28 December 2008

Global Education Digest 2008

Cover of the Global Education Digest 2008The UNESCO Institute for Statistics (UIS) has announced the publication of the Global Education Digest 2008: Comparing Education Statistics Across the World. This annual publication contains detailed statistical tables with the latest UIS data on pre-primary, primary, secondary and tertiary education, education finance and literacy.

The introductory chapters in the this year's edition of the Digest discuss the data collection process at UIS, the International Standard Classification of Education (ISCED) and differences between national and international education data, the use of historical time series to track educational trends, and programs of cooperation between UIS and the Organisation for Economic Co-operation and Development (OECD) and the Statistical Office of the European Communities (Eurostat).

The Global Education Digest 2008 contains several tables that were not available in the 2007 edition. New tables with time series data provide statistics for more than 200 countries and territories from 1970, 1980, 1990, 2000 and 2005 for the following indicators: primary and secondary school age; population of secondary school age (the population of primary school age is available at the UIS Data Centre, see below); enrollment in primary, secondary and post-secondary education; total enrollment from primary to tertiary education; primary and secondary school gross enrollment ratio (GER); primary school gross intake ratio; gross intake ratio to the last grade of primary school (a proxy indicator for the primary completion rate); repetition rate in primary and secondary school; school life expectancy (primary to secondary and primary to tertiary); pupil/teacher ratio in primary and secondary school; and public expenditure on education.

A further addition in the new publication is a set of tables with data for 62 UOE and WEI countries. UOE refers to a joint data collection program by UIS, OECD and Eurostat in high- and middle-income countries. WEI stands for World Education Indicators, a UIS program for middle-income countries. The participating countries are listed on pages 30 and 31 of the Global Education Digest 2008.

The data from the tables in the Global Education Digest can be downloaded from the UIS Data Centre (click on "Predefined Tables" and then "Education"). The time series data for the years 1970 to 2005 are available in Excel format in Tables 21 to 23. The population of primary school age between 1970 and 2005 is not shown in the printed report but included in Table 21. In addition, the Data Centre offers annual data for the years 1999 to 2008, while the Digest only shows data for one or two years, depending on the indicator.

References
  • UNESCO Institute for Statistics (UIS). 2008. Global education digest 2008: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 7.3 MB)
  • UNESCO Institute for Statistics (UIS). 2007. Global education digest 2007: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 3.7 MB)
External links
Related articles
Friedrich Huebler, 28 December 2008 (edited 31 July 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/ged.html
on No comments:

20 December 2008

Education and democracy

Democratic government and the level of education in a country tend to be highly correlated. Seymour Lipset described this link in his article "Some social requisites of democracy: Economic development and political legitimacy."
"Education presumably broadens man's outlook, enables him to understand the need for norms of tolerance, restrains him from adhering to extremist doctrines, and increases his capacity to make rational electoral choices. ... The higher one's education, the more likely one is to believe in democratic values and support democratic practices. ... If we cannot say that a 'high' level of education is a sufficient condition for democracy, the available evidence suggests that it comes close to being a necessary one." (Lipset 1959: 79-80)
The correlation between education and democracy can be demonstrated with data on the school life expectancy from the UNESCO Institute for Statistics (UIS) and the democracy index from the Economist Intelligence Unit (EIU).

The democracy index is based on five categories: electoral process and pluralism, civil liberties, the functioning of government, political participation, and political culture. The methodology is explained in the full report from the EIU. The EIU calculated the democracy index for 167 countries and territories and placed them within four types of regime, depending on the index score.
  1. Full democracies (score 8-10): 30 countries
  2. Flawed democracies (score 6-7.9): 50 countries
  3. Hybrid regimes (score 4-5.9): 36 countries
  4. Authoritarian regimes (score below 4): 51 countries
The school life expectancy, obtained from the UIS Data Centre, is the total number of years of schooling a child can expect to receive. For 9 of the 167 countries rated by the EIU no data on the school life expectancy were available: Bosnia and Herzegovina, Haiti, North Korea, Montenegro, Papua New Guinea, Saudia Arabia, Singapore, Taiwan, and Turkmenistan.

The values for the 158 countries with data are plotted in the graph below. The school life expectancy is plotted along the horizontal axis and the EIU democracy index along the vertical axis. All countries are identified with their ISO alpha-3 codes.

National school life expectancy and EIU democracy index
Scatter plot with school life expectancy and EIU democracy index
Data source: UNESCO Institute for Statistics, Economist Intelligence Unit.

The graph shows that increasing school life expectancy is generally associated with a higher EIU democracy index. The average school life expectancy is 16.1 years for full democracies, 12.8 years for flawed democracies, 9.8 years for hybrid regimes, and 9.6 years for authoritarian regimes.

Average school life expectancy by regime type
Regime type School life expectancy (years)
Full democracies 16.1
Flawed democracies 12.8
Hybrid regimes 9.8
Authoritarian regimes 9.6
Data source: UNESCO Institute for Statistics, Economist Intelligence Unit.

Among authoritarian regimes the school life expectancy has a wider spread than among the other three types of regime. Two countries with authoritarian regimes, Cuba (democracy index 3.5, school life expectancy 16.1 years) and Libya (democracy index 2.0, school life expectancy 16.5 years), match or exceed the average school life expectancy in full democracies.

In contrast, no full democracy except Costa Rica (democracy index 8.0, school life expectancy 11.7 years) has a school life expectancy below 13.5 years. This observation supports Lipset's argument that a high level of education is a necessary condition for democracy.

References
  • Lipset, Seymour Martin. 1959. Some social requisites of democracy: Economic development and political legitimacy. American Political Science Review 53 (1), March: 69-105.
  • Economist Intelligence Unit. 2008. The Economist Intelligence Unit's index of democracy 2008. October. (Download PDF, 536 KB)
Related articles
External links
Friedrich Huebler, 20 December 2008 (edited 21 December 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/democracy.html
on No comments:

08 December 2008

EFA Global Monitoring Report 2009

Cover of the EFA Global Monitoring Report 2009UNESCO released the 2009 edition of the Education for All Global Monitoring Report 2009 on 25 November 2008. The title of this year's report is Overcoming inequality: Why governance matters.

The report emphasizes the responsibility of governments across the world to tackle persistent inequalities in education - linked to wealth, gender, ethnicity, area of residence, and other factors - that threaten the Millennium Development Goal of universal primary education. According to projections by UNESCO, at least 29 million children of primary school age will still be out of school in 2015. Many children who attend school fail to reach basic literacy and numeracy. A lack of education among disadvantaged groups contributes to persistent poverty, increased child mortality, and slower economic growth.

The EFA Global Monitoring Report 2009 and related material are available at the EFA website of UNESCO.

References
  • UNESCO. 2008. EFA Global Monitoring Report 2009 - Overcoming inequality: Why governance matters. Paris: UNESCO. (Download in PDF format, 9.2 MB)
External links
Related articles
Friedrich Huebler, 8 December 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/efa.html
on No comments:

23 November 2008

Multiple Indicator Cluster Survey blog

Screenshot of the "MICS For All" blogThe Multiple Indicator Cluster Surveys (MICS) are household surveys carried out in developing countries with the support of UNICEF to collect data on the situation of children and women. The most recent round of MICS surveys was conducted between 2005 and 2007 in more than 40 countries. MICS data and documentation are available at the Childinfo website of UNICEF.

MICS surveys are among the sources of data analyzed on this site. MICS data were used in articles on trends in primary education in Nepal, children out of school in India, child labor and school attendance in Bolivia, education disparity trends in South Asia, global data on child labor and school attendance, household wealth and years of education, the link between years of schooling and literacy, and other studies.

UNICEF staff members working on the MICS have launched a new blog at globalmics.blogspot.com. The goal of the blog is "to facilitate information sharing between different organizations and individuals involved with MICS implementation around the world" and "to play the role of an unofficial, informal forum to share information on MICS activities." Articles posted since the launch have treated a variety of topics, among them acronyms and abbreviations related to MICS, members of the global MICS team, and the evaluation of the latest round of MICS.

External links
Related articles
Friedrich Huebler, 23 November 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/mics.html
on No comments:

16 November 2008

Pupil/teacher ratio in secondary school

The pupil/teacher ratio is an indicator of education quality. In crowded classrooms with a high number of pupils per teacher the quality of education suffers. For pupils it is difficult to follow the course and teachers can dedicate less time to the needs of each individual student. Data from UNESCO on the pupil/teacher ratio in primary school show that crowded classrooms are more common in Sub-Saharan Africa and Southern Asia than in other parts of the world. 22 of the 27 countries with 40 or more pupils per primary school teacher are located in Sub-Saharan Africa.

In secondary school, pupil/teacher ratios are lower than in primary school. The Data Centre of the UNESCO Institute for Statistics provides the pupil/teacher ratio in secondary school for 189 countries and territories. For 100 countries, the pupil/teacher ratios are from 2006, 9 countries have data from 2007, 51 countries have data from 2004 or 2005, and the remaining 29 countries have data from 1999 to 2003. For the map below, all countries with data were divided into five groups:
  • Fewer than 10 pupils per teacher: 24 countries
  • 10 to 19 pupils per teacher: 107 countries
  • 20 to 29 pupils per teacher: 41 countries
  • 30 to 39 pupils per teacher: 13 countries
  • 40 or more pupils per teacher: 4 countries
Pupil/teacher ratio in secondary school, circa 2006
Map of the world showing national pupil/teacher ratios in secondary school
Data source: UNESCO Institute for Statistics, Data Centre, May 2008.

The lowest pupil/teacher ratios in secondary school were reported for Bermuda (6.0), Tokelau (7.0), Portugal (7.1), and Andorra (7.8). 20 additional countries have pupil/teacher ratios above 8 and below 10: Armenia, Azerbaijan, Belarus, British Virgin Islands, Cayman Islands, Croatia, Georgia, Greece, Kuwait, Lebanon, Liechtenstein, Lithuania, Malta, Monaco, Niue, Norway, Qatar, Russia, Sweden, and Turks and Caicos Islands.

More than half of all countries - including most countries in North and South America, Europe, the Middle East, and East Asia - have pupil/teacher ratios between 10 and 19. The group also includes some countries in other regions. Although pupil/teacher ratios in Sub-Saharan Africa are generally higher than in other parts of the world, the following countries from the region have only 10 to 19 pupils per secondary school teacher: Angola, Botswana, Burundi, Cameroon, Cape Verde, Comoros, Democratic Republic of Congo, Ghana, Guinea-Bissau, Mauritius, Seychelles, and Swaziland. 22 of the 41 countries with pupil/teacher ratios between 20 and 29 are also located in Sub-Saharan Africa.

17 countries have 30 or more pupils per teacher in secondary school and 10 of these countries are in Sub-Saharan Africa. The countries with 30 to 39 pupils per teacher are Chad, Congo, Djibouti, Honduras, India, Kenya, Mozambique, Myanmar, Nepal, Nicaragua, Philippines, South Africa, and Zambia. Classes at the secondary level of education are most crowded in Nigeria (pupil/teacher ratio 40.2), Pakistan (41.9), Malawi (45.6), and Eritrea (54.4).

The following table lists the average pupil/teacher ratio in secondary school by Millennium Development Goal region. The Commonwealth of Independent States (10.9), the developed countries (11.4), Oceania (14.8), Western Asia (15.3), Latin America and the Caribbean (16.6), Eastern Asia (19.0), and Northern Africa (19.0) have average pupil/teacher ratios below 20. Pupil/teacher ratios are highest in South-Eastern Asia (22.8), Sub-Saharan Africa (25.8), and Southern Asia (26.4). The global average is 18.0 pupils per teacher in secondary school. These average values are unweighted, which means that each country is given the same weight within its region, regardless of the size of its population.

Average pupil/teacher ratio in secondary school by MDG region, circa 2006
MDG region
 Pupil/teacher ratio
Developed countries 11.4
Commonwealth of Independent States 10.9
Eastern Asia 19.0
South-Eastern Asia 22.8
Oceania 14.8
Southern Asia 26.4
Western Asia 15.3
Northern Africa 19.0
Sub-Saharan Africa 25.8
Latin America and the Caribbean 16.6
World 18.0
Data source: UNESCO Institute for Statistics, Data Centre, May 2008. Regional and global averages are unweighted.

The data analyzed in this article can be downloaded from the UNESCO Institute for Statistics Data Centre, under Predefined Tables - Education - Table 11: Indicators on teaching staff at ISCED levels 0 to 3.

Related articles
External links
Friedrich Huebler, 16 November 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/ptr.html
on 2 comments:

08 November 2008

School attendance in Brazil

Brazil is the largest and most populous country in South America. The Brazilian Institute of Geography and Statistics (IBGE) estimates that the population of Brazil grew to 190 million in 2008. The World Bank ranks Brazil as the world's tenth largest economy with a gross domestic product (GDP) of $1.3 trillion in 2007.

Brazil has achieved high levels of school attendance and literacy. The UNESCO Institute for Statistics (UIS) estimates that 94 percent of all children of primary school age were enrolled in primary school in 2005, the latest year with data. The youth literacy rate, for persons aged 15 to 24 years, was 99 percent in 2007 according to the UIS. Among the adult population aged 15 years and older, 91 percent were literate in 2007. In contrast, in 1980 only 75 percent of the adult population of Brazil could read and write.

The patterns of school attendance in Brazil can be studied in greater detail with data from the 2006 National Household Sample Survey (Pesquisa Nacional por Amostra de Domicílios, PNAD). The survey collected data on current and past school attendance for all household members, regardless of age. For the analysis that follows, the levels of education in the PNAD data were recoded to match the International Standard Classification of Education (ISCED) of 1997. Five levels of education are identified:
  • Pre-primary education
  • Primary education
  • Secondary education
  • Tertiary education
  • Adult literacy programs
Adult literacy programs are not part of the ISCED classification but they play an important role in Brazil and are therefore included as a separate group. The graph below illustrates current school attendance by age and level of education for the population aged 0 to 30 years. The number at the top of each bar is the percent of persons of a particular age that are currently in school. For example, 97 percent of all 7-year-olds were in school at the time of the survey; the majority attended primary school but more than 10 percent of all 7-year-olds were still in preschool.

The official school ages in Brazil are indicated along the horizontal axis. The official entrance age for pre-primary education is 4 years, primary education begins at 7 years, and secondary education at 11 years. Education is compulsory for all children aged 7 to 14 years.

Brazil: Current school attendance by age and level of education, 2006
Level of education attended for persons 0 to 30 years, Brazil 2006
Data source: Brazil National Household Sample Survey (PNAD), 2006.

The PNAD data show that many young children in Brazil attend pre-primary education. Two thirds of all children between 4 and 6 years are in preschool or day care. The laws on compulsory education have the desired effect and almost all children between 7 and 14 years are in fact in school. The attendance rates in this age group range from 94 percent among 14-year-olds to 99 percent among 8- to 11-year-olds. Among children of secondary school age, the attendance rate drops steadily from 99 percent at age 11 to 74 percent at age 17. About 8 percent of 18-year-olds are in tertiary education. University attendance rates reach a peak of 15 percent among 20- to 22-year-olds.

Overage school attendance is relatively common in Brazil and many children older than 10 years are still in primary school. Persons up to and beyond age 30 attend secondary education. These high levels of primary and secondary school attendance among the older population are partly a result of a system of education that offers persons who dropped out of school an opportunity to continue their education later in life. Adult literacy programs reach a relatively small part of the population but they contribute to the high level of literacy in Brazil. About 0.5 to 1 percent of the population between 30 and 75 years participate in programs that teach reading and writing.

Data sources
Related articles
External links
Friedrich Huebler, 8 November 2008 (edited 24 January 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/brazil.html
on No comments:

01 November 2008

Education disparity trends in South Asia

An article on education disparity in South Asia described a newly developed Education Parity Index (EPI). This index combines data on primary school attendance, secondary school attendance and the survival rate to the last grade of primary school, disaggregated by gender, area of residence and household wealth. The value of the EPI has a theoretical range of 0 to 1, where 1 indicates absolute parity.

Through a combination of survey data from several years it is possible to analyze trends in disparity as measured by the EPI. For the trend analysis, data from the following South Asian household surveys - mainly Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) - were available.
  • Afghanistan: 2003 MICS
  • Bangladesh: 1999-2000 DHS, 2004 DHS, 2006 DHS
  • India: 1998-99 DHS, 2000 MICS, 2005-06 DHS
  • Nepal: 1996 DHS, 2000 MICS, 2001 DHS, 2006 DHS
  • Pakistan: 2000-01 survey, 2006-07 DHS
The graph below plots the EPI values calculated from each survey. Due to a lack of data, no trends can be shown for Afghanistan.

Education disparity trends in South Asia, 1996-2007
Trend lines with Education Parity Index values between 1996 and 2007
Data source: Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), 1996-2007.

In Bangladesh, India and Nepal, the EPI has increased from the earliest to the latest year with data, indicating a decrease in disparity over the period of observation. In Bangladesh, the EPI grew from 0.79 in 2000 to 0.84 in 2006. In India, the EPI was at 0.77 in 1999 and 0.82 in 2006. In Nepal, the EPI shows the biggest increase, from 0.67 in 1996 to 0.83 in 2006, interrupted by a decrease from 2000 to 2001. Compared to the other countries, Nepal has thus made the most progress toward parity in the education system.

For Pakistan, the EPI has decreased from 2000 to 2007, indicating an increase in disparity. However, an inspection of the underlying data reveals that the earlier survey did not provide data on household wealth. Disparities related to wealth are usually greater than disparities related to gender or area of residence. If data on wealth had been available, the EPI for 2000 would most likely have been lower. The data from the 2006-07 DHS confirm this assumption. Children from the poorest quintile have much lower attendance and survival rates than children from the richest quintile, and the disparity between these two groups of children is much greater than the disparity between boys and girls and between children from urban and rural households. For example, the primary school net attendance rate (NAR) in Pakistan is 46 percent among children from the poorest household quintile but twice as high, 93 percent, among children from the richest quintile. In comparison, the primary NAR is 76 percent for boys, 67 percent for girls, 82 percent for urban children, and 67 percent for rural children according to the 2006-07 DHS.

The data gaps in the graph bring to attention one limitation of the EPI. The net enrollment rate and other data published annually by UNESCO in the Global Education Digest or the Education For All Global Monitoring Report are not disaggregated beyond gender and can therefore not be used to calculate the EPI. On the other hand, national household survey data, which permit the required level of disaggregation, are not collected every year but only every four or five years, on average.

Related articles
External links
Friedrich Huebler, 1 November 2008 (edited 22 November 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/south-asia.html
on 1 comment:

26 October 2008

Pupil/teacher ratio in primary school

Global primary school attendance rates have been on a steady upward trend over the past years. As the world moves closer to the goal of universal primary education, the issue of education quality attracts increasing attention. One measure of education quality is the pupil/teacher ratio, the number of pupils per teacher in a school. Teachers of a large class can dedicate less time to each pupil than in a small class. For the pupils, crowded classrooms make it difficult to concentrate on the material and to learn. The results of overcrowding are lower academic achievement and increased dropout rates.

The map below displays the pupil/teacher ratio in primary school in 194 countries and territories for which data were available. The data were obtained from the UNESCO Institute for Statistics. For 124 countries, the pupil/teacher ratios are from 2006, 12 countries have data from 2007, 42 countries have data from 2004 or 2005, and the remaining 16 countries have data from 1999 to 2003. For the map, all countries were divided into five groups:
  • Fewer than 10 pupils per teacher: 7 countries
  • 10 to 19 pupils per teacher: 90 countries
  • 20 to 29 pupils per teacher: 43 countries
  • 30 to 39 pupils per teacher: 27 countries
  • 40 or more pupils per teacher: 27 countries
Pupil/teacher ratio in primary school, circa 2006
Map of the world showing national pupil/teacher ratios in primary school
Data source: UNESCO Institute for Statistics, Data Centre, May 2008.

The lowest pupil/teacher ratios in primary school were observed in Tokelau (5.8), San Marino (6.3), Bermuda (8.3), Liechtenstein (8.4), Denmark (9.9), and Sweden and Cuba (10.0). Most developed countries, countries in Eastern Europe and former members states of the Soviet Union have pupil/teacher ratios between 10 and 19. Some countries in East and South-East Asia, the Middle East, Africa, and Latin America also belong to this group, among them China, the world's most populous country, with a pupil/teacher ratio of 18.3. The majority of countries in Latin America, as well as some countries in Africa and Asia, have pupil/teacher ratios between 20 and 29.

Pupil/teacher ratios above 30 are common in Sub-Saharan Africa and South Asia. In 11 countries, primary school teachers have more than 50 pupils on average: Afghanistan (83.4), Mozambique (67.4), Rwanda (65.9), Chad (63.2), Mali (55.6), Congo (54.8), Burundi (54.2), Tanzania (53.1), Zambia (51.2), Bangladesh (50.9), and Cambodia (50.4). 22 of the 27 countries with 40 or more pupils per teacher are located in Sub-Saharan Africa.

The following table lists the average pupil/teacher ratio in primary school by Millennium Development Goal region. The highest pupil/teacher ratios exist in Sub-Saharan Africa (40.7) and Southern Asia (37.8). In contrast, the average pupil/teacher ratio in the developed countries is 13.7. In Western Asia (17.8), the Commonwealth of Independent States (17.9), and Oceania (19.8), the average pupil/teacher ratio is also below 20. The global average is 24.6 pupils per teacher in primary school. All regional and global averages are not weighted the population of each country; instead, each country is given the same weight within its region, regardless of the size of its population.

Pupil/teacher ratio in primary school by MDG region, circa 2006
MDG region
 Pupil/teacher ratio
Developed countries 13.7
Commonwealth of Independent States 17.9
Eastern Asia 23.4
South-Eastern Asia 26.5
Oceania 19.8
Southern Asia 37.8
Western Asia 17.8
Northern Africa 24.4
Sub-Saharan Africa 40.7
Latin America and the Caribbean 21.3
World 24.6
Data source: UNESCO Institute for Statistics, Data Centre, May 2008. Regional and global averages are unweighted.

The data analyzed in this article can be downloaded from the UNESCO Institute for Statistics Data Centre, under Predefined Tables - Education - Table 11: Indicators on teaching staff at ISCED levels 0 to 3.

Related articles
External links
Friedrich Huebler, 26 October 2008 (edited 16 November 2006), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/ptr.html
on No comments:

17 October 2008

UN Millennium Development Goals Report 2008

Cover of UN MDG Report 2008In August 2008, the United Nations published the latest edition of its annual report on progress toward the Millennium Development Goals (MDG). The Millennium Development Goals Report 2008 presents data for each of the eight MDGs.
  1. Eradicate extreme poverty and hunger
  2. Achieve universal primary education
  3. Promote gender equality and empower women
  4. Reduce child mortality
  5. Improve maternal health
  6. Combat HIV/AIDS, malaria and other diseases
  7. Ensure environmental sustainability
  8. Develop a global partnership for development
In the section on MDG 2, universal primary education, trends in primary school enrollment from 1991 to 2006 are shown for each MDG region. One region, the Commonwealth of Independent States, is further divided into countries in Europe and Asia. No data are provided for the Oceania region.

Primary school net enrollment rate, 1991-2006
Bar graph with regional primary school net enrollment rates from 1991 to 2006
Source: United Nations, The Millennium Development Goals Report 2008, page 12.

Six MDG regions have reached primary school net enrollment rates at or above 90 percent: Commonwealth of Independent States (Europe and Asia), Eastern Asia, South-Eastern Asia, Southern Asia, Northern Africa, and Latin America. Western Asia is slightly behind with a primary NER of 88 percent. In absolute terms, Sub-Saharan Africa has made the most progress since the turn of the millennium, with a 13 percent increase in the primary NER from 58 percent in 2000 to 71 percent in 2006. This increase was achieved in spite of strong growth in the population of primary school age. Still, three out of ten children of primary school age in Sub-Saharan Africa are not enrolled in primary school. In all developing regions combined, the primary NER rose from 80 percent in 1991 to 88 percent in 2006. In contrast, the primary NER in the developed regions declined from 98 percent in 1991 to 96 percent in 2006.

References
  • United Nations. 2008. The millennium development goals report 2008. New York: United Nations. (Download PDF document, 3.3 MB)
Related articles
External links
Friedrich Huebler, 17 October 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/mdg-report.html
on No comments:

12 October 2008

Education disparity in South Asia

Cover of "Beyond gender: Measuring disparity in South Asia using an education parity index" by Friedrich HueblerA new publication by Friedrich Huebler describes education disparity in the countries of South Asia. The report Beyond gender: Measuring disparity in South Asia using an education parity index was published by the UNICEF regional office for South Asia in its series of papers on girls' education.

Analysis of disparities in national education systems is often limited to gender although other dimensions of disparity are also important. The publication presents data on disparity in primary and secondary education by gender, area of residence and household wealth for countries in South Asia.

To facilitate the interpretation of complex data a newly developed Education Parity Index is introduced. The EPI combines information on disparities across different education indicators and across different groups of disaggregation. This distinguishes the EPI from existing indicators of disparity in education, including the gender parity index and the EFA development index. The EPI is flexible and can be modified according to national priorities, for example by including information on disparities between different ethnic groups.

The use of the EPI as a tool to assess education disparities is illustrated with household survey data from Afghanistan, Bangladesh, India, Nepal and Pakistan. For each country, the report describes how the EPI is calculated. In addition, national trends in education disparity from 1996 to 2006 are presented.

References
  • Huebler, Friedrich. 2008. Beyond gender: Measuring disparity in South Asia using an education parity index. Kathmandu: UNICEF. (Download PDF document, 194 KB)
External links
Related articles
Friedrich Huebler, 12 October 2008 (edited 9 September 2012), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/epi.html
on 1 comment:

05 October 2008

Child labor and school attendance

A previous article on child labor on this site presented a definition of child labor that considers both economic activity and household chores. The inclusion of household chores leads to a more precise measure of the burden of work on children. In particular, this new child labor indicator is less biased against girls, who typically spend more time on household chores and less time on economic activity than boys.

In the graph below, the proposed child labor indicator is used to evaluate the trade-off between child labor and school attendance among children aged 7 to 14 years in 35 developing countries. This age group was selected because in all 35 countries children are expected to enter primary school by age 7. The underlying data were collected with 26 Multiple Indicator Cluster Surveys (MICS) and 9 Demographic and Health Surveys (DHS) between 1999 and 2005. 34 of the surveys are nationally representative and one, Palestinians in Syria, is a subnational sample. Surveys conducted during school vacation were excluded from the analysis. The results therefore show the trade-off between child labor and school attendance during a time of the year when children are supposed to be in school.

School attendance refers to attendance of any type of school and not only schools that are part of the formal system of education. In addition, children of secondary school age who are still in primary school are also counted as attending school for the purpose of the present analysis. In contrast, such overage children are counted as out of school when indicators like the secondary school net attendance rate (NAR) are calculated. In a further simplification, child labor is defined for all ages as at least one hour of economic activity or 28 or more hours of household chores per week.

Child labor and school attendance, children 7-14 years
Scatter plot with child labor and school attendance rates in 35 countries
Data source: Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), 1999-2005.

The scatter plot above demonstrates the trade-off between child labor and school attendance. Countries with low child labor rates typically have high school attendance rates and vice versa. A linear regression shows that a 10 point increase in child labor is associated with a 7.6 point decrease in school attendance at the national level.

On average across the 35 countries in the sample, 77 percent of 7- to 14-year-olds attended school at the time of they survey. In ten countries, at least 90 percent of children were in school. In seven countries - Central African Republic, Chad, Guinea-Bissau, Mali, Niger, Sierra Leone, and Somalia - less than half of all children went to school. Somalia has by far the lowest attendance rate with 19 percent.

25 percent of all children between 7 and 14 years were engaged in child labor, ranging from 4 percent among Palestinians in Syria to 78 percent in Niger and Sierra Leone. In six countries, more than half of all children in this age group were child laborers: Central African Republic, Chad, Guinea-Bissau, Niger, Sierra Leone, and Uganda.

Related articlesExternal links
Friedrich Huebler, 5 October 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/child-labor.html
on No comments:

07 September 2008

Child labor: economic activity and household chores

Child labor is one of the obstacles on the way to the Millennium Development Goal of universal primary education by 2015. In a report on global child labor trends, the International Labour Organization (ILO) estimates that there are 218 million child laborers worldwide. 126 million of these children are estimated to be engaged in hazardous work (ILO 2006). The concept of child labor used by the ILO is derived from two conventions: ILO Convention 138, which sets 15 years as the general minimum age for employment, and ILO Convention 182 on the worst forms of child labor. Any work in violation of Conventions 138 and 182 is considered illegal child labor that should be eliminated.

One limitation of statistics like those published by the ILO is that they only refer to economic activity, that is work related to the production of goods and services, as defined in the United Nations System of National Accounts (UNSD 2001). This definition excludes chores undertaken in a person's own household like cooking, cleaning or caring for children.

Statistics of child labor that ignore household chores are problematic because they underestimate the burden of work on children, especially for girls. To examine the relative burden of economic activities and household chores carried out by children, data from 35 household surveys were analyzed for this article. Grouped by Millennium Development Region, these surveys are:
  • Developed countries: Albania.
  • Eastern Asia: Mongolia.
  • South-eastern Asia: Lao PDR, Philippines.
  • Southern Asia: India.
  • Western Asia: Bahrain, Lebanon, Palestinians in Syria.
  • Sub-Saharan Africa: Angola, Burundi, Central African Republic, Chad, Comoros, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Gambia, Guinea, Guinea-Bissau, Kenya, Lesotho, Malawi, Mali, Niger, Senegal, Sierra Leone, Somalia, Swaziland, Tanzania, Uganda.
  • Latin America and the Caribbean: Bolivia, Colombia, Dominican Republic, Nicaragua, Trinidad and Tobago.
The surveys were conducted between 1999 and 2005. 26 of the surveys were Multiple Indicator Cluster Surveys (MICS) and 9 were Demographic and Health Surveys (DHS). All 35 surveys collected data on work by children in the week preceding the survey. Surveys conducted during school vacation were excluded because the focus of the present analysis is work by children that should have been in school at the time of the survey.

The share of children aged 7 to 14 years in economic activity and household chores is depicted in the following graph. The graph also displays the number of hours spent per week on both types of work. All numbers are averages across the 35 surveys, weighted by each country's population between 7 and 14 years.

Economic activity and household chores, children 7-14 years
Graph showing the link between household wealth and average years of education
Data source: 35 DHS and MICS surveys, 1999-2005.

The results confirm that boys are more likely to be engaged in economic activity while girls are more likely to do household chores. On average across the 35 surveys, 22 percent of all boys and 19 percent of all girls between 7 and 14 years are engaged in economic activity. Boys also spend more hours on economic activity than girls, 20 compared to 19 hours. By comparison, girls are much more likely than boys to do household chores. 70 percent of all girls and 47 percent of all boys did household chores in the week preceding the survey. On average, girls spent 13 hours and boys 10 hours per week on household chores.

What are the implications of these findings for statistics of child labor, as currently defined by the ILO? Take the case of two families that need additional income to provide food for everyone in the household. In the first family, a 10-year-old boy is withdrawn from school and put to work on a farm. Because such work is considered economic activity the number of child laborers goes up. In the second family, the mother decides to start working on a farm and her 10-year-old daughter is asked to stay at home to care for her younger siblings. Because the girl is engaged in household chores the number of child laborers does not change. The consequences are the same for both children: they no longer go to school and miss out on the benefits from education.

To address the limitations of the ILO's definition of child labor, UNICEF has developed an expanded definition that covers household chores in addition to economic activity. This revised indicator is the basis for the child labor estimates that are reported in publications like Progress for Children (UNICEF 2007a) or The State of the World’s Children (UNICEF 2007b). For children 5 to 17 years of age, UNICEF defines child labor as follows:
  • 5 to 11 years: any economic activity, or 28 hours or more household chores per week;
  • 12 to 14 years: any economic activity (except light work for less than 14 hours per week), or 28 hours or more household chores per week;
  • 15 to 17 years: any hazardous work, including any work for 43 hours or more per week.
The goal of UNICEF's child labor indicator is the measurement of work that should be eliminated because it violates international child labor conventions and interferes with school attendance. The threshold for household chores is set relatively high because it is assumed that household chores are less harmful than economic activity. Moreover, the high threshold of 28 hours household chores per week avoids a possible overestimation of the number of child laborers.

References
  • International Labour Organization (ILO). 2006. Global child labour trends 2000-2004. Geneva: ILO. (Download PDF, 640 KB)
  • United Nations Children's Fund (UNICEF). 2007a. Progress for children: A World Fit for Children statistical review. New York: UNICEF. (Download PDF, 3.6 MB)
  • United Nations Children's Fund (UNICEF). 2007b. The state of the world's children 2008: Child survival. New York: UNICEF. (Download PDF, 4.3 MB)
  • United Nations Statistics Division (UNSD). 2001. System of national accounts 1993. http://unstats.un.org/unsd/sna1993/toctop.asp.
Related articles
External links
Friedrich Huebler, 7 September 2008 (edited 5 October 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/09/child-labor.html
on 2 comments:

24 August 2008

Household wealth and years of education

At the national level, a country's wealth (measured by GDP per capita) and the education of its population (measured by school life expectancy) are highly correlated, as demonstrated in an article on national wealth and years of education. In developed countries with a high level of national income the population usually has more years of education than the population of low income countries.

A similar link can be observed at the level of individual households. Households whose members have a higher level of education are usually wealthier than households with less educated members. The relationship between household wealth and education can be analyzed with data from household surveys. This article looks at data from 12 nationally representative household surveys that were conducted between 2004 and 2006 in Bangladesh, Cambodia, Colombia, Egypt, Ethiopia, Haiti, India, Moldova, Nepal, Niger, Sierra Leone, and Zimbabwe. The data from Bangladesh and Sierra Leone is from Multiple Indicator Cluster Surveys (MICS) and the data from the other countries was collected with Demographic and Health Surveys (DHS).

DHS and MICS surveys collect data on assets owned by a household - for example, water supply and sanitation facilities, housing material, radio, telephone, refrigerator, bicycle, automobile, and livestock - that can be used to construct an index of household wealth (Filmer and Pritchett 2001). With this index it is possible to rank the households in a survey from poorest to richest. The households can then be divided into wealth deciles, each containing 10 percent of the sample population.

DHS and MICS surveys also collect data on the education of all household members above a certain age, usually 5 to 7 years. For the analysis in this article, the years of formal education of all household members aged 20 to 65 years were examined. For example, a person that did not complete primary school may have 3 years of education while someone with a university degree may have 16 years of education. In the next step, the average number of years of education within each wealth decile is calculated.

The data on household wealth and years of education is plotted in the graph below. Wealth deciles are plotted along the horizontal axis. The average number of years of education of persons aged 20 to 65 years in each wealth decile is plotted along the vertical axis. As an example, in Bangladesh, persons in the poorest decile have 1.3 years of education on average and persons in the richest decile have 10.1 years of education.

Household wealth and years of education
Graph showing the link between household wealth and average years of education
Data source: Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), 2004-2006.

The graph shows that an increase in the average years of education of all adult household members is correlated with an increase in household wealth. This relationship is true without exception in all 12 countries that were analyzed. Persons in higher wealth deciles always have more years of education than persons in lower deciles.

The graph also shows that the disparity between poorer and richer households in terms of education varies from country to country. In Moldova, almost everyone attends primary and secondary school and even in the poorest decile the average number of years of education is 9.3, compared to 13.6 years of education in the richest decile. In Zimbabwe, most persons attended at least primary school; persons in the poorest decile have 5.4 years of education on average and persons in the richest decile 11.4 years.

In contrast, Niger is a country where few persons between 20 and 65 years of age attended school. 80 percent of the population have less than 1 year of education. The average number of years of education is 0.3 in the poorest decile, 0.9 in the eighth decile, 1.8 in the ninth decile, and 5.3 in the richest decile. In Ethiopia, 80 percent of the adult population have fewer than 2 years of education and in Sierra Leone, 70 percent have fewer than 2 years of education. Cambodia and Nepal are also countries where a large part of the population has relatively little formal education.

In other countries, the increase in the number of years of education from poorer to richer deciles is more pronounced. In Egypt, persons in the poorest decile have 3.1 years of education on average and those in the richest decile have 13.8 years of education. In India, the average number of years of education is 1.4 in the poorest decile and 11.9 in the richest decile. In Haiti, the respective numbers are 1.2 and 10.7 years of education. In Colombia, the average number of years of education ranges from 3.6 in the poorest decile to 12.5 in the richest decile.

The positive link between wealth and years of education at the household level can be explained similarly to the link between these two variables at the national level. Persons with a higher level of education can earn more than those with less education. At the same time, members of wealthier households can afford education more easily than members of poorer households. At the extreme end, very poor families may not only lack the financial resources to send their children to school, they may also have to rely on the income from child labor to guarantee the survival of everyone in the household. This relationship between household wealth and child labor was analyzed in two articles on child labor and school attendance in Bolivia.

Reference
  • Filmer, Deon, and Lant H. Pritchett. 2001. Estimating wealth effects without expenditure data - or Tears: An application to educational enrollments in states of India. Demography 38 (1), February: 115-132.
Related articles
External links
Friedrich Huebler, 24 August 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/08/hh-wealth.html
on No comments:

03 August 2008

National wealth and years of education

A country's national wealth and the education of its population are highly correlated. In developed countries with a high level of national income the population usually has more years of education than the population of low income countries. Countries with a highly educated work force can achieve higher economic growth rates and at the same time wealthy countries have the financial resources to invest more in education.

The relationship between national wealth and years of education can be illustrated with a comparison of national data on school life expectancy (SLE) and gross domestic product (GDP) per capita. The school life expectancy is the average number of years a child of school entrance age is expected to spend in primary, secondary or tertiary education. GDP per capita is the total value of all goods and services produced in a country, divided by its population.

The graph below plots the school life expectancy against GDP per capita in 2006, the year with the most recent data. The GDP data was adjusted with purchasing power parities (PPP) to account for differences in the price levels between countries. To emphasize the shape of the relationship with school life expectancy the GDP data is plotted on a logarithmic scale. In total, data for 175 countries was available. Each country is identified by a marker that indicates the Millennium Development Goal (MDG) region in which it is located.

The graph clearly demonstrates that GDP per capita is positively correlated with school life expectancy. The upper right corner of the graph is populated mainly by developed countries with a high GDP per capita and a long school life expectancy. The countries with the highest school life expectancy are Australia (SLE 20.5 years, GDP per capita $35,500), New Zealand (SLE 19.5 years, GDP per capita $25,500), and Iceland (SLE 18.2 years, GDP per capita $36,900). The countries with the lowest school life expectancy are Angola (SLE 3.7 years, GDP per capita $4,400), Niger (SLE 3.9 years, GDP per capita $630), and the Democratic Republic of the Congo (SLE 4.3 years, GDP per capita $280). The Democratic Republic of the Congo has the lowest GDP per capita of all countries with data.

GDP per capita and school life expectancy, 2006
Scatter plot of school life expectancy and GDP per capita in 175 countries
Data sources: UNESCO Institute for Statistics, World Bank, UN Population Division.

The following table lists the average school life expectancy, the average GDP per capita, and the total population in each MDG region and for the world as a whole. At the global level, the average school life expectancy is 11.5 years and the average GDP per capita is $9,300. Developed countries have the highest school life expectancy (15.8 years) and the highest GDP per capita ($33,500). Countries in Latin America and the Caribbean and members of the Commonwealth of Independent States (the former Soviet Union) also have a high school life expectancy (13.5 years and 13.4 years, respectively) but at lower levels of GDP per capita ($9,100 and $9,400).

In Northern Africa, the average school life expectancy is 12.2 years, with a GDP per capita around $5,400. In Eastern Asia, South-Eastern Asia, Oceania, and Western Asia, the school life expectancy ranges from 11 to 11.4 years. Western Asia, which includes the oil-rich countries of the Middle East, is the region with the second highest GDP per capita ($11,400) but school life expectancy is the third lowest of all ten MDG regions. Southern Asia has the second lowest school life expectancy with 9.6 years and an average GDP per capita of $2,600. The lowest school life expectancy is observed in Sub-Saharan Africa (7.7 years) and this region also has the lowest GDP per capita ($1,800).

MDG regions: school life expectancy, GDP per capita, and total population, 2006
MDG region School life expectancy (years) GDP per capita, PPP (current international $) Total population (1,000)
Developed countries 15.8 33,508 1,015,487
Commonwealth of Independent States 13.4 9,371 278,295
Eastern Asia 11.4 5,471 1,402,837
South-Eastern Asia 11.3 4,190 565,105
Oceania 11.4 2,323 8,804
Southern Asia 9.6 2,649 1,612,841
Western Asia 11.0 11,394 200,205
Northern Africa 12.2 5,433 155,086
Sub-Saharan Africa 7.7 1,818 788,122
Latin America and the Caribbean 13.5 9,109 564,732
World 11.5 9,262 6,591,513
Data sources: UNESCO Institute for Statistics, World Bank, UN Population Division. Regional averages are weighted by each country's total population.

A related article on this site analyzes the link between national wealth and school enrollment at the primary and secondary level of education. Countries with a high GDP per capita usually have higher net enrollment rates than countries with a low GDP per capita. This relationship is particularly strong at the secondary level of education. Two articles on poverty and educational attainment in the United States examine poverty rates and high school graduation rates in the 50 U.S. states.

Data sources
Related articles
External links
Friedrich Huebler, 3 August 2008 (edited 28 August 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/08/wealth.html
on No comments:

27 July 2008

A view inside primary schools

Cover of "A view inside primary schools" by UISA new publication by the UNESCO Institute for Statistics, A view inside primary schools: A World Education Indicators (WEI) cross-national study, presents new data on quality and equality in primary education. The data is from 11 countries in Asia, Latin America, and North Africa that participated in the Survey of Primary Schools by the World Education Indicators Programme in 2005 and 2006. For the survey, fourth grade teachers and principals from over 7,600 schools responded to questions about teaching and learning conditions.

The countries in the study - Argentina, Brazil, Chile, India, Malaysia, Paraguay, Peru, Philippines, Sri Lanka, Tunisia, and Uruguay - are close to the Millennium Development Goal of universal primary education. However, the survey reveals large resource gaps between schools in urban and rural areas. Children in poorly equipped and maintained schools often come from poor families and these children are thus doubly disadvantaged.

Other findings of the survey include:
  • In Paraguay, the Philippines, and Sri Lanka, more than one in five pupils attended schools without running water.
  • In India, Paraguay, Peru, the Philippines, Sri Lanka, and Tunisia, less than half of all pupils were in schools with a telephone.
  • Sri Lanka was the only country participating in the survey that provided free textbooks to virtually all pupils.
  • The overall weekly teaching load for Grade 4 teachers working in only one school ranged from 14 hours in Malaysia to 31 hours in Chile and the Philippines. The average teaching load was 23 hours per week.
  • In all countries in the survey - except in India, Malaysia, and Sri Lanka - most teachers expressed low levels of satisfaction with their salaries.
The full report, with detailed tables and figures, is available for download at the UIS website.

External links
Related articles
Friedrich Huebler, 27 July 2008 (edited 26 October 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/07/primary-schools.html
on No comments:

22 June 2008

Updates to two Stata guides

A new section on troubleshooting was added to the guide to integrating Stata and external text editors. The guide describes a set of programs that can be used to run Stata commands from an external text editor. The installation of these programs is straightforward and users should not encounter any problems if the installation instructions are followed exactly. In case the programs do not work, the new section offers simple steps to track down the source of the problem. The guide to reading Statalist with Gmail was also updated to include information on a new "fixed width font" feature of Gmail.

Friedrich Huebler, 22 June 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/06/stata-guides.html
on No comments:

15 June 2008

Adult literacy in 2007

The release of new literacy data by the UNESCO Institute for Statistics (UIS) in May 2008 provides an opportunity to update an article on adult literacy rates that was published on this site in July 2007. The adult literacy rate is the share of literate persons in the population aged 15 years and older. Compared to the previous analysis, literacy data for more countries and for more recent years is available. An article on literacy data from the UIS provides additional information on the latest UIS database.

Before the update of May, the UIS database contained adult literacy rates for 136 countries and territories. For 10 countries, the most recent data was from 2005, for 30 countries from 2004, and for 5 countries from 2003. The remaining countries had data from 2002 or earlier years.

The UIS Data Centre now offers the adult literacy rate for 145 countries and territories. For 115 countries, data from 2007 is available. The map below displays the adult literacy rate for all countries with data.

Adult literacy rates by country, 2007
World map with adult literacy rates by country in 2007
Source: UNESCO Institute for Statistics, Data Centre, May 2008

The unweighted mean of the adult literacy rate is 81.2 percent. In 71 countries - including most of Eastern Europe, East and Southeast Asia, and Latin America - 90 percent or more of the adult population can read and write. The highest adult literacy rate, 99.8 percent, is reported for Cuba, Estonia and Latvia. Most countries without data are in the group of industrialized countries, where literacy rates are also likely to be above 90 percent. In 23 countries, the adult literacy rate is between 80 and 90 percent.

At the other extreme are eight countries with literacy rates below 40 percent: Mali (23.3), Chad (25.7), Afghanistan (28.0), Burkina Faso (28.7), Guinea (29.5), Niger (30.4), Ethiopia (35.9), and Sierra Leone (38.1). Another 16 countries have literacy rates between 40 and 60 percent: Benin (40.5), Senegal (42.6), Mozambique (44.4), Central African Republic (48.6), Cote d'Ivoire (48.7), Togo (53.2), Bangladesh (53.5), Pakistan (54.9), Liberia (55.5), Morocco (55.6), Bhutan (55.6), Mauritania (55.8), Nepal (56.5), Papua New Guinea (57.8), Yemen (58.9), and Burundi (59.3). Almost all of these countries are in Sub-Saharan Africa and South Asia.

Finally, the world's two largest countries in terms of population have very different literacy rates. In China, the adult literacy rate is 93.3 percent. In India, only 66 percent of the adult population can read and write.

The complete dataset with adult and youth literacy rates is available at the UIS Data Centre.

Related articles
External links
Friedrich Huebler, 15 June 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/06/adult-literacy.html
on 2 comments:

01 June 2008

Literacy data from the UNESCO Institute for Statistics

In May 2008, the UNESCO Institute for Statistics (UIS) added new literacy data for many countries to its database at the UIS Data Centre. In total, 208 countries and territories are covered by the database. The adult literacy rate - the share of the population aged 15 years and above that can read and write - is available for 145 countries. For 115 countries, the most recent literacy data is from 2007. Historical data is also provided, going back as far as 1975, to allow the analysis of national trends in literacy.

The previous UIS database from 2007 listed the adult literacy rates for 136 countries and territories for years between 1985 and 2005. For 10 countries, the most recent data was from 2005, for 30 countries from 2004, and for 5 countries from 2003.

The graph below describes the availability of data on adult literacy in the UIS database as of late May 2008.
  • The blue bars indicate the number of countries with data on adult literacy per year between 1975 and 2007. For each country, the adult literacy rate may be available in more than one year. The number of countries with data from a particular year is shown at the bottom of the bars, along the horizontal axis. For example, 115 countries have literacy data from 2007 and 36 countries have data from 2000.
  • The brown bars show the number of countries with adult literacy rates from the current year or the previous 4 years. For example, the bar for the year 2007 indicates that 117 countries have literacy data from any year between 2003 and 2007.
  • The beige bars show the cumulative number of countries with literacy data from any year since 1975. For example, in 2007, the adult literacy rate is available for a total of 145 countries and territories. The difference between the beige and brown bars in 2007 is the number of countries with the most recent literacy data from a year before 2003. The difference between the beige and blue bars in 2007 is the number of countries with the most recent data from a year before 2007.
Data on adult literacy from the UNESCO Institute for Statistics, 1975-2007
Bar chart showing availability of data on adult literacy from 1975 to 2007
Source: UNESCO Institute for Statistics, Data Centre, May 2008

Related articles
External links
Friedrich Huebler, 1 June 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/06/uis-literacy.html
on 5 comments: