15 March 2009

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.

Data source
Related articles
External links
Friedrich Huebler, 15 March 2009, Creative Commons License
Permanent URL: http://huebler.blogspot.com/2009/03/elr2.html

01 March 2009

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