International Education Statistics

Global Education Digest 2011

2011-10-30T23:30:00.001-04:00

The UNESCO Institute for Statistics (UIS) announced the publication of the Global Education Digest 2011. The focus of this year's edition of the GED is on secondary education.

Growing enrolment in primary education over past decades - partly due to the emphasis on universal primary education by the Millennium Development Goals and Education for All - has led to increased demand for secondary education. The Global Education Digest 2011describes trends in participation in and completion of lower and uppersecondary education from 1970 to the present, as well as disparities inaccess to education of children of secondary school age. The GED alsocontains analysis of data on educational attainment, technical andvocational education and training, secondary school teachers, andeducation finance.

The analytical chapter is accompanied by 200pages of statistical tables on pre-primary, primary, secondary andtertiary education. The GED 2011 introduces several new tables that didnot appear in previous editions. Table 5 lists national, regional and global estimates of the number and percentof children of primary and lower secondary school age out of school.Table 19 introduces a new indicator of educational attainment, thepercentage of the population 25 years and older with at least completedprimary, lower secondary, upper secondary, post-secondary, or tertiaryeducation. All data from the statistical annex will also be availablein the UIS Data Centre.

Reference

UNESCO Institute for Statistics (UIS). 2011. Global education digest 2011: Comparing education statistics across the world. Montreal: UIS. (Download in PDF format, 7.5 MB)

External links

Friedrich Huebler, 30 October 2011 (edited 31 October 2011), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/10/ged.html

Adult and youth literacy in 2009

2011-09-30T23:53:00.000-04:00

8 September was International Literacy Day. On this occasion, the UNESCO Institute for Statistics (UIS) released a fact sheet with estimates of adult and youth literacy in 2009, the most recent year with data.

Theglobal adult literacy rate, for the population 15 years and older, was83.7% in 2009, compared to 83.4% in 2008. The adult illiteratepopulation fell from 796.2 million in 2008 to 793.1 million in 2009.64.1% of the adult illiterate population were women. Adult literacyrates are lowest in sub-Saharan African and in South and WestAsia (see Figure 1). In 11 countries, less than half of the adultpopulation were able to read and write: Benin, Burkina Faso, Chad,Ethiopia, Gambia, Guinea, Haiti, Mali, Niger, Senegal and Sierra Leone.

Figure 1: Adult literacy rate, 2009

Source: UNESCO Institute for Statistics, 2011

Youth literacy rates - for the population 15 to 24 years - aregenerally higher than adult literacy rates, due to increased school attendance rates amongyounger generations. The global youth literacy rate was 89.3% in 2009,compared to 89.0% in 2008. The youth illiterate population fell from130.6 million in 2008 to 127.3 million in 2009. Youth literacy rates are lowest in sub-Saharan Africa(see Figure 2) and the five countries worldwide with youth literacy rates below 50%are from this region: Burkina Faso, Chad, Ethiopia, Mali and Niger.

Figure 2: Youth literacy rate, 2009

Source: UNESCO Institute for Statistics, 2011

Reference

UNESCO Institute for Statistics (UIS). 2011. Adult and youth literacy. UIS fact sheet no. 16, September. Montreal: UIS. (Download in PDF format, 350 KB)

External links

Friedrich Huebler, 30 September 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/09/literacy.html

New version of programs to integrate Stata with an external text editor

2011-08-14T23:27:00.002-04:00

I released a new version of the rundo and rundolines programs to integrate the Stata statistical package with an external text editor. Version 4 of the programs supports Stata 12, released in July 2011, as well as previous versions of Stata. Users who upgrade from an older version of Stata to Stata 12 must install the new rundo and rundolines programs. The old programs are not compatible with Stata 12 because some keyboard shortcuts in Stata have changed. Users of Stata 8 to 11 can continue to use version 3.1 of rundo and rundolines.

Related articles

External links

Stata (official site)

Friedrich Huebler, 14 August 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/08/stata.html

School attendance by grade and age in Liberia

2011-07-31T23:56:00.004-04:00

The article "Overage pupils in primary and secondary education" of June 2011 summarized data on school attendance from 36 countries and found that overage school attendance is common in sub-Saharan Africa. The countries with the highest share of overage pupils in the sample were Haiti, Liberia, Uganda, Rwanda, Cambodia, Ethiopia, Ghana, Madagascar, and Malawi. In Liberia, 93% of all pupils in primary and secondary education are at least one year overage for their grade and 84% are at least two years overage. This article takes a closer look at Liberia by analyzing data from the same Demographic and Health Survey (DHS) from 2007 that was analyzed for the earlier article.

The official primary school age in Liberia, as defined by the International Standard Classification of Education (ISCED), is 6 to 11 years. The official secondary school age is 12 to 17 years. Given these school ages, a 6-year-old in grade 1 and a 7-year-old in grade 2 are in the right grade for their age. A 7-year-old in grade 1 would be one year overage and an 8-year-old in grade 1 would be two years overage. A 5-year-old in grade 1 would be one year underage.

The graph below shows the age distribution of pupils in primary and secondary education in Liberia. Pupils who are in the right grade for their age or underage are in a small minority. In the first twelve grades, their share never exceeds 9%. By contrast, as many as 98% of all pupils in a single grade are overage. The degree of overage attendance is astounding: 5% of all first graders are 9 or more years overage, meaning that they start primary school at age 15 or later. 19% of all first graders are at least 7 years overage and 44% are at least 5 years overage. In grade 8, 18% of all pupils are 9 or more years overage; while the official age for eighth graders is 13 years, one in five pupils in that grade in Liberia is 22 years or older.

Age distribution of pupils in primary and secondary education in Liberia, 2007

Source: Demographic and Health Survey (DHS) 2007.

What are the reasons for this high prevalence of overage school attendance? In Liberia, as in other countries of sub-Saharan Africa, many pupils enter school late for a variety of reasons that include poverty, a scarcity of educational facilities, and lack of enforcement of the official school ages. High repetition rates further exacerbate the problem of overage school attendance. Among the consequences of this age structure in school are a higher probability of dropout and reduced lifetime earnings caused by incomplete education or late entry into the labor market.

Related articles

External links

Friedrich Huebler, 31 July 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/07/liberia.html

Overage pupils in primary and secondary education

2011-06-30T21:28:00.011-04:00

Pupils can be overage for their grade for two reasons: late entry and repetition. Take for example a country where children are expected to enter primary school at 6 years of age. If a child enters grade 1 at age 7, he or she is one year overage for the grade. A child who enters grade 1 at age 8 and repeats the grade will be three years overage for the grade; two of the three years are due to late entry and the third year is due to repetition.

Children who are many years overage are less likely to complete their education. If they stay in school, they graduate later than pupils who entered school at the official starting age. These overage graduates enter the labor market late and often with lower educational attainment. As a consequence, they are likely to have lower cumulative earnings over their lifetime than persons who graduated and entered the labor market at a younger age and with higher educational attainment. For the country as a whole this in turn means reduced national income and slower economic growth.

Overage school attendance is common in sub-Saharan Africa but also occurs in other regions. The figure below shows data from 36 nationally representative household surveys that were conducted between 2004 and 2009. 34 of these surveys were Demographic and Health Surveys (DHS) and the remaining two surveys, those for Bangladesh and Kyrgyzstan, were Multiple Indicator Cluster Surveys (MICS). For each country, the graph shows the share of children in primary and secondary education who are at least one or two years overage for their grade. The entrance ages and durations of primary and secondary education used in this study are those specified by the International Standard Classification of Education (ISCED).

Percentage of children in primary and secondary education who are at least 1 or 2 years overage for their grade

Source: Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), 2004-2009.

In the sample of 36 countries, the share of children who are at least one year overage for their grade ranges from 5 percent in Armenia to 95 percent in Haiti. Other countries where at least three out of four pupils in primary or secondary education are overage include Liberia (93%), Uganda (86%), Rwanda (83%), Cambodia (78%), Mozambique (76%), and Ethiopia (75%). In addition to Armenia, the percentage of pupils who are at least one year overage is below 10 percent in Moldova and Egypt (8%).

The share of children in primary and secondary education who are at least two years overage for their grade ranges from 1 percent in Armenia to 85 percent in Haiti. In addition to Haiti, at least half of all pupils are two or more years overage in Liberia (84%), Uganda (67%), Rwanda (65%), Ethiopia (59%), Cambodia (55%), Malawi (51%), and Madagascar (50%). On average, the share of children who are at least two years overage is 19 percent less than the share of children who are at least one year overage.

However, there are exceptions. In Albania and the Ukraine, 43 and 26 percent respectively of all children in primary and secondary education are at least one year overage. By contrast, only 5 and 2 percent respectively are at least two years overage. This means that in these two countries, a relatively large number of children enter school one year late or repeat one grade, but hardly any children enter school two years late or repeat more than one grade. Late entry and repetition are therefore less likely to have negative consequences on lifetime earnings and national income in Albania and the Ukraine than in other countries.

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External links

Friedrich Huebler, 30 June 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/06/age.html

Education finance in sub-Saharan Africa

2011-05-31T23:53:00.011-04:00

A new report by the UNESCO Institute for Statistics, Financing education in sub-Saharan Africa, presents comprehensive data for the past decade for 45 African countries.

The number of children enrolled in primary school in sub-Saharan Africa grew from 87 million in 2000 to 129 million in 2008, an increase of 48 percent. Over the 1999-2009 decade, real public expenditure on education, adjusted for inflation, grew on average by 6.1 percent per year, based on data from 26 countries. The highest annual growth rates of education spending in sub-Saharan Africa, over 12 percent, were observed in Mozambique and Burundi. Of the countries with data, only the Central African Republic experienced a decline in public expenditure on education.

The countries of sub-Saharan Africa combined spend 5.0 percent of their GDP on education, the second highest value of the eight EFA regions, after North America and Western Europe, where 5.3 percent of the regional GDP is spent on the education sector.

The figure below shows data on education expenditure in 28 countries in sub-Saharan Africa. The horizontal axis indicates a country's total public expenditure as a percentage of gross domestic product (GDP). The vertical axis indicates a country's total public expenditure on education as a percentage of total public expenditure. Total public expenditure on education as a percentage of GDP can be calculated as the product of the two values plotted along the vertical and horizontal axes.

Public education expenditure / GDP =
(Public education expenditure / Total public expenditure) × (Total public expenditure / GDP)

The three curves in the graph indicate where total public expenditure on education is equal to 2, 5 or 10 percent of GDP. Countries with higher expenditures on education as a percentage of GDP are found near the upper right corner of the graph, countries with lower expenditures near the lower left corner. For the countries in the graph, public expenditure on education as a percentage of GDP ranges from 1.3 percent in the Central Africal Republic to 12.4 percent in Lesotho.

Total public expenditure on education as a percentage of total public expenditure in relation to total public expenditure as a percentage of GDP

Source: UIS 2011, page 30, Figure 11

Reference

UNESCO Institute for Statistics (UIS). 2011. Financing education in sub-Saharan Africa: Meeting the challenges of expansion, equity and quality. Montreal: UIS. (Download in PDF format, 8.7 MB)

External links

Friedrich Huebler, 31 May 2011 (edited 1 June 2011), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/05/ssa.html

Update to "Integrating Stata and external text editors"

2011-04-17T23:36:00.023-04:00

The guide to integrating Stata with an external text editor has been revised. The rundo and rundolines programs were updated to support Stata version 11.2, which was released on 30 March 2011. Some links in the guide were also updated.

External links

Stata (official site)

Friedrich Huebler, 17 April 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/04/stata.html

Education for All regions

2011-03-26T18:24:00.004-04:00

For monitoring of progress towards the six Education for All (EFA) goals, the world has been divided into eight EFA regions:

North America and Western Europe
Central and Eastern Europe
Central Asia
East Asia and the Pacific
South and West Asia
Arab States
Sub-Saharan Africa
Latin America and the Caribbean

These regions, shown in the map below, are used in publications like the EFA Global Monitoring Report by UNESCO or the Global Education Digest by the UNESCO Institute for Statistics.

Regions for monitoring of Education for All goals

Combined, the eight EFA regions cover 204 countries and territories. Two EFA regions - East Asia and the Pacific, and Latin America and the Caribbean - are further divided into two sub-regions.

Composition of EFA regions

North America and Western Europe (26 countries and territories)
Andorra, Austria, Belgium, Canada, Cyprus, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Israel, Italy, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Sweden, Switzerland, United Kingdom, United States.
Central and Eastern Europe (21 countries)
Albania, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Montenegro, Poland, Republic of Moldova, Romania, Russian Federation, Serbia, Slovakia, Slovenia, The former Yugoslav Republic of Macedonia, Turkey, Ukraine.
Central Asia (9 countries)
Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, Uzbekistan.
East Asia and the Pacific (33 countries and territories)
East Asia (16 countries and territories)
Brunei Darussalam, Cambodia, China, Democratic People's Republic of Korea, Indonesia, Japan, Lao People's Democratic Republic, Macao (China), Malaysia, Myanmar, Philippines, Republic of Korea, Singapore, Thailand, Timor-Leste, Viet Nam.
Pacific (17 countries and territories)
Australia, Cook Islands, Fiji, Kiribati, Marshall Islands, Micronesia (Federated States of), Nauru, New Zealand, Niue, Palau, Papua New Guinea, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu, Vanuatu.
South and West Asia (9 countries)
Afghanistan, Bangladesh, Bhutan, India, Iran (Islamic Republic of), Maldives, Nepal, Pakistan, Sri Lanka.
Arab States (20 countries and territories)
Algeria, Bahrain, Djibouti, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libyan Arab Jamahiriya, Mauritania, Morocco, Occupied Palestinian Territory, Oman, Qatar, Saudi Arabia, Sudan, Syrian Arab Republic, Tunisia, United Arab Emirates, Yemen.
Sub-Saharan Africa (45 countries)
Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo, Côte d'Ivoire, Democratic Republic of the Congo, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritius, Mozambique, Namibia, Niger, Nigeria, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, Swaziland, Togo, Uganda, United Republic of Tanzania, Zambia, Zimbabwe.
Latin America and the Caribbean (41 countries and territories)
Latin America (19 countries)
Argentina, Bolivia (Plurinational State of), Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, Venezuela (Bolivarian Republic of).
Caribbean (22 countries and territories)
Anguilla, Antigua and Barbuda, Aruba, Bahamas, Barbados, Belize, Bermuda, British Virgin Islands, Cayman Islands, Dominica, Grenada, Guyana, Haiti, Jamaica, Montserrat, Netherlands Antilles, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Suriname, Trinidad and Tobago, Turks and Caicos Islands.

References

UNESCO. 2011. EFA Global Monitoring Report 2011: The hidden crisis: Armed conflict and education. Paris: UNESCO. Annex, p. 269. (Download in PDF format, 6.4 MB)
UNESCO Institute for Statistics (UIS). 2010. Global education digest 2010: Comparing education statistics across the world. Montreal: UIS. Annex, p. 274-275. (Download in PDF format, 8 MB)

External links

Friedrich Huebler, 26 March 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/03/efa.html

EFA Global Monitoring Report 2011

2011-03-06T16:13:00.003-05:00

The Education for All Global Monitoring Report 2011 was released by UNESCO on 1 March 2011. This year's edition of this annual report has the title The hidden crisis: Armed conflict and education. The report documents the impact of violent conflict on education and the long-lasting negative effects on educational attainment and literacy.

Today, 28 million or over 40 percent of all children out of school (67 million worldwide) live in countries affected by conflict, although these countries are home to only 116 million or 18 percent of the global population of primary school age (653 million) (see Figure 1). (Only out-of-school children in low and lower-middle income conflict-affected countries were counted to arrive at the total of 28 million. In addition, for large countries like India, Indonesia, Nigeria and Pakistan, only children living in conflict-affected areas were included in the 28 million children affected by conflict.) In conflict areas, the out-of-school rate is around 24 percent, compared to 7 percent in other parts of the world. Children affected by armed conflict are thus more than three times as likely to be out of school as other children.

Conflict-affected countries also have some of the lowest levels of literacy. In these countries, only 79 percent of youth between 15 and 24 years and 69 percent of adults are literate, compared to 93 percent of youth and 85 percent of adults in other countries.

War does not only destroy lives and schools, it also diverts resources from education to military spending. The Global Monitoring Report documents how lack of access to education or exposure to the wrong kind of education can contribute to persistent inequality, prejudice and renewed armed conflict, a vicious cycle that is difficult to break.

Lastly, the Global Monitoring Report 2011 examines the role of development assistance in conflict-affected countries and argues for increased and more effective aid for the education sector.

Figure 1: Population of primary school age and children out of school in countries affected and not affected by armed conflict, 2008

Source: UNESCO 2011, pages 132, 308, 309; author's calculations.

Reference

UNESCO. 2011. EFA Global Monitoring Report 2011: The hidden crisis: Armed conflict and education. Paris: UNESCO. (Download in PDF format, 6.4 MB)

External links

Friedrich Huebler, 6 March 2011 (edited 26 March 2011), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/03/gmr.html

UIS time series with education data since 1970

2011-02-27T23:52:00.004-05:00

The UNESCO Institute for Statistics (UIS) has released new time series with education data for the years since 1970. Until this release, most indicators in the UIS Data Centre only had data for 1999 and later years, except for literacy, for which the UIS offered data for the period since 1975. The historical data are compliant with the International Standard Classification of Education (ISCED) of 1997 and therefore comparable with existing post-1998 data in the UIS Data Centre.

With the new release, the UIS now offers data for the past 40 years for the following indicators:

Entry age and duration of pre-primary, primary and secondary education
School age population of pre-primary, primary, secondary and tertiary age
Enrolment in pre-primary, primary, secondary and tertiary education
Gross enrolment ratio (GER) for pre-primary, primary, secondary and tertiary education
Net enrolment rate (NER) for primary education
New entrants to primary education
Gross intake ratio for primary education
Repeaters in primary and secondary education
Gross intake rate to the last grade of primary education
School life expectancy
Teaching staff in pre-primary, primary, secondary and tertiary education
Pupil/teacher ratio in pre-primary, primary and secondary education

As an example for the expanded coverage, Figure 1 shows the gross enrolment ratio in primary education for China, India, Indonesia, Nigeria and the United States, the five countries with the largest population of primary school age in 2010, for the period 1970-2009. Figure 2 shows how school life expectancy evolved in these countries over the same period.

Figure 1: Gross enrolment ratio (GER) in primary education, 1970-2009

Source: UIS Data Centre, February 2011

Figure 2: School life expectancy, primary to tertiary education, 1970-2009

Source: UIS Data Centre, February 2011

The time series can be retrieved from the UIS Data Centre, under "Predefined Tables" and "Education". Data for the years 1970 to 1998 are in Tables 21 to 26, and data for 1999 and following years are in Tables 1 to 20H.

As an example, the primary GER in Figure 1 is available in Tables 5 (for 1970-1998) and 23 (for 1999-2009). To create a complete time series for 1970-2009, the data from Tables 5 and 23 must be merged after download from the Data Centre. Data on school life expectancy are in Tables 8 and 22.

Related articles

External links

Friedrich Huebler, 27 February 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/02/hist.html

Educational attainment in the United States, 1940-2009

2011-01-03T19:38:00.003-05:00

In the United States, the level of education of the adult population has increased steadily since the middle of the 20th century. The share of the population 25 years and over who attended college increased from 10 percent in 1940 to 56 percent in 2009. 30 percent of the population in this age group had completed 4 or more years of college in 2009. The share of the population with only elementary education or no formal schooling fell from 60 percent in 1940 to 6 percent in 2009. High school reached its peak as the most common level of education in the 1970s and 1980s, with a share around 50 percent, but younger cohorts are more likely to continue their education at the post-secondary level.

This increase in educational attainment of the work force has contributed to a strengthening of U.S. competitiveness in the global economy. At the same time, the increased demand for highly skilled workers emphasizes the importance of secondary and higher education for individuals in search of employment.

The trends in years of schooling of the adult U.S. population from 1940 to 2009 are visualized in the figure below. The table that follows lists data for selected years. The data on educational attainment were collected with the Current Population Survey (CPS), a joint survey by the Bureau of Labor Statistics and the Census Bureau that has been conducted since 1940.

Years of school completed by population 25 years and over, 1940-2009

Source: U.S. Census Bureau, September 2010

Years of school completed by population 25 years and over, 1940-2009

Years of school	Percent of population
Years of school	1940	1950	1960	1970	1980	1990	2000	2009
0 to 4 years elementary school	13.5	10.8	8.3	5.3	3.4	2.4	1.6	1.4
5 to 8 years elementary school	46.0	36.1	31.4	22.4	14.1	8.8	5.4	4.1
1 to 3 years high school	15.0	16.9	19.2	17.1	13.9	11.2	8.9	7.9
4 years high school	14.1	20.1	24.6	34.0	36.8	38.4	33.1	31.1
1 to 3 years college	5.4	7.1	8.8	10.2	14.9	17.9	25.4	26.1
4 or more years college	4.6	6.0	7.7	11.0	17.0	21.3	25.6	29.5

Source: U.S. Census Bureau, September 2010

Data source

U.S. Census Bureau, CPS historical time series tables, September 2010, Table A-1, "Years of school completed by people 25 years and over, by age and sex: Selected years 1940 to 2009" (Excel file, 85 kB; CSV file, 47 kB)

External links

Friedrich Huebler, 3 January 2011, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2011/01/usa.html

Mobile version of International Education Statistics blog

2010-12-17T07:10:00.006-05:00

The International Education Statistics blog is now available in a version formatted for mobile devices. If you access the blog on an iPhone, Android phone or similar device, the site will be displayed differently. The navigation bar, the tags and other elements are removed, graphs are reformatted to fit the smaller screen of mobile devices, and navigation is simplified. The mobile version of the blog can be viewed at http://huebler.blogspot.com/?m=1. The bottom of each page on the mobile version has a link to the web version of the blog.

Screenshot of mobile version of blog

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Friedrich Huebler, 17 December 2010 (edited 18 December 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/12/mobile.html

Children out of school: Global trend 1999-2008

2010-11-30T23:50:00.006-05:00

68 million children of primary school age were out of school in 2008 according to estimates by the UNESCO Institute for Statistics (UIS). Compared to 1999, when 106 million children were out of school, this is a decrease of over 38 million (see Figure 1). However, in spite of the observed progress over the last decade, the Millennium Development Goal of universal primary education by 2015 will not be reached if current trends continue unchanged.

Figure 1: Children of primary school age out of school, 1999-2008

Source: UNESCO Institute for Statistics, Data Centre, November 2010.

The UIS also publishes data on the regional distribution of children out of school, but complete data are only available until 2007. 43 percent - 30.4 million - of all children out of school in 2007 lived in sub-Saharan Africa (see Figure 2). A further 25 percent - 17.7 million - lived in South and West Asia. These two regions combined accounted for two thirds of the global out-of-school population. The shares of the remaining regions were as follows: 13 percent of all children out of school lived in East Asia and the Pacific, 9 percent in the Arab States, 4 percent in Latin America and the Caribbean, 3 percent in North America and Western Europe, 2 percent in Central and Eastern Europe, and less than 1 percent in Central Asia.

Figure 2: Regional distribution of children out of school, 2007

Source: UNESCO Institute for Statistics, Data Centre, November 2010.

Regional and global estimates of the number of children out of school can be obtained from the UIS Data Centre. On the main Data Centre page at stats.uis.unesco.org, click on Predefined Tables and then Education. Table 20H, "Regional sum of primary school age children out of school", lists the total, male and female number of children of primary school age out of school for the period 1999 to 2008.

Related articles

External links

Friedrich Huebler, 30 November 2010 (edited 17 December 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/11/oos.html

UN Millennium Development Goals Report 2010

2010-10-31T23:29:00.001-04:00

On 20-22 September 2010, world leaders met at the United Nations in New York on the occasion of the 10-year anniversary of the Millennium Summit of 2000. One outcome of the 2000 Summit was the adoption of eight Millennium Development Goals (MDGs).

Eradicate extreme poverty and hunger
Achieve universal primary education
Promote gender equality and empower women
Reduce child mortality
Improve maternal health
Combat HIV/AIDS, malaria and other diseases
Ensure environmental sustainability
Develop a global partnership for development

Progress toward the MDGs is documented in the annual Millennium Development Goals Report by the United Nations. The 2010 report contains statistics and analysis for each of the eight goals. For the goal of universal primary education by 2015, "hope dims" according to the report. Although enrollment rates continue to grow worldwide, 69 million children of primary school age were still out of school in 2008, the most recent year with data. Almost three quarters of all out-of-school children lived in two regions: sub-Saharan Africa (31 million) and Southern Asia (18 million).

Reference

United Nations. 2010. The millennium development goals report 2010. New York: United Nations. (Download PDF, 8.5 MB)

External links

Millennium Development Goals (United Nations)
Millennium Development Goals (United Nations Development Programme)
Millennium Development Goals Indicators
MDG Monitor
Millennium Campaign

Friedrich Huebler, 31 October 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/10/mdg.html

Global Education Digest 2010

2010-09-19T23:35:00.002-04:00

On 17 September, the UNESCO Institute for Statistics (UIS) announced the publication of the Global Education Digest 2010. This year's edition of the GED focuses on gender and education.

The Millennium Development Goals (MDGs) call for the elimination of gender disparity at all levels of education by 2015 but according to the GED, only 85 of 157 countries with data will have reached gender parity in primary and secondary education by 2015, if current trends continue. 23 countries are unlikely to reach the goal at the primary level and 63 countries are unlikely to do so at the secondary level.

Gender disparities in access to education are greatest in sub-Saharan Africa, South and West Asia, and to a lesser extent in the Arab States. In these regions, fewer girls than boys are enrolled in primary, secondary and tertiary education. The opposite - gender disparity in favor of girls - can be observed in tertiary education in Central and Eastern Europe, Central Asia, Latin America and the Caribbean, and North America and Western Europe.

Other topics discussed in the Global Education Digest 2010 include: the differences between boys and girls in terms of progression through and completion of primary and secondary education; the interaction between gender, socio-economic status, geographic location, ethnicity and other factors as determinants of participation in education; differences in learning achievement of boys and girls; trends in adult literacy; women's choice of field of study at the tertiary level of education; and national education policies.

The statistical tables in the GED were updated with data up to 2008 for most indicators. All data are also available at the UIS Data Centre.

Reference

UNESCO Institute for Statistics (UIS). 2010. Global education digest 2010: Comparing education statistics across the world. Montreal: UIS. (Download in PDF format, 8 MB)

External links

Friedrich Huebler, 19 September 2010 (edited 20 September 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/09/ged.html

Trends in adult literacy, 1990-2008

2010-09-08T00:09:00.005-04:00

8 September is International Literacy Day, which was first celebrated in 1966. New estimates of adult and youth literacy by the UNESCO Institute for Statistics (UIS) show that the percentage of literate persons continues to grow worldwide. Even so, in 2008, 796 million adults aged 15 years or older - 17% of all adults worldwide - still lacked basic reading and writing skills and 64% of them were women (see UIS fact sheet on adult and youth literacy). By comparison, 24% of all adults were illiterate in 1990.

Figure 1 displays how the adult literacy rate and the associated gender parity index (GPI) have evolved between 1990 and 2008 for the 10 Millennium Development Goal regions and for the world as a whole. The gender parity index is the ratio of the female over the male literacy rate. For example, the female and male literacy rate in 2008 - 78.9% and 88.2%, respectively - yield a GPI of 0.9 (see Table 1). A GPI between 0.97 and 1.03 is usually considered gender parity. At GPI values below 1, women are disadvantaged and at GPI values above 1, men are disadvantaged. If a country or region reaches universal literacy, with male and female literacy rates of 100%, the GPI must be 1 by definition. This can be seen in the developed regions and in the countries of the Commonwealth of Independent States (CIS), both of which are near universal literacy with a GPI of 1.

Figure 1: Adult literacy rate and gender parity, 1990-2008

Data source: UNESCO Institute for Statistics, Data Centre, September 2010.

At the global level, both the adult literacy rate and gender parity improved over the past 20 years. The literacy rate grew from 76% in 1990 to 83% in 2008 and the GPI from 0.84 to 0.90 (see Table 1). Progress was especially strong in Northern Africa, where the adult literacy rate increased by 20%, and in Eastern and Southern Asia, which saw an increase of 15%. In Northern Africa and Southern Asia less than half of all adults were literate in 1990, less than in any other region. In 2008, the lowest literacy rates were observed in Southern Asia and sub-Saharan Africa, with 62% and 63%, respectively. However, even sub-Saharan Africa managed to increase the share of adults with basic reading and writing skills by 9% between 1990 and 2008. In the remaining regions, the increase in the adult literacy rate over the past two decades was as follows: Western Asia 11%; South-Eastern Asia, and Latin America and the Caribbean 7%; Oceania 4%; CIS 1%; and the developed regions 0.3%. The rate of increase in the developed regions and in the CIS countries was neglible because both regions had already reached near-universal adult literacy in 1990. Literacy rates are also high in Eastern Asia, South-Eastern Asia, and Latin America and the Caribbean; in all three regions more than 9 out of 10 adults are able to read and write.

Gender parity also improved in all MDG regions, with Northern Africa again showing the biggest increase, from 0.57 in 1990 to 0.76 in 2008, followed by Eastern Asia and Southern Asia, where the GPI increased by 0.14 over the same period. In spite of this increase, Southern Asia continues to exhibit relatively high gender disparity in adult literacy, with a GPI of 0.70. The UIS reports similar disparities for sub-Saharan Africa (0.75) and Northern Africa (0.76). In the other regions the GPI for adult literacy was as follows in 2008: Western Asia 0.84, Oceania 0.89, Eastern Asia 0.94, South-Eastern Asia 0.95, and CIS and the developed regions 1.00.

Table 1: Adult literacy rate and gender parity, 1990-2008

MDG region	Year	Adult literacy rate (%)
MDG region	Year	Total	Male	Female	GPI
Developed regions	1990	98.7	99.0	98.4	0.99
	2008	99.0	99.2	98.9	1.00
Commonwealth of Independent States	1990	98.1	99.4	97.1	0.98
	2008	99.5	99.7	99.4	1.00
Eastern Asia	1990	78.9	87.7	69.7	0.80
	2008	93.8	96.8	90.7	0.94
South-Eastern Asia	1990	84.8	90.0	80.0	0.89
	2008	91.9	94.5	89.5	0.95
Southern Asia	1990	47.3	60.1	33.5	0.56
	2008	61.9	73.2	50.9	0.70
Western Asia	1990	73.8	84.2	62.6	0.74
	2008	84.5	91.5	76.9	0.84
Northern Africa	1990	47.8	60.8	34.6	0.57
	2008	67.3	76.7	58.1	0.76
Sub-Saharan Africa	1990	53.1	63.7	43.1	0.68
	2008	62.5	71.6	53.6	0.75
Latin America and the Caribbean	1990	84.4	85.9	82.8	0.96
	2008	91.0	91.9	90.3	0.98
Oceania	1990	62.9	68.9	56.5	0.82
	2008	66.4	70.2	62.6	0.89
World	1990	75.7	82.2	69.2	0.84
	2008	83.4	88.2	78.9	0.90

Data source: UNESCO Institute for Statistics, Data Centre, September 2010.

National and regional literacy rates can be obtained from the UIS Data Centre. From the main Data Centre page at stats.uis.unesco.org, click on Predefined Tables and then Literacy. National literacy rates are available for the years 1975 to 2008. Regional and global literacy rates are presented by census decade, from 1985-1994 to 2005-2008.

Related articles

External links

Friedrich Huebler, 8 September 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/09/lit.html

Update to "Integrating Stata and external text editors"

2010-08-31T22:46:00.008-04:00

The guide to integrating the Stata statistical package with an external text editor has been updated. One more screenshot was added to the instructions and the list of supported editors was revised. The rundo and rundolines programs have been confirmed to work with Crimson Editor, EditPlus, EmEditor, Notepad++, PSPad, TextPad, TeXnicCenter, and UltraEdit. In addition, previous versions of the programs were reported to work with gVim, Hidemaru, jEdit, SciTE, Vim, and WinEdt.

External links

Stata, official site

Friedrich Huebler, 31 August 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/08/stata.html

Review of the International Standard Classification of Education (ISCED)

2010-07-30T21:31:00.002-04:00

The International Standard Classification of Education (ISCED) was developed by UNESCO in the 1970s as a framework for the international comparison of national education statistics and indicators. The current version of ISCED was adopted in 1997. The text of the classification is available on the website of the UNESCO Institute for Statistics (UIS) in the six official UN languages.

Figure 1: Cover of ISCED 1997 in English, French, Spanish, Russian, Arabic and Chinese

Table 1 lists the seven levels of education defined in ISCED 1997: pre-primary (level 0), primary (level 1), lower secondary (level 2), upper secondary (level 3), post-secondary non-tertiary (level 4), first stage of tertiary (level 5), and second stage of tertiary (level 6).

Table 1: Levels of education in ISCED 1997

ISCED level	Description
0	Pre-primary education Initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment.
1	Primary education Normally designed to give pupils a sound basic education in reading, writing and mathematics.
2	Lower secondary education The lower secondary level of education generally continues the basic programmes of the primary level, although teaching is typically more subject-focused, often employing more specialised teachers who conduct classes in their field of specialisation.
3	Upper secondary education The final stage of secondary education in most countries. Instruction is often more organised along subject-matter lines than at ISCED level 2 and teachers typically need to have a higher level, or more subject-specific, qualification than at ISCED 2.
4	Post-secondary non-tertiary education These programmes straddle the boundary between upper secondary and postsecondary education from an international point of view, even though they might clearly be considered as upper secondary or post-secondary programmes in a national context. They are often not significantly more advanced than programmes at ISCED 3 but they serve to broaden the knowledge of participants who have already completed a programme at level 3. The students are typically older than those in ISCED 3 programmes. ISCED 4 programmes typically have a duration of 6 months to 2 years.
5	First stage of tertiary education ISCED 5 programmes have an educational content more advanced than those offered at levels 3 and 4. ISCED 5A programmes are largely theoretically based and are intended to provide sufficient qualifications for gaining entry into advanced research programmes and professions with high skills requirements. ISCED 5B programmes are generally more practical/technical/occupationally specific than ISCED 5A programmes.
6	Second stage of tertiary educationThis level is reserved for tertiary programmes that lead to the award of an advanced research qualification. The programmes are devoted to advanced study and original research.

Source: UIS, 2009, Global education digest 2009, Annex C

To assign national education programmes to internationally comparable ISCED levels, ISCED mappings are produced by the UIS in collaboration with national authorities in UNESCO member states. As an example, Figure 2 shows the ISCED mapping for Mozambique. The columns on the left half of the table list national education programmes, and the right half of the table lists the corresponding ISCED levels, from pre-primary to tertiary education. The information on ISCED levels is used to generate internationally comparable data on primary or secondary school enrolment and other indicators. For example, UIS estimates on the number of children out of school are produced by referring to primary and lower secondary school ages defined by ISCED.

Figure 2: ISCED mapping for Mozambique

Source: ISCED mappings, UIS, July 2010

Changes in national education systems since the adoption of ISCED 1997, as well as problems with its implementation, made it necessary to review the existing classification. At the UNESCO General Conference in October 2007, the UIS was appointed to lead such a review. In 2009 and 2010, an international panel of experts discussed the current classification and drafted a new ISCED. The most important areas under review were the classification of post-secondary and tertiary education, criteria to define the orientation (general or vocational) and destination (labour market or further education) of secondary education, the coverage of early childhood care and education (ECCE) and of technical and vocational education and training (TVET), the definition of educational attainment, and the classification of non-formal education.

A global consultation on ISCED began in June 2010, with the distribution of the draft of a new ISCED to national statistical offices, education ministries, policy makers, and experts working in the field of statistical classifications. The feedback from this consultation will be incorporated into the final recommendations that will be submitted for approval to the UNESCO General Conference in 2011.

More information on ISCED and on the current review is available on the ISCED web page of the UIS. The page offers background documents on the review and reports from meetings that took place between 2009 and 2010.

Related articles

External links

UNESCO
UNESCO Institute for Statistics (UIS)
UIS ISCED page
UIS announcement of global consultation on draft ISCED 2011
ISCED 1997 in English (PDF, 330 KB)
ISCED 1997 in French (PDF, 476 KB)
ISCED 1997 in Spanish (PDF, 381 KB)
ISCED 1997 in Russian (PDF, 1.0 MB)
ISCED 1997 in Arabic (PDF, 987 KB)
ISCED 1997 in Chinese (PDF, 1.3 MB)
ISCED mappings
ISCED mapping for Mozambique (Excel, 1.2 MB)
Global education digest 2009, UIS (PDF, 6.8 MB)

Friedrich Huebler, 30 July 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/07/isced.html

UNESCO releases data from 2008 education survey

2010-06-28T20:08:00.003-04:00

The UNESCO Institute for Statistics (UIS) has announced its main education data release for 2008. The UIS Data Centre is updated three times per year, in January, May-June, and in October. The current release adds new data on primary education for about 155 countries. New data are also available for secondary and tertiary education, for 135 and 103 countries, respectively.

Main page of UIS Data Centre

Source: stats.uis.unesco.org, June 2010

The data can be retrieved from predefined tables or custom tables. Data are also available in country and region profiles, and in global rankings for specific indicators. The Data Centre offers the following predefined tables.

Table 1: Education Systems
Table 2: Demographic and economic data
Table 3A: Enrolment of new entrants to primary education (ISCED 1)
Table 3B: Enrolment by ISCED level
Table 3C: Enrolment of pupils of the official age in pre-primary, primary and secondary education (ISCED 0-3)
Table 3D: Enrolment by grade in primary education (ISCED 1)
Table 3E: Repeaters by grade in primary education (ISCED 1)
Table 3F: Enrolment by grade in general secondary education (ISCED 2 and 3)
Table 3G: Repeaters by grade in general secondary education (ISCED 2 and 3)
Table 4: Teaching staff by ISCED level
Table 5: Enrolment ratios by ISCED level
Table 6: Intake rates to primary education
Table 7: Measures of children out of school
Table 8: School life expectancy (approximation method)
Table 9: Repetition rates and percentage of repeaters in primary education (ISCED 1)
Table 10: Percentage of repeaters in general secondary education (ISCED 2 and 3)
Table 11: Indicators on teaching staff at ISCED levels 0 to 3
Table 12: Measures of progression and completion in primary education (ISCED 1)
Table 13: Upper secondary (ISCED 3) graduation and entry to tertiary (ISCED 5) education. 2007 (selected countries)
Table 14: Tertiary Indicators
Table 15: Enrolments by broad field of education in tertiary education
Table 16: Graduates by broad field of education in tertiary education
Table 17: Inbound mobility rate, female percentage, and sums of internationally mobile students in tertiary education by host country and continent of origin
Table 18: International flows of mobile students at the tertiary level (ISCED 5 and 6)
Table 19: Finance Indicators by ISCED level
Table 20A: Regional sum of enrolment by ISCED level
Table 20B: Regional sum of new entrants to primary education (ISCED 1)
Table 20C: Regional sum of teaching staff by ISCED level
Table 20D: Regional average of enrolment ratios for pre-primary to tertiary education (ISCED 0-6)
Table 20E: Regional average of intake rates to primary education
Table 20F: Regional average of indicators on teaching staff by ISCED level
Table 20G: Regional average of school life expectancy (approximation method) by ISCED level
Table 20H: Regional sum of primary school age children out of school

External links

Friedrich Huebler, 28 June 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/06/uis.html

Primary school entrance age and duration

2010-05-30T18:17:00.061-04:00

Education for All (EFA) and the Millennium Development Goals (MDG) both aim at universal primary education. All children worldwide should attend and complete primary school by 2015. However, national education systems differ and the meaning of primary education for all children therefore varies from country to country.

The UNESCO Institute for Statistics (UIS) maintains a database with the entrance age and duration of primary education for 204 countries and territories. Table 1 summarizes the distribution of primary school entrance ages from the UIS database. In nearly two thirds of all countries, children are expected to enter primary school when they are 6 years old. In a further third of countries, the entrance age is 5 or 7 years. Two countries have different primary school entrance ages, Ireland with 4 years and Mongolia with 8 years..

Table 1: Primary school entrance age

Age	Countries	Percent
4 years	1	0.5
5 years	29	14.2
6 years	126	61.8
7 years	47	23.0
8 years	1	0.5
Total	204	100.0

Source: UIS Data Centre, May 2010.

The geographic distribution of the entrance ages is shown in the map in Figure 1. 6 years is the common primary school start age in most of North and South America, Western Europe, Africa, the Arab States, and East Asia, with some exceptions. 7 years is more common in Eastern Europe, Central Asia, and parts of Sub-Saharan Africa. 7 years is also the primary school start age in some large countries: Brazil, China and Russia.

Figure 1: Primary school entrance age

Source: UIS Data Centre, May 2010.

The duration of primary school, shown in Table 2, ranges from 3 to 8 years. In 126 of 204 countries and territories, primary school has a duration of 6 years. In about 25 countries each, the duration is 4, 5 or 7 years. The shortest duration, 3 years, is reported for Armenia, Russia and Turkmenistan. In Ireland, which has the earliest entrance age with 4 years, children have to attend primary school for 8 years.

Table 2: Primary school duration

Age	Countries	Percent
3 years	3	1.5
4 years	26	12.8
5 years	23	11.3
6 years	126	61.8
7 years	25	12.3
8 years	1	0.5
Total	204	100.0

Source: UIS Data Centre, May 2010.

The map in Figure 2 illustrates the primary school duration by country. 6 years is the most frequent duration in North and South America, East Asia and the Pacific, the Arab States and most of Africa except for Southern Africa, where 7 years is the most common primary school duration. In Central and Eastern Europe, Central Asia, and South and West Asia, primary education is typically shorter, with a duration of 4 or 5 years.

Figure 2: Primary school duration

Source: UIS Data Centre, May 2010.

What are the implications of the different primary school entrance ages and durations for the MDG and EFA goal of universal primary education by 2015? The official duration of primary education is closely linked to the number of children out of school. As an example, assume that a country has a primary school duration of 5 years and that the number of children in and out of school is evenly distributed across the official primary school ages. Shortening the duration of primary school from 5 to 4 years would immediately reduce the number of children out of school by 20 percent. However, the primary school net enrollment rate, the official indicator for the MDG of universal primary education, would not change and the country would therefore not be closer to the 2015 goal.

Related articles

External links

Friedrich Huebler, 30 May 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/05/age.html

Age distribution by wealth quintile in household survey data

2010-04-30T21:31:00.015-04:00

Household survey data may not contain precise ages for all household members. Age heaping, an unusually high share of ages ending in 0 and 5, is especially common in survey data from developing countries. Age heaping can be caused by uncertainty of survey respondents about their own age or the age of other household members, intentional misreporting, or errors during data collection and processing. Errors in age data can affect the estimation of education indicators from household survey data because these indicators are often calculated for specific age groups. Examples include the youth literacy rate and school attendance rates for the population of primary and secondary school age.

An article on age distribution in household survey data on this site demonstrated age heaping in survey data from India, Nigeria and to a lesser extent Indonesia. Data for Brazil showed little to no age heaping. To investigate whether age heaping is more common among certain segments of the population, the survey samples can be disaggregated by household wealth quintile. For this purpose, the households in the sample are first ranked by wealth, from poorest to richest. The population is then divided into five equally sized groups with 20 percent each of all household members in the sample.

Figure 1 shows the age distribution by single year of age and wealth quintile in data from Brazil. The data were collected in 2006 with a Pesquisa Nacional por Amostra de Domicílios (PNAD) or National Household Sample Survey. No preference for ages ending in 0 and 5 could be observed for the entire survey sample combined and disaggregation does not change the result. The age distribution in each quintile is smooth, with no peaks at ages ending in 0 and 5. The only obvious difference between the population in the different quintiles is that poorer families tend to have more children, indicated by a peak in the age distribution in the younger age groups.

Figure 1: Age distribution in household survey data by single-year age group and household wealth quintile, Brazil

Data source: Brazil PNAD 2006.

Figure 2 shows the age distribution in Demographic and Health Survey (DHS) data from India. The data were collected in 2005-06. In contrast to Brazil, there is considerable age heaping in the Indian data. However, peaks around ages ending in 0 and 5 are more pronounced among poorer households. Increasing household wealth is associated with a decrease in age heaping.

Figure 2: Age distribution in household survey data by single-year age group and household wealth quintile, India

Data source: India DHS 2005-06.

Data from Indonesia, collected with a Demographic and Health Survey in 2007, are shown in Figure 3. At the aggregate level, the survey data from Indonesia exhibit little age heaping. However, disaggregation by wealth quintile reveals that reported ages ending in 0 and 5 are more common among poorer households.

Figure 3: Age distribution in household survey data by single-year age group and household wealth quintile, Indonesia

Data source: Indonesia DHS 2007.

Finally, Figure 4 displays data from a 2008 Demographic and Health Survey in Nigeria. Similar to India, there is a high percentage of ages ending in 0 and 5 in the combined survey sample. The disaggregated data show that age heaping occurs more frequently among poorer households but also exists in the richest wealth quintile.

Figure 4: Age distribution in household survey data by single-year age group and household wealth quintile, Nigeria

Data source: Nigeria DHS 2008.

Disaggregation of household survey data from Brazil, India, Indonesia and Nigeria has shown that age heaping occurs more frequently in data collected from poorer households. Wealthier households may have more access to birth registration and therefore may be able to verify their ages with birth certificates. Wealthier households are also likely to be smaller and survey respondents would therefore have to know and report the ages of fewer persons than respondents from larger households.

Age heaping in survey data reduces the accuracy of education indicators that are calculated for single years of age, for example for all children of primary school entrance or graduation age. However, indicator estimates for larger age groups, for example all children of primary or secondary school age, are less likely to be affected by errors in age data.

Related articles

External links

Demographic and Health Surveys (DHS)
Brazil National Household Sample Survey 2006
Education glossary by the UNESCO Institute for Statistics

Friedrich Huebler, 30 April 2010, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/04/age.html

Children of primary and secondary school age out of school

2010-03-28T17:52:00.004-04:00

The UNESCO Institute for Statistics (UIS) publishes annual estimates of the number of children of primary school age out of school. A recent paper by Michael Bruneforth and Peter Wallet, Out-of-school adolescents (UIS 2010), extends the analysis to children of lower secondary school age. Any child enrolled in primary, secondary or tertiary education is considered in school, regardless of the child's age. Only children that are truly excluded from education are counted as out of school.

The paper's regional and global estimates of the number and percent of children out of school are reproduced in this article. Table 1 lists the population of primary and lower secondary school age in 2007. Worldwide there were about 653 million children of primary school age and 388 million children of lower secondary school age. More than half of these children lived in South and West Asia and East Asia and the Pacific.

Table 1: Population of primary and lower secondary school age by region (million), 2007

Region	Primary	Lower secondary	Total
Sub-Saharan Africa	124.9	57.9	182.7
Arab States	41.4	21.9	63.5
South and West Asia	176.8	106.8	284.2
Central Asia	5.6	8.0	13.8
East Asia and the Pacific	173.8	106.5	281.2
Central and Eastern Europe	22.2	20.3	42.1
North America and Western Europe	50.8	31.0	81.6
Latin America and the Caribbean	58.6	35.9	93.7
World	652.6	388.2	1042.5

Source: UIS 2010, page 10, Table 1; author's calculations. - Note: Figures may not sum due to rounding.

Figure 1 illustrates the regional distribution of the population of primary and lower secondary school age. The number of children in these age groups is plotted along the horizontal axis. The vertical axis indicates the share of children of primary and lower secondary school age in each region. The regions with the largest number of school-age children in 2007 were South and West Asia (284 million), East Asia and the Pacific (281 million), and Sub-Saharan Africa (183 million). More than 60 percent of the combined population of primary and lower secondary school age were of primary school age. Central Asia and Central and Eastern Europe were exceptions, with a greater share of children of lower secondary school age than in other regions. The large share of primary-age children in Sub-Saharan Africa is a symptom of its high population growth rate.

Figure 1: Population of primary and lower secondary school age by region, 2007

Source: UIS 2010, page 10, Table 1; author's calculations. - CEE: Central and Eastern Europe, NAWE: North America and Western Europe, LAC: Latin America and the Caribbean.

The share and number of children out of school are listed in Table 2. At the global level, 11 percent or 72 million of all children of primary school age and 18 percent or 71 million of all children of lower secondary school age were out of school. The combined global share of children out of school was 14 percent. Out-of-school rates were highest in Sub-Saharan Africa, where 26 percent of all primary school-age children and 37 percent of all secondary school-age children were excluded from education.

Table 2: Children of primary and lower secondary school age out of school by region, 2007

Region	Primary		Lower secondary		Total
Region	Percent	Million	Percent	Million	Percent	Million
Sub-Saharan Africa	25.8	32.2	36.8	21.3	29.3	53.5
Arab States	13.9	5.8	19.5	4.3	15.8	10.0
South and West Asia	10.2	18.0	27.3	29.1	16.6	47.2
Central Asia	4.8	0.3	4.9	0.4	4.8	0.7
East Asia and the Pacific	5.2	9.0	10.0	10.6	7.0	19.7
Central and Eastern Europe	7.0	1.6	9.6	1.9	8.3	3.5
North America and Western Europe	3.8	1.9	4.3	1.3	4.0	3.3
Latin America and the Caribbean	5.1	3.0	5.5	2.0	5.3	5.0
World	11.0	71.8	18.3	71.0	13.7	142.8

Source: UIS 2010, page 10, Table 1.

As illustrated in Figure 2, out-of-school rates are always higher at the secondary level of education than at the primary level. This is not surprising because not all students complete primary education and not all of those who graduate from primary school transfer to secondary school to continue their education. In addition to Sub-Saharan Africa, South and West Asia (27 percent) and the Arab States (20 percent) also had a high share of children of secondary school age out of school.

Figure 2: Children of primary and lower secondary school age out of school by region, 2007

Source: UIS 2010, page 10, Table 1.

The distribution of children out of school by region in 2007 is shown in Figure 3. A comparison with the population distribution in Figure 1 makes clear that children from Sub-Saharan Africa and South and West Asia were disproportionately more likely to be out of school than children from other regions. More than two thirds of the 143 million out-of-school children of primary and lower secondary age were from Sub-Saharan Africa (54 million) and South and West Asia (47 million). 20 million children out of school lived in East Asia and 10 million in the Arab States. The remaining 13 million children out of school were from Latin America and the Caribbean (5 million), Central and Eastern Europe (3.5 million), North America and Western Europe (3.3 million), and Central Asia (0.7 million).

Figure 3: Children of primary and lower secondary school age out of school by region, 2007

Source: UIS 2010, page 10, Table 1. - CEE: Central and Eastern Europe, NAWE: North America and Western Europe, LAC: Latin America and the Caribbean.

In Sub-Saharan Africa, the Arab States, North America and Western Europe, and Latin America and the Caribbean most children out of school were of primary age. In South and West Asia, East Asia, and Central and Eastern Europe most children out of school were of lower secondary age. At the global level, the number of out-of-school children of primary school age and lower secondary school age was roughly equal (see Table 2).

References

UNESCO Institute for Statistics (UIS). 2010. Out-of-school adolescents. Montreal: UIS.
Announcement of paper on UIS website
Download English version (PDF, 208 KB)
Download French version: Adolescents non scolarisés (PDF, 216 KB)
Figures 1 and 3 were created with the spineplot add-on for Stata by Nicholas Cox.
Cox, Nicholas J. 2008. "Speaking Stata: Spineplots and their kin." Stata Journal 8 (1): 105-121. http://www.stata-journal.com/article.html?article=gr0031

External links

Friedrich Huebler, 28 March 2010 (edited 17 August 2011), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/03/coos.html

Age distribution in household survey data

2010-02-28T23:49:00.057-05:00

Indicators in the field of education statistics, such as those defined in the education glossary of the UNESCO Institute for Statistics, are typically calculated for specific age groups. For example, the youth literacy rate is for the population age 15 to 24 years, the adult literacy rate for the population age 15 and over, and the net attendance rates for primary and secondary education are for the population of primary and secondary school age, respectively. The net intake rate is an example for an indicator that is calculated for a single year of age, the official start age of primary school.

For a correct calculation of education indicators it is necessary to have precise age data. In the case of data collected with population censuses or household surveys this means that the ages recorded for each household member should be without error. However, census or survey data sometimes exhibit the phenomenon of age heaping, usually on ages ending in 0 and 5. Such heaping or digit preference occurs when survey respondents don't know their own age or the ages of other household members, or when ages are intentionally misreported.

The presence of age heaping can be tested with indices of age preference such as Whipple's index. Heaping can also be detected through visual inspection of the age distribution in household survey data. Figures 1 and 2 summarize the age distribution in survey data from Brazil, India, Indonesia and Nigeria. The data from Brazil were collected with a Pesquisa Nacional por Amostra de Domicílios or National Household Sample Survey in 2006. The data for the other three countries are from Demographic and Health Surveys conducted between 2005 and 2008.

Figure 1 shows the share of single years of age in the total survey sample. A preference for ages ending in 0 and 5 is strikingly obvious in the data from India and Nigeria. In the data from Indonesia, age heaping is also present, but to a lesser extent than for India and Nigeria. Lastly, the graph for Brazil is relatively smooth, indicating a near absence of age heaping.

Figure 1: Age distribution in survey data by single-year age group

Data source: Brazil PNAD 2006, India DHS 2005-06, Indonesia DHS 2007, Nigeria DHS 2008.

In Figure 2, single ages are combined in five-year age groups, from 0-4 years and 5-9 years to 90-94 years and 95 years and over. Compared to Figure 1, the distribution lines are much smoother, including for India and Nigeria. We can conclude that age heaping is problematic for education indicators that are calculated for single years, for example all children of primary school entrance age, but less so for indicators that are calculated for a larger age group, for example all children of primary or secondary school age or all persons over 15 years of age.

Figure 2: Age distribution in survey data by five-year age group

Data source: Brazil PNAD 2006, India DHS 2005-06, Indonesia DHS 2007, Nigeria DHS 2008.

Related articles

External links

Demographic and Health Surveys (DHS)
Brazil National Household Sample Survey 2006
Whipple's index entry in Wikipedia
Education glossary by the UNESCO Institute for Statistics
Net intake rate definition in UIS education glossary
UNESCO Institute for Statistics (UIS)

Friedrich Huebler, 28 February 2010 (edited 30 September 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/02/age.html

EFA Global Monitoring Report 2010

2010-01-31T19:54:00.008-05:00

The Education for All Global Monitoring Report 2010 was released on 19 January 2010. The Global Monitoring Report is written annually by an independent team and published by UNESCO.

The title of this year's report is Reaching the marginalized. UNESCO estimates that 72 million children of primary school age were out of school in 2007. The report examines who these children are and why they are excluded from education. The report further argues that there is a persistent financing gap that prevents countries from reaching the goal of education for all and that, based on current trends, 56 million children of primary school age will still be out of school in 2015.

The report introduces a new database on Deprivation and Marginalization in Education that was developed by the EFA Global Monitoring Report team and the Department of Economics at the University of Göttingen. The DME database introduces a measure of "education poverty", defined as the share of the population aged 17 to 22 years with less than 4 years or less than 2 years in school. Data are presented as global snapshots and in individual country profiles. All statistics were calculated with data from Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS).

Excerpt from Nigeria country overview in DME database

Source: Deprivation and Marginalization in Education database, country overviews.

Reference

UNESCO. 2010. EFA Global Monitoring Report 2010: Reaching the marginalized. Paris: UNESCO. (Download in PDF format, 12 MB)

External links

Friedrich Huebler, 31 January 2010 (edited 7 March 2011), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2010/01/gmr.html

MICS Compiler by UNICEF

2009-12-30T05:19:00.008-05:00

MICS Compiler, a new website by UNICEF, provides easy access to data from Multiple Indicator Cluster Surveys (MICS), nationally representative household surveys that are carried out with support from UNICEF. The site is similar to STATcompiler, which offers data from Demographic and Health Surveys (DHS).

MICS Compiler was launched with data from 26 surveys conducted in Africa, Asia, Eastern Europe, and Latin America and the Caribbean between 2005 and 2007. Estimates are available for 39 indicators in ten areas.

Survey information
Child mortality
Nutrition
Child health
Environment
Reproductive health
Child development
Education
Child protection
HIV/AIDS, sexual behavior, and orphaned and vulnerable children

Access to the data requires two steps. In the first step, users of MICS Compiler must select one or more surveys. In the second step, the indicators are selected. The results are presented in tables or graphs. As an example, the screenshot below shows a graph with the female youth literacy rate in 21 countries.

MICS Compiler by UNICEF: Female youth literacy rate in 21 countries, 2005-2006

At present, the female youth literacy rate is the only indicator listed in the area of education but the MICS for All blog has announced plans to expand MICS Compiler with data for more indicators and more surveys. There are also plans for adding a mapping function, similar to the DHS STATmapper.

Related articles

External links

Friedrich Huebler, 30 December 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/12/mics.html

Release of 2008 education data by UIS

2009-11-27T20:19:00.002-05:00

The UNESCO Institute for Statistics (UIS) has announced the release of new education statistics for the year 2008. For 70 countries, new data on primary education are available at the UIS Data Centre. All indicators were calculated with new population estimates from the World Population Prospects 2008 by the UN Population Division. As part of the new data release, all historical estimates in the UIS education database were also revised.

External links

Friedrich Huebler, 27 November 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/11/uis.html

Regional disparities in school life expectancy

2009-10-31T22:10:00.005-04:00

The school life expectancy is the number of years of schooling a child of school entrance age can expect to receive. It is calculated as the sum of age-specific enrollment rates for the specified levels of education. The UNESCO Institute for Statistics (UIS) provides data on the school life expectancy for the following levels of education: pre-primary, primary to secondary, primary to tertiary, and tertiary.

Figure 1 displays the average school life expectancy for primary to secondary education in eight geographic regions - Arab States, Central Asia, Central and Eastern Europe, East Asia and the Pacific, Latin America and the Caribbean, North America and Western Europe, South and West Asia, and Sub-Saharan Africa - and for the world as a whole. For each region, the total, male and female school life expectancy is shown. A high value for this indicator means that school enrollment rates as well as retention rates are high and that children are likely to spend a high number of years in formal education.

The values plotted in Figure 1 are also listed in Table 1. In addition to the school life expectancy in years, Table 1 lists the gender parity index for each region. The GPI is the ratio of the female to male school life expectancy. Values below 1 mean that girls have a lower school life expectancy than boys, while GPI values above 1 mean the opposite. A GPI of 1 indicates gender parity. All data in Figure 1 and Table 1 were obtained from the UIS Data Centre and are for the years 2007 and 2008.

Figure 1: School life expectancy in years, primary to secondary education, 2007/2008

Data source: UNESCO Institute for Statistics, Data Centre, October 2009.

Children in North America and Western Europe have the highest school expectancy. On average, boys and girls alike can expect to spend about 12.3 years in school. In Latin America and the Caribbean, the average school life expectancy is 11.7 years. In three other regions children are also likely to receive more than 10 years of primary and secondary education: Central Asia (10.8 years), Central and Eastern Europe (10.5 years), and East Asia and the Pacific (10.4 years). In Sub-Saharan Africa (8.1 years), South and West Asia (9.1 years), and in the Arab States (9.3 years) the average school life expectancy is lower than in the other regions.

Table 1: School life expectancy in years, primary to secondary education, 2007/2008

Region	Total	Male	Female	GPI
Arab States	9.3	9.8	8.8	0.90
Central Asia	10.8	10.9	10.6	0.98
Central and Eastern Europe	10.5	10.6	10.3	0.96
East Asia and the Pacific	10.4	10.3	10.5	1.02
Latin America and the Caribbean	11.7	11.6	11.8	1.02
North America and Western Europe	12.3	12.3	12.3	1.00
South and West Asia	9.1	9.4	8.7	0.92
Sub-Saharan Africa	8.1	8.7	7.6	0.87
World	9.8	10.0	9.5	0.95

Note: GPI is the gender parity index (female / male school life expectancy).
Data source: UNESCO Institute for Statistics, Data Centre, October 2009.

Sub-Saharan Africa, the Arab States, and South and West Asia have not only the lowest school life expectancy, they are also the worst performers in terms of gender parity. As the graph shows, there is a relatively large gap between the male and female school life expectancy in these regions, with GPI values ranging from 0.87 in Sub-Saharan Africa to 0.92 in South and West Asia. On average, girls receive one year less education than boys in these three regions. In Sub-Saharan Africa, the school life expectancy is 7.6 years for girls and 8.7 years for boys.

In the other regions, there is little or no difference between the school life expectancy of boys and girls. In Central and Eastern Europe, the GPI is 0.96, with a school life expectancy of 10.6 years for boys and 10.3 years for girls. North America and Western Europe have reached gender parity. In East Asia and the Pacific, and in Latin America and the Caribbean, the school life expectancy is higher for girls than for boys; in both regions, the GPI is 1.02.

Compared to the beginning of the decade, the school life expectancy has increased in all regions, especially in Sub-Saharan Africa. However, the gap between the best- and worst-performing countries is still large. In addition, gender disparity continues to be a problem, especially in regions where the school life expectancy is low.

Related articles

External links

Friedrich Huebler, 31 October 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/10/sle.html

NER, GER and universal primary education

2009-09-29T22:52:00.007-04:00

The net enrollment ratio (NER) in primary education is one of the official indicators for the Millennium Development Goal of universal primary education. The primary NER is the share of children of primary school age that are enrolled in primary school.

Primary NER	=	Number of children of primary school age enrolled in primary school
		Number of children of primary school age

If all children of primary school age are enrolled in primary school, the primary NER is 100 percent. A primary NER below 100 percent means that not all children of primary school age are in primary school; some may be out of school, some may be in preschool, in secondary school or in other forms of education. By definition, the NER cannot exceed 100 percent.

The gross enrollment ratio (GER) is a related indicator. The primary GER indicates how many children, regardless of their age, are enrolled in primary school, relative to the population of primary school age.

Primary GER	=	Number of children enrolled in primary school
		Number of children of primary school age

The value of the GER can exceed 100 percent. Values above 100 percent mean that some children above or below primary school age are in primary school. A GER above 100 percent is usually an indicator of overage enrollment, for example due to repetition or late entry.

Ideally, all children in a country enter primary school at the official primary school entrance age and graduate from the final primary grade after the official duration of primary school, for example after four or six years. In this case, the primary NER would be 100 percent and universal primary education would be achieved. If no children repeated a grade, the primary GER would also be 100 percent. If we assume that some children have to repeat a grade and remain in primary school although they have reached official secondary school age, the primary GER would be slightly above 100 percent.

However, we can demonstrate that a primary NER of 100 percent is not a necessary condition for universal primary education. Similarly, the primary GER can be below 100 percent in a country, although universal primary education has been achieved. For the demonstration we refer to data for Japan. According to the Global Education Digest 2009 by the UNESCO Institute for Statistics, Japan has achieved universal primary education with a primary NER and GER of 100 percent in 2007, the most recent year with data.

What would happen to the NER and GER if Japanese children systematically entered and graduated from primary school one year early or one year late? These hypothetical situations can be simulated with data from the World Population Prospects 2008 by the UN Population Division. Table 1 lists the estimated population of Japan between 5 and 12 years of age in the year 2009.

Table 1: Estimated population of Japan between 5 and 12 years, 2009

Age	Population
5 years	1,120,774
6 years	1,134,317
7 years	1,145,758
8 years	1,155,440
9 years	1,163,697
10 years	1,171,297
11 years	1,179,006
12 years	1,185,028
5-10 years	6,891,283
6-11 years	6,949,515
7-12 years	7,000,226

Source: UN Population Division. 2009. World Population Prospects: 2008 Revision.

Scenario 1: entry and graduation at official age

Primary school in Japan has 6 grades and the official primary school age is 6 to 11 years. If all children enter primary school at age 6 and graduate after 6 years, the primary NER and GER can be calculated as follows.

Primary NER	=	Number of children of primary school age enrolled in primary school
Primary NER	=	Number of children of primary school age
	=	6,949,515 / 6,949,515
	=	100%

Because there is no overage or underage enrollment, the number of children in primary school is identical to the number of children of primary school age (6 to 11 years) and thus the primary GER is identical to the primary NER.

Primary GER	=	Number of children enrolled in primary school
Primary GER	=	Number of children of primary school age
	=	6,949,515 / 6,949,515
	=	100%

Scenario 2: early entry

If all children enter and graduate from primary school one year early, the primary NER and GER are no longer 100 percent. The population of primary school age (6-11 years) is still 6,949,515, but in this age group only children between 6 and 10 are in primary school, in addition to children aged 5 years. In this scenario, children age 11 are already in secondary school. The number of children of primary school age enrolled in primary school is therefore 6,949,515 - 1,179,006 = 5,770,509 and the primary NER is no longer 100 percent but 83 percent.

Primary NER (early entry)	=	Number of children of primary school age enrolled in primary school
Primary NER (early entry)	=	Number of children of primary school age
	=	5,770,509 / 6,949,515
	=	83.0%

The primary GER is still near 100 percent because the population in primary school (5-10 years) is similar to the population of primary school age (6-11 years).

Primary GER (early entry)	=	Number of children enrolled in primary school
Primary GER (early entry)	=	Number of children of primary school age
	=	6,891,283 / 6,949,515
	=	99.2%

Scenario 3: late entry

Now assume that all children enter and graduate from primary school one year late. Only children between 7 and 12 years are in primary school. Of the population of primary school age (6-11 years) only those between 7 and 11 are in primary school, in addition to children aged 12 years. The number of children of primary school age enrolled in primary school is therefore 6,949,515 - 1,134,317 = 5,815,198 and the primary NER is now 83.7 percent.

Primary NER (late entry)	=	Number of children of primary school age enrolled in primary school
Primary NER (late entry)	=	Number of children of primary school age
	=	5,815,198 / 6,949,515
	=	83.7%

As in scenario 2 with early entry, the primary GER is near 100 percent because the population in primary school (7-12 years) is close to the population of primary school age (6-11 years).

Primary GER (late entry)	=	Number of children enrolled in primary school
Primary GER (late entry)	=	Number of children of primary school age
	=	7,000,226 / 6,949,515
	=	100.7%

Table 2 and Figure 1 summarize the primary NER and GER under the three scenarios described above. In all three scenarios there is universal primary education but in the case of early or late entry, the primary NER is far below 100 percent. On the other hand, the primary GER is equal to or near 100 percent in all three scenarios, due to the small difference between the number of children in the individual age cohorts.

Table 2: Primary NER and GER in Japan in the case of age-appropriate, early and late entry and graduation

Scenario for primary school enrollment	Primary NER (%)	Primary GER (%)
Entry and graduation at official age	100.0	100.0
Entry and graduation one year early	83.0	99.2
Entry and graduation one year late	83.7	100.7

Figure 1: Primary NER and GER in Japan in the case of age-appropriate, early and late entry and graduation

In an ideal situation, when all or almost all children enter primary school at the official entrance age and graduate after the official duration of primary school, both the NER and GER are near 100 percent. However, as demonstrated with data for Japan, a primary NER and GER of 100 percent is not a necessary condition for universal primary education. In countries where children enter school before or after the official entrance age, universal primary education can exist although the primary NER may be below 100 percent.

Related articles

External links

Friedrich Huebler, 29 September 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/09/upe.html

Stata text editor integration: update for Stata 11

2009-08-31T23:58:00.003-04:00

In July, version 11 of the Stata statistical package was released. To support the latest version of Stata, the programs to integrate Stata and external text editors have been updated.

External links

Stata statistical package, official site

Friedrich Huebler, 31 August 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/08/stata.html

Global Education Digest 2009

2009-07-31T23:10:00.005-04:00

The UNESCO Institute for Statistics (UIS) has published the 2009 edition of its annual Global Education Digest. The GED presents the latest statistics on pre-primary, primary, secondary and tertiary education, education finance, literacy and educational attainment. The statistical tables contain data for more than 200 countries and territories. In addition to national data, the tables offer global values and regional values for the Arab States, Central and Eastern Europe, Central Asia, East Asia and the Pacific, Latin America and the Caribbean, North America and Western Europe, South and West Asia, and Sub-Saharan Africa.

The analytical chapter that precedes the statistical tables is dedicated to a different topic every year. The analytical chapter in the GED 2009 explores global trends in higher education, including levels of participation, fields of study, student mobility, and tertiary education finance. The tables with time series data from 1970 to 2005 that were introduced in the previous GED are limited to data on tertiary education this year. The GED 2008 also contained time series tables on primary and secondary education.

The data from the GED are available free of charge at the UIS Data Centre. To access the statistical tables, click on "Predefined Tables" and then "Education". For most indicators, the GED only lists data for one or two years, whereas the Data Centre provides annual statistics from 1999 to 2008. The Data Centre also offers time series data for selected primary, secondary and tertiary education indicators from 1970 to 2005.

References

UNESCO Institute for Statistics (UIS). 2009. Global education digest 2009: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 7.0 MB)
UNESCO Institute for Statistics (UIS). 2008. Global education digest 2008: Comparing education statistics across the world. Montreal: UIS. (Download PDF, 6.3 MB)

External links

UNESCO Institute for Statistics (UIS)
Announcement of the Global Education Digest 2009 by the UIS
Global Education Digest 2008, with links to the Arabic, English, French and Spanish editions
UIS Data Centre

Friedrich Huebler, 31 July 2009 (edited 19 September 2010), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/07/ged.html

Updated "Guide to creating maps with Stata"

2009-06-30T23:08:00.005-04:00

The guide to creating maps with Stata has been updated with new links to third-party software.

Map created with spmap in Stata: length of country names

Related articles

Friedrich Huebler, 30 June 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/06/stata-maps.html

Achievement gap between black and white students in the United States

2009-05-09T10:05:00.003-04:00

Two previous articles on this site presented data on disparities in school attendance by ethnicity, language or religion from 17 nationally representative household surveys. Net attendance rates among the least disadvantaged groups are up to 1.7 times higher than net attendance rates among the most disadvantaged groups at the primary level of education and up to 6 times higher at the secondary level of education.

Similar gaps in access to education and in student achievement exist in the United States. The National Center for Education Statistics has published the most recent findings of its National Assessment of Educational Progress, a long term study of student achievement, in the report NAEP 2008 Trends in Academic Progress. The results of the periodic assessments by the NCES demonstrate a persistent achievement gap between black and white students.

Figure 1 summarizes the results of 12 reading assessments over the period 1971 to 2008. For each assessment, the average reading scores of black and white students aged 9, 13 and 17 years are plotted in the graph. The shaded area indicates the achievement gap between black and white students. For 2004, two scores are shown for each group because the assessment format was revised in that year. The reading scores in 1971 and 2008 are also listed in Table 1.

Figure 1: Average reading scores of black and white students, 1971-2008

Data source: NAEP 2008 Trends in Academic Progress, p. 14-15.

Black and white students of all ages achieved higher reading scores in 2008 than in previous years. In 1971, 9-year-old white students had an average score of 214 and black students in the same age group scored 170 on average. In 2008, the average score of 9-year-olds was 228 for white students and 204 for black students. As a result, the score gap between black and white 9-year-olds fell from 44 in 1971 to 24 in 2008. For 13-year-old students the score gap fell from 39 to 21 over the same period and for 17-year-olds it fell from 52 to 29.

Closer inspection of the data reveals that most of this reduction in the achievement gap occurred during the 1970s and 1980s. Since the 1990s, the gap between black and white students has remained relatively stable. Although the reading scores of black students continue to improve, they no longer grow fast enough to close the gap with white students.

Table 1: Average reading scores of black and white students, 1971 and 2008

Year	Age	Average reading score		Score gap
Year	Age	Black	White	Score gap
1971	9 years	170	214	44
2008	9 years	204	228	24
1971	13 years	222	261	39
2008	13 years	247	268	21
1971	17 years	239	291	52
2008	17 years	266	295	29

Data source: NAEP 2008 Trends in Academic Progress, p. 14-15.

The NAEP report shows a similar achievement gap between black and white students in the area of mathematics. In addition, there is a similar but smaller gap between white and Hispanic students in reading and mathematics. In spite of long-running efforts to improve the education system for all parts of the population, minority students consistently lag behind white students in the United States.

Reference

Rampey, Bobby D., Gloria S. Dion, and Patricia L. Donahue. 2009. NAEP 2008 Trends in Academic Progress. Washington: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education. (Download PDF file, 1.1 MB)

External links

Friedrich Huebler, 9 May 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/05/usa.html

New version of programs to integrate Stata and external text editors

2009-04-05T19:15:00.002-04:00

Version 3.1 of the rundo and rundolines programs to integrate Stata and external text editors has been released. The new version corrects a bug in version 3 of the rundo program, which had pointed to the wrong INI file. As a result of this bug, changed settings in rundo.ini had no effect on the execution of the program. Version 3.1 also updates the code of the rundo and rundolines programs to version 10.1 of Stata. Older versions of Stata are still supported.

Related articles

External links

Stata

Friedrich Huebler, 5 April 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/04/stata.html

Disparities in secondary school attendance by ethnicity, language or religion

2009-03-15T21:32:00.002-04:00

Members of ethnic, linguistic or religious minorities face barriers to access to education in many countries. In an article on primary school attendance by ethnicity, language or religion the presence of such disparities was demonstrated with data from Multiple Indicator Cluster Surveys. The MICS are nationally representative household surveys supported by UNICEF that collect data on school attendance and other household member characteristics. In the most recent round of MICS surveys, carried out in 2005 and 2006, 17 countries collected data on school attendance by ethnicity, language or religion: Albania, Belize, Gambia, Georgia, Guinea-Bissau, Guyana, Kazakhstan, Kyrgyzstan, Lao PDR, Macedonia, Montenegro, Serbia, Sierra Leone, Thailand, Togo, Uzbekistan, and Viet Nam.

The school attendance data from the MICS surveys can be used to generate an education parity index that measures relative disparity across different groups of disaggregation, as described in the article on primary school attendance. To calculate the index, the attendance rate of the group with the lowest value is divided by the attendance rate of the group with the highest value. The result is a value between 0 and 1, where 1 means that children from different ethnic, linguistic or religious groups have the same secondary school attendance rate. Values closer to 0 indicate increasing disparity.

As an example, Thailand collected data on school attendance that can be linked to the mother tongue of the household head. The secondary school net attendance rates (NAR) for two groups of children identified in the 2005-06 MICS data are shown in Table 1.

Table 1: Secondary school attendance in Thailand

Mother tongue of household head	Secondary NAR (%)
Thai	81.2
Other language	65.8
Total	79.8

Data source: MICS 2005-06.

Among children from households whose head speaks Thai, the secondary NAR is 81.2 percent. Among children from households headed by someone with a different mother tongue, the secondary NAR is 65.8 percent. The secondary school parity index for Thailand is then calculated as follows.

Secondary school parity index	= Lowest secondary NAR / Highest secondary NAR
	= Secondary NAR of speakers of another language / Secondary NAR of speakers of Thai
	= 65.8 / 81.2
	= 0.81

The parity index is a relative, not an absolute measure of disparity. The value 0.81 means that the secondary NAR of speakers of another language is, relatively speaking, 19 percent below the secondary NAR of Thai speakers. The absolute gap between children from the two groups is 15.4 percent, the difference between 81.2 and 65.8.

The secondary school parity index for all 17 countries with data is shown in Figure 1. The index ranges from a high of 0.98 in Viet Nam to a low of 0.17 in Serbia. The low value for Serbia is explained by extremely low secondary school attendance among the Roma ethnic group. The secondary school NAR for Roma children is 14.8 percent, compared to 85.9 percent for Serbians and 88.6 percent for children from other ethnic groups. In addition to Serbia, six other countries have index values at or below 0.5: Lao PDR, Macedonia, Guinea-Bissau, Togo, Belize, and Montenegro. In these countries, children from the most advantaged ethnic, linguistic or religious group have secondary school net attendance rates that are at least twice as high as the attendance rates of children from the most disadvantaged group. In Viet Nam, Kazakhstan, Albania, and Uzbekistan, on the other hand, disparities in access to secondary education are relatively small.

Figure 1: Secondary school parity index: School attendance by ethnicity, language or religion

Data source: MICS 2005-2006.

The attendance rates used to calculate the secondary school parity index are summarized in Table 2. The table also shows whether the national agencies that implemented a survey chose ethnicity, language or religion to identify minorities. A comparison with data on primary school attendance makes clear that disparities at the secondary level of education are much larger than disparities at the primary level, where the parity index for the same group of countries has a range from 0.59 to 0.99.

Table 2: Disparities in secondary school attendance by ethnicity, language or religion

Country	Year	Characteristic	Primary NAR (%)		Parity index
Country	Year	Characteristic	Min.	Max.	Parity index
Albania	2005	Religion	77.1	83.7	0.92
Belize	2006	Language	36.9	79.2	0.47
Gambia	2006	Ethnicity	27.5	48.2	0.57
Georgia	2005	Ethnicity	69.0	90.6	0.76
Guinea-Bissau	2006	Language	4.3	13.8	0.31
Guyana	2006	Ethnicity	56.0	81.1	0.69
Kazakhstan	2006	Language	90.8	96.0	0.95
Kyrgyzstan	2006	Language	79.3	92.4	0.86
Lao PDR	2006	Language	10.0	45.6	0.22
Macedonia	2005	Ethnicity	17.4	73.7	0.24
Montenegro	2005	Ethnicity	46.5	92.9	0.50
Serbia	2005	Ethnicity	14.8	88.6	0.17
Sierra Leone	2005	Religion	17.8	24.4	0.73
Thailand	2005-06	Language	65.8	81.2	0.81
Togo	2006	Ethnicity	22.9	53.1	0.43
Uzbekistan	2006	Language	87.1	95.4	0.91
Viet Nam	2006	Ethnicity	93.8	95.7	0.98

Data source: MICS 2005-2006.

Data source

Multiple Indicator Cluster Surveys (MICS), 2005-2006.

External links

Friedrich Huebler, 15 March 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/03/elr2.html

Disparities in primary school attendance by ethnicity, language or religion

2009-03-01T23:38:00.003-05:00

In many parts of the world, members of ethnic, linguistic or religious minorities face barriers to access to education. One example is Nepal, where caste and ethnicity are closely linked to primary and secondary school attendance rates. Because of the importance of this issue, "Minorities and the right to education" was the thematic focus of the first United Nations Forum on Minority Issues, which took place in Geneva on 15 and 16 December 2008.

The presence of disparities in national education systems can be demonstrated with data from Multiple Indicator Cluster Surveys (MICS), nationally representative household surveys that are carried out with the support of UNICEF. The MICS data collection process is explained in the Multiple Indicator Cluster Survey Manual 2005 (UNICEF 2006). MICS surveys conducted in 2005 and 2006 collected data on school attendance by ethnicity, language or religion in the following countries: Albania, Belize, Gambia, Georgia, Guinea-Bissau, Guyana, Kazakhstan, Kyrgyzstan, Lao PDR, Macedonia, Montenegro, Serbia, Sierra Leone, Thailand, Togo, Uzbekistan, and Viet Nam.

Minority Rights Group International (MRG) defines minorities as "non-dominant ethnic, religious and linguistic communities, who may not necessarily be numerical minorities. ... [These groups] may lack access to political power, face discrimination and human rights abuses, and have 'development' policies imposed upon them" (MRG 2009). The MICS data alone are not sufficient to identify groups that can be considered minorities as defined by MRG because the size of particular groups in relation to the entire population of a country does not indicate whether these groups are discriminated in any way. This article therefore examines differences in school attendance between all ethnic, linguistic or religious groups for which data are available. Disparities between these groups can provide insights into whether any part of a country's population faces discrimination or is otherwise disadvantaged.

With the school attendance data from the MICS surveys it is possible to generate an education parity index that measures relative disparity across different groups of disaggregation, following the methodology developed by Huebler (2008) for data on school attendance by sex, area of residence, and household wealth. The education parity index has a range of 0 to 1, where 1 indicates parity between all groups of disaggregation. This methodology can also be applied to primary school attendance rates by ethnicity, language or religion. To calculate the index, the attendance rate of the group with the lowest value is divided by the attendance rate of the group with the highest value, yielding a value between 0 and 1. The value 1 means that children from different ethnic, linguistic or religious groups have the same primary school attendance rates. Smaller values indicate increasing disparity.

The calculation of the parity index can be illustrated with data from Macedonia. A MICS survey conducted in 2005 collected data on school attendance by ethnic group of the household head. Four ethnic groups are identified in the data and their respective primary school net attendance rates (NAR) are shown in Table 1.

Table 1: Primary school attendance in Macedonia

Ethnic group of household head	Primary NAR (%)
Albanian	97.8
Macedonian	97.5
Roma	61.1
Other ethnic group	81.9
Total	94.9

Data source: MICS 2005.

Albanians in Macedonia have the highest primary NAR, 97.8 percent. By contrast, Roma have the lowest NAR, 61.1 percent. In other words, only 6 of 10 Roma children of primary school age are attending primary school. With these values, the primary school parity index for Macedonia can be calculated as follows:

Primary school parity index	= Lowest primary NAR / Highest primary NAR
	= Primary NAR of Roma / Primary NAR of Albanians
	= 61.1 / 97.8
	= 0.62

The value 0.62 means that the attendance rate of the most disadvantaged group, Roma, is 62 percent of the attendance rate of the least disadvantaged group, Albanians. In other words, the primary NAR of Roma is 38 percent below the primary NAR of ethnic Albanians. 38 percent is not the absolute but the relative difference in school attendance because the education parity index is a relative measure of disparity.

Applying the same formula to primary NAR values from other MICS surveys yields the values in Figure 1, which shows the parity index for primary school attendance by ethnicity, language or religion. In the 17 countries with data, the parity index ranges from a high of 0.99 in Guyana to a low of 0.59 in the Lao People's Democratic Republic. In Laos, speakers of the Lao language are significantly more likely to attend primary school than speakers of other languages, whose primary school NAR is 41 percent below the NAR of Lao speakers. Similar disparities exist in Togo, where members of the Para-Gourma ethnic group have a much lower primary school attendance rate than members of the Akposso-Akébou group, and in Macedonia.

Uzbekistan and Viet Nam are characterized by the near absence of disparities in primary school attendance between different ethnic, linguistic or religious groups, similar to Guyana. In these countries, the primary NAR of the group with the lowest attendance rate is only 1 or 2 percent below the primary NAR of the group with the highest attendance rate.

Figure 1: Primary school parity index: School attendance by ethnicity, language or religion

Data source: MICS 2005-2006.

The primary school net attendance rates used to calculate the parity index are listed in Table 2. The table also shows whether ethnicity, language or religion were chosen to identify minorities in a country. This choice was made by the national agencies that implemented the survey. Eight countries selected ethnicity, seven countries selected language, and two countries selected religion as the characteristic that best captures minority status.

Table 2: Disparities in primary school attendance by ethnicity, language or religion

Country	Year	Characteristic	Primary NAR (%)		Parity index
Country	Year	Characteristic	Min.	Max.	Parity index
Albania	2005	Religion	91.3	94.9	0.96
Belize	2006	Language	86.6	100	0.87
Gambia	2006	Ethnicity	53.2	72.9	0.73
Georgia	2005	Ethnicity	86.9	97.5	0.89
Guinea-Bissau	2006	Language	44.9	64.7	0.69
Guyana	2006	Ethnicity	95.7	96.8	0.99
Kazakhstan	2006	Language	95.4	98.9	0.96
Kyrgyzstan	2006	Language	86.7	95.4	0.91
Lao PDR	2006	Language	52.4	88.7	0.59
Macedonia	2005	Ethnicity	61.1	97.8	0.62
Montenegro	2005	Ethnicity	69.4	100	0.69
Serbia	2005	Ethnicity	77.9	100	0.78
Sierra Leone	2005	Religion	68.3	72.3	0.94
Thailand	2005-06	Language	94.8	98.2	0.97
Togo	2006	Ethnicity	55.2	91.1	0.61
Uzbekistan	2006	Language	94.9	96.8	0.98
Viet Nam	2006	Ethnicity	93.8	95.7	0.98

Data source: MICS 2005-2006.

References

Huebler, Friedrich. 2008. Beyond gender: Measuring disparity in South Asia using an education parity index. Kathmandu: UNICEF.
Minority Rights Group International (MRG). 2009. Who are minorities?
United Nations Children's Fund (UNICEF). 2006. Multiple Indicator Cluster Survey manual 2005: Monitoring the situation of women and children. New York: UNICEF.

Data source

Multiple Indicator Cluster Surveys (MICS), 2005-2006.

External links

Friedrich Huebler, 1 March 2009 (edited 15 March 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/03/elr.html

Population structure and children out of school

2009-02-08T22:29:00.041-05:00

Sub-Saharan Africa is the region with the highest percentage of children out of school. At the same time, the population of most countries in Sub-Saharan Africa is increasing and children of primary school age constitute a large and growing share of the population.

The link between the population structure and the number of children out of school is shown in the figures and table below. Data on the share of children of primary school age out of school were obtained from the Childinfo website of UNICEF. The official primary school ages in individual countries from the Data Centre of the UNESCO Institute for Statistics were combined with demographic data from the UN Population Division to calculate the share of children of primary school age in each country's population. In total, data for 177 countries were available. All values are for the year 2007.

In Figure 1, the population of primary school age as a percentage of the total population is plotted along the horizontal axis. At the lower end of the scale are Belarus, Bulgaria, Germany, Latvia, Russia, and Ukraine. In these countries, children of primary school age account for less than 4 percent of the total population. The countries with the highest share of children of primary school age are located in Sub-Saharan Africa: Uganda (21 percent), Zambia (20 percent), Lesotho, Mozambique, Somalia (19 percent), Malawi, Swaziland, and Tanzania (18 percent).

The share of children out of school is plotted along the vertical axis. For five countries, the available statistics indicate that less than 0.5 percent of children are out of school: Japan, Malaysia, Spain, Uruguay, and Uzbekistan. In eight countries, half or more of all children are not in school: Somalia (77 percent), Chad (64 percent), Niger (62 percent), Liberia (61 percent), Ethiopia (55 percent), Eritrea (54 percent), Burkina Faso (53 percent), and Haiti (50 percent). Except for Haiti and Pakistan, the 20 countries with the highest share of children out of school are located in Sub-Saharan Africa.

The color of the marker for each country in Figure 1 indicates the geographic region according to the grouping used for the UN Millennium Development Goals (MDG). The size of each marker indicates the absolute size of the population of primary school age. The big red circle is the marker for India and the big green circle is the marker for China. Other countries with a large number of children of primary school age are Indonesia in South-Eastern Asia, USA in the developed countries, and Nigeria in Sub-Saharan Africa.

The distribution of the points in Figure 1 shows that countries with a small share of children of primary school age in the total population also tend to have a small percentage of children out of school. By contrast, countries with a relatively large population of primary school age also have a higher percentage of children out of school. This positive correlation between the two variables is confirmed by a linear regression of the percent of children out of school on the percent of children of primary school age and the squared percent of children of primary school age. The predicted share of children out of school is indicated by the dark gray line. The light gray band around the prediction line indicates the 95 percent confidence interval.

Figure 1: Population of primary school age and children out of school by country, 2007

Note: Marker size indicates the number of children of primary school age in a country.
Data source: UNESCO Institute for Statistics, UNICEF, UN Population Division.

For Figure 2, the data from the 177 countries in Figure 1 were combined by MDG region. The share of children of primary school age in a region's population is plotted along the horizontal axis and the share of children out of school along the vertical axis. The colors of the markers are the same as in Figure 1. The regional values, summarized in Table 1, reflect the 177 countries for which data were available.

Figure 2: Population of primary school age and children out of school by MDG region, 2007

Note: Marker size indicates the number of children of primary school age in a region.
Data source: UNESCO Institute for Statistics, UNICEF, UN Population Division.

At the global level, about 10 percent of the population are of primary school age. The regional values range from 4.6 percent in the Commonwealth of Independent States to 16.5 percent in Sub-Saharan Africa. The average share of children out of school across the 177 countries with data is 15.5 percent. In six regions, fewer than 10 percent of all children are out of school: Commonwealth of Independent States, developed countries, Eastern Asia, Latin America and the Caribbean, Northern Africa, and South-Eastern Asia. Sub-Saharan Africa has by far the highest share of children out of school, with 36.2 percent, followed by Southern Asia with 20 percent and Oceania with 17.1 percent.

Table 1: Population of primary school age and children out of school by MDG region, 2007

MDG region	Population of primary school age as share of total population (%)	Children of primary school age out of school (%)
Developed countries	6.4	4.6
Commonwealth of Independent States	4.6	6.8
Eastern Asia	7.1	0.8
South-Eastern Asia	10.8	6.5
Oceania	14.5	17.1
Southern Asia	10.8	20.0
Western Asia	12.5	12.5
Northern Africa	11.9	5.9
Sub-Saharan Africa	16.5	36.2
Latin America and the Caribbean	10.3	7.2
World	9.8	15.5

Data source: UNESCO Institute for Statistics, UNICEF, UN Population Division.

Due to their current population structure and demographic trends, countries in Sub-Saharan Africa have to provide schools and teachers for a relatively larger number of children than countries in other regions. The Millennium Development Goal of universal primary education by 2015 is therefore more difficult to meet for countries in Sub-Saharan Africa than for countries with a relatively small and constant or shrinking population of primary school age.

Data sources

Children out of school: UNICEF Childinfo, "Children out of school", January 2009.
Official primary school age: UNESCO Institute for Statistics, Data Centre, May 2008.
Population structure: UN Population Division, World Population Prospects: The 2006 Revision, March 2007.

External links

Friedrich Huebler, 8 February 2009 (edited 9 February 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/02/coos.html

The State of the World's Children 2009

2009-02-01T12:41:00.003-05:00

The 2009 edition of The State of the World's Children was released by UNICEF in January. The main theme of this year's report is maternal and newborn health. Women in developing countries are at a much higher risk of dying from complications during pregnancy or delivery than women in developed countries. For example, the lifetime risk of maternal death is 1 in 7 in Niger and 1 in 17400 in Sweden.

The statistical annex to The State of the World's Children contains tables with national, regional and global data on nutrition, health, HIV and AIDS, education, demography, economy, women, and child protection. In the area of education, the annex lists data for the following indicators:

Primary school enrollment and attendance rate
Secondary school enrollment and attendance rate
Survival rate to the last grade of primary school
Youth and adult literacy rate

The survival rate to the last grade of primary school replaced the survival rate to grade 5 that was reported in previous years. This change was made to match the official list of Millennium Development Goal indicators, in which the survival rate to grade 5 was replaced by the survival rate to the last grade as a new indicator for MDG 2, universal primary education by 2015.

The publication of The State of the World's Children was accompanied by an update of UNICEF's Childinfo website, where additional data and analysis can be found. For example, the education section of the Childinfo site lists new national estimates for the number of children out of school, among other statistics.

External links

Friedrich Huebler, 1 February 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/02/sowc.html

Educational attainment in Brazil since 1920

2009-01-24T17:51:00.001-05:00

Brazil is likely to reach the Millennium Development Goal of universal primary education by 2015. According to the UNESCO Institute for Statistics (UIS), 94 percent of all children of primary school age (7 to 10 years) were enrolled in primary school in 2005. Data from the 2006 National Household Sample Survey (Pesquisa Nacional por Amostra de Domicílios, PNAD), analyzed in an article on school attendance in Brazil, show that 99 percent of all children between 7 and 10 years were in pre-primary, primary or secondary education.

PNAD data can also be used to demonstrate how the education system in Brazil has expanded over the past decades. The PNAD survey collected information on the highest level of education attended for all persons in the sample. By comparing the highest level of education of persons born in different years it is possible to show the change in school attendance patterns over time. The following graph displays the highest level of education for persons born between 1920 and 2000. Household members born in 2000 were 5 or 6 years old at the time of the survey in 2006.

Highest level of education attended by year of birth, Brazil 1920-2000

Data source: Brazil National Household Sample Survey (PNAD), 2006.

Only 59 percent of all Brazilians born in 1920 ever attended school, and three out of four persons who attended school never went beyond primary education. Primary, secondary and tertiary school attendance rates increased steadily over the following decades. By the 1960s, nine out of ten Brazilians were able to receive a formal education. 91 percent of all persons born in 1960 attended at least primary school, 58 percent in this age group attended at least secondary school, and 14 percent went to a university.

The expansion of the primary education system began to slow down in the 1960s, after it had already reached a high level of coverage, but secondary school attendance rates continued to grow at a rapid pace. Among persons born in 1990, 98 percent attended primary school and 90 percent attended secondary school. Among persons born in 1994, 99 percent attended primary school. The peak value for participation in secondary education is 91 percent for persons born in 1988.

Fewer Brazilians have tertiary education, but almost one fifth of the population born around 1980 had attended a university or other institution of higher education by the time the PNAD survey was conducted in 2006. The peak value for participation in tertiary education is 19 percent for persons born in 1981.

Data sources

Brazilian Institute of Geography and Statistics (IBGE), National Household Sample Survey (Pesquisa Nacional por Amostra de Domicílios, PNAD), 2006
UNESCO Institute for Statistics (UIS), Data Centre, January 2009

External links

Friedrich Huebler, 24 January 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/01/brazil.html

Update to Stata guide

2009-01-08T22:56:00.003-05:00

I revised the guide to integrating the Stata statistical package with an external text editor. The programs described in the guide allow the execution of Stata commands directly from an external editor. The programs have been confirmed to work under Windows Vista, using the same installation procedure as for Windows XP. Most graphs and maps on this site were created with Stata.

Related articles

External links

Stata

Friedrich Huebler, 8 January 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/01/stata.html

Global Education Digest 2008

2008-12-28T11:14:00.004-05:00

The 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

Friedrich Huebler, 28 December 2008 (edited 31 July 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/ged.html

Education and democracy

2008-12-20T23:58:00.004-05:00

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.

Full democracies (score 8-10): 30 countries
Flawed democracies (score 6-7.9): 50 countries
Hybrid regimes (score 4-5.9): 36 countries
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

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)

External links

UNESCO Institute for Statistics Data Centre
ISO alpha-3 codes (United Nations Statistics Division)

Friedrich Huebler, 20 December 2008 (edited 21 December 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/democracy.html

EFA Global Monitoring Report 2009

2008-12-08T21:04:00.001-05:00

UNESCO 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

Friedrich Huebler, 8 December 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/12/efa.html

Multiple Indicator Cluster Survey blog

2008-11-23T17:02:00.002-05:00

The 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

Friedrich Huebler, 23 November 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/mics.html

Pupil/teacher ratio in secondary school

2008-11-16T13:12:00.002-05:00

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

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

UNESCO Institute for Statistics Data Centre

Friedrich Huebler, 16 November 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/ptr.html

School attendance in Brazil

2008-11-08T17:16:00.002-05:00

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

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

Brazilian Institute of Geography and Statistics (IBGE), National Household Sample Survey (Pesquisa Nacional por Amostra de Domicílios, PNAD), 2006
Brazilian Institute of Geography and Statistics (IBGE), population clock, November 2008
World Bank, quick reference tables, GDP 2007, September 2008
UNESCO Institute for Statistics (UIS), Data Centre, November 2008

External links

International Standard Classification of Education (ISCED), 1997

Friedrich Huebler, 8 November 2008 (edited 24 January 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/11/brazil.html

Education disparity trends in South Asia

2008-11-01T18:19:00.004-04:00

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

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

Pupil/teacher ratio in primary school

2008-10-26T10:17:00.004-04:00

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

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

External links

Friedrich Huebler, 26 October 2008 (edited 16 November 2006), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/ptr.html

UN Millennium Development Goals Report 2008

2008-10-17T20:33:00.002-04:00

In 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.

Eradicate extreme poverty and hunger
Achieve universal primary education
Promote gender equality and empower women
Reduce child mortality
Improve maternal health
Combat HIV/AIDS, malaria and other diseases
Ensure environmental sustainability
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

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)

External links

Official announcement of the MDG report 2008
UN Millennium Development Goals (UN Development Programme)
MDG indicators (UN Statistics Division)

Friedrich Huebler, 17 October 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/mdg-report.html

Education disparity in South Asia

2008-10-12T10:34:00.008-04:00

A 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

Friedrich Huebler, 12 October 2008 (edited 30 January 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/epi.html

Child labor and school attendance

2008-10-05T20:51:00.001-04:00

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

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 articles

External links

Friedrich Huebler, 5 October 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/10/child-labor.html

Child labor: economic activity and household chores

2008-09-07T23:23:00.003-04:00

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

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.

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

Household wealth and years of education

2008-08-24T15:12:00.003-04:00

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

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.

External links

Friedrich Huebler, 24 August 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/08/hh-wealth.html

National wealth and years of education

2008-08-03T23:28:00.004-04:00

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

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

School life expectancy: UNESCO Institute for Statistics, Data Centre, May 2008
GDP per capita: World Bank, World Development Indicators Online, July 2008
Population: UN Population Division, World Population Prospects: The 2006 Revision, March 2007

External links

Gross domestic product (Wikipedia article)
School life expectancy (definition by the UNESCO Institute for Statistics)
Purchasing power parity (Wikipedia article)
Logarithmic scale (Wikipedia article)
UNESCO Institute for Statistics
World Bank
UN Population Division
UN Millennium Development Goals

Friedrich Huebler, 3 August 2008 (edited 28 August 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/08/wealth.html

A view inside primary schools

2008-07-27T17:42:00.003-04:00

A 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

Download A view inside primary schools (PDF document, 2.9 MB)
Press release by the UNESCO Institute for Statistics
UN Millennium Development Goals

Friedrich Huebler, 27 July 2008 (edited 26 October 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/07/primary-schools.html

Updates to two Stata guides

2008-06-22T22:34:00.004-04:00

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

Adult literacy in 2007

2008-06-15T22:13:00.001-04:00

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

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

Literacy data from the UNESCO Institute for Statistics
UNESCO releases data from 2007 education survey
Adult literacy rates (article of July 2007)
Youth literacy rates (article of July 2007)
Disparity between adult and youth literacy
Disparity between male and female literacy rates
Adult literacy in Sub-Saharan Africa

External links

Friedrich Huebler, 15 June 2008, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/06/adult-literacy.html

Literacy data from the UNESCO Institute for Statistics

2008-06-01T15:40:00.007-04:00

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

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

UNESCO releases data from 2007 education survey

2008-05-18T21:53:00.007-04:00

The UNESCO Institute for Statistics (UIS) has released the data from its latest survey of international education indicators, conducted in 2007. The UIS Data Centre offers annual data for 208 countries and territories from the years 1999 to 2007. The previous survey had data for 207 countries and territories but starting in 2008, Serbia and Montenegro are listed separately, after both countries had declared their independence in 2006.

The graph below presents the distribution of the latest UIS data for two official Millennium Development Goal indicators, the primary school net enrollment rate (NER) and the survival rate to the last grade of primary school.

The primary NER is available for 178 countries. In 121 countries, the latest data is from 2006. For 10 countries - Egypt, Ethiopia, Ghana, Kazakhstan, Marshall Islands, Saint Kitts and Nevis, Sao Tome and Principe, Serbia, South Korea, and Vanuatu - the primary NER in 2007 is available.

The survival rate to the last grade of primary school is available for 157 countries. To calculate this indicator, data from two consecutive years is needed. For this reason, the latest available data for 88 of the 157 countries is from 2005. For 6 countries - Egypt, Ethiopia, Kazakhstan, Sao Tome and Principe, South Korea, and Tanzania - the survival rate for 2006 is provided in the UIS database.

Distribution of latest national data from UIS education survey 2007

Source: UNESCO Institute for Statistics, Data Centre, May 2008

Related articles

External links

Friedrich Huebler, 18 May 2008 (edited 26 October 2008), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2008/05/uis.html