Showing posts with label disparity. Show all posts
Showing posts with label disparity. Show all posts

Global Education Digest 2010

Cover of the Global Education Digest 2010On 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)
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Trends in adult literacy, 1990-2008

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
Graph with trends in adult literacy and gender parity from 1990 to 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 (%)
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.

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Children of primary and secondary school age out of school

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
Spine plot showing the distribution of the population of primary and lower secondary school age by region in 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
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
Bar chart showing the share of children of primary and lower secondary school age out of school by region in 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
Spine plot showing the distribution of children of primary and lower secondary school age out of school by region in 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).

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EFA Global Monitoring Report 2010

Cover of the EFA Global Monitoring Report 2010The 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
Graph with education disparity data from Nigeria
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)
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Regional disparities in school life expectancy

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
Graph with total, male and female school life expectancy by geographic region
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.

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Achievement gap between black and white students in the United States

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
Trendlines with reading scores of black and white students in the United States between 1971 and 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
Black White
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)
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Disparities in secondary school attendance by ethnicity, language or religion

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
Bar graph showing secondary school parity index in 17 countries
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
Min. Max.
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.

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Disparities in primary school attendance by ethnicity, language or religion

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
Bar graph showing primary school parity index in 17 countries
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
Min. Max.
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
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External links
Friedrich Huebler, 1 March 2009 (edited 15 March 2009), Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/03/elr.html
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