiopia
9 Benin
10 Niger
0.24
0.31
0.32
0.33
0.33
0.36
0.38
0.38
Source: UNESCO Institute for Statistics in EdStats, Oct. 2012; Notes:
Maroon=2011; Black = 2010; Purple = 2009; Blue = 2008; Data were not available for 73 of 213 countries.




Levels of gender disparity in postsecondary attendance are much lower than levels of location and income disparity. More girls than boys attend post-secondary schools in EAP, ECA, and LAC.
Rural areas have between 5 (SSA) and 15
(LAC) percent lower attendance ratios than urban areas.
Income is the largest source of disparity across regions. Income disparities range from 8 percentage points in
SSA to 34 in LAC.
2
25
20
15
10
5
0
Income is the largest source of disparity in postsecondary gross attendance ratios in all regions.
35
30
Gender disparity
Location disparity
Income disparity
-5
EAP ECA LAC MNA SAS SSA
Source: Estimated by Porta (2011) using data from Demographic and Health
Surveys, Multiple Indicator Cluster Surveys, and Living Standards
Measurement Studies for 1985-2007




Globally, there is still a gender gap in youth literacy rates, though the gap has been shrinking over time.
There was a 8.6% difference between male and female youth literacy rates during 1985-1994.
The gender gap shrunk by 41.5% to 5.0% during
2005-2010. 92% of males were literate compared to 87% of females.
95
Fewer females emerge from education systems with basic literacy skills than males.
Male Female
92,2
90
90,4
85
80
87,6
79,0
83,9
87,1
75
70
1985-1994 1995-2004 2005-2010
Source: UNESCO Institute for Statistics in EdStats, March 2013

Gender disparities in youth literacy rates have decreased over time in all regions.
1,05




Gender disparities between male and female youth literacy rates have decreased in all regions.
EAP, ECA, and LAC have achieved almost perfect gender parity
(1.0), while MNA, SAS, and SSA lag behind.
SAS and MNA have improved greatly over time: They moved 0.17 and 0.14 closer to gender parity.
Progress in SSA has been slower with only
0.09 improvement.
1,00
0,95
0,90
0,85
0,80
0,75
0,70
0,65
0,90
0,93
0,95
EAP
1985-1994 1995-2004 2005-2010
ECA LAC MNA SAS SSA WLD
Source: UNESCO Institute for Statistics in EdStats, March 2013

(2006-2010)
Male
Bias
Male
Bias
Male
Bias
Gender
Parity
Source: UNESCO Institute for Statistics in EdStats, 2013
Note: Data displayed is for the most recent available year
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.




The 20 lowest female youth literacy rates were all found in Sub-
Saharan African countries except for
Pakistan.
Only 1/3 of female youth are literate in
Burkina Faso and Mali.
Less than half of female youth are literate in the top 5 countries.
10 Countries with the Lowest
Female Youth Literacy Rates
(2006-2010)
1 Burkina Faso
2 Mali
33.1
33.9
3 Chad
4 Benin
5 Ethiopia
40.6
44.6
47.0
6 Sierra Leone
7 Senegal
8 Guinea
9 Central African Republic
50.1
56.2
57.0
58.2
10 Pakistan 61.5
Source: UNESCO Institute for Statistics in EdStats, March 2013; Note:
Data points are the most recent year available: Green = 2009; Blue =
2007; Black = 2010; Data were not available for 71 countries.





These countries have increased their female youth literacy rates by
14 to 23 percentage points over time.
8 of 10 countries are in SSA and 2 are in
SAS.
Despite great improvement, only 4 of 10 countries have female youth literacy rates higher than
75%.
Haiti’s female youth literacy rate worsened over the period by 10 percentage points.
10 Countries with the
Most Improvement in
Female Youth Literacy Rates
Percentage
Points
Improved
1999-
2004
Rate
2006-
2010
Rate
1 Guinea
%
Improved
22.9
34.1
57.0
67.2
2 Gambia, The
3 Guinea-Bissau
4 Nepal
5 Bangladesh
6 Chad
20.3
41.4
61.7
49.1
19.4
45.9
65.3
42.3
18.2
60.1
78.4
30.3
18.2
60.3
78.5
30.3
17.3
23.2
40.6
74.6
7 Eritrea
8 Senegal
17.2
69.5
86.7
24.7
15.2
41.0
56.2
37.2
9 Mozambique
1
0
Ghana
15.0
50.0
65.1
30.0
14.4
65.5
79.9
22.0
Source: UNESCO Institute for Statistics in EdStats, March 2013
Notes: Data are most current available year within the time period;
Data were not available for 92 of 213 countries .

(2006-2010)
Source: UNESCO Institute for Statistics in EdStats, 2013
Note: Data displayed is for the most recent available year
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.




Globally, there is still a gender gap in adult literacy rates, though the gap has been shrinking over time.
There was a 12.6% difference between male
(82%) and female
(69.4%) adult literacy rates during 1985-1994.
The gender gap shrunk by 29% to 8.9% during
2005-2010. 88.6% of males were literate compared to 79.7% of females.
Fewer adult females have basic literacy skills, but the gender gap has decreased over time.
100
Male Female
90
88,6
86,9
80
82,0
79,7
76,9
70
69,4
60
50
40
30
20
10
0
1985-1994 1995-2004 2005-2010
Source: UNESCO Institute for Statistics in EdStats, Mar. 2013






Gender disparities in adult literacy rates have decreased over time in all regions.
ECA and LAC have achieved gender parity with GPIs at 0.98.
MNA, SAS, and EAP have made the most progress by moving 0.16,
0.13, and 0.13 closer to
1.0 (gender parity) respectively.
Progress in SSA has been slower with only
0.09 improvement.
SAS, SSA, and MNA are furthest from gender parity in adult literacy.
1,05
All regions are moving closer to gender parity in adult literacy rates.
0,75
0,70
0,65
0,60
0,55
0,50
1,00
0,95
0,90
0,85
0,80
0,85 0,88
0,90
1985-1994 1995-2004 2005-2010
EAP ECA LAC MNA SAS SSA WLD
Source: UNESCO Institute for Statistics in EdStats, March 2013




Less than one quarter of females are literate in the top 3 countries –
Mali, Burkina Faso, and Chad. Less than one third of females are literate in the top 7 countries.
All the countries on the list are in SSA except
Pakistan.
Of the 144 countries with data, 19 countries have female adult literacy rates less than
50% and 70 countries have rates higher than
90%.
10 Countries with the Lowest
Female Adult Literacy Rates
(2006-2010)
1 Mali
2 Burkina Faso
20.3
21.6
3 Chad
4 Ethiopia
5 Guinea
24.2
28.9
30.0
6 Benin
7 Sierra Leone
8 Senegal
9 Pakistan
30.3
31.4
38.7
40.3
10 Gambia, The 40.4
Source: UNESCO Institute for Statistics in EdStats, March 2013
Note: Data were not available for 71 countries. Data are for the most recent available year. Blue = 2007; Green = 2009; Black = 2010.





These countries have increased their female adult literacy rates by
11 to 23 percentage points over time.
Six of the countries are in SSA; 2 are in SAS.
Despite great improvement, more than 1/3 of women are illiterate in all of these countries except Saudi
Arabia.
Haiti’s rate worsened by 10.3 percentage points over time.
10 Countries with the
Most Improvement in
Female Adult Literacy Rates
Percentage
Points
Improved
1999-
2004
Rate
2006-
2010
Rate
1 Timor-Leste
%
Improved
23.0
30.0
53.0
76.5
2 Eritrea
3 Gambia, The
4 Nepal
5 Guinea-Bissau
6 Saudi Arabia
17.3
40.2
57.5
43.1
15.4
25.1
40.4
61.4
13.5
34.9
48.3
38.6
13.1
27.5
40.6
47.7
12.1
69.3
81.3
17.4
7 Guinea
8 Ghana
11.8
18.2
30.0
64.7
11.4
49.8
61.2
22.9
9 Bangladesh
1
0
Chad
11.4
40.8
52.2
27.9
11.4
12.8
24.2
89.0
Source: UNESCO Institute for Statistics in EdStats, March 2013
Notes: Data are most current available year within the time period;
Data were not available for 90 of 213 countries .

(2006-2010)
Source: UNESCO Institute for Statistics in EdStats, 2013
Note: Data displayed is for the most recent available year
The maps displayed were produced by EdStats. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The maps are for reference only.

This presentation utilizes the following data sources:
1) UNESCO Institute for Statistics data in the EdStats Query


The presentation was created with the most recent UIS data release that included 2010 data for most indicators/countries.
Indicators were calculated by UIS according to definitions available in the
EdStats Query .
2) Demographic and Health Surveys, Multiple Indicator Cluster Surveys, and Living Standards Measurement Studies for 1985-2007; Reports were generated through ADePT Edu (2011)
3) Demographic and Health Surveys and Multiple Indicator Cluster
Surveys in the World Inequality Database on Education (WIDE)
4) Learning Outcome Data from the EdStats Query:



Southern and Eastern Africa Consortium for Monitoring Educational Quality
(SACMEQ)
Latin American Laboratory for Assessment of the Quality of Education (LLECE
SERCE)
Programme for International Student Assessment (PISA)

The following State of Education presentations are available on the EdStats website :

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
Access
Quality
Expenditures
Gender
Literacy
Equity

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Pre-Primary Education
Primary Education
Secondary Education
Tertiary Education