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 (%)|
|Other language||65.8 |
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|
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|
|Lao PDR||2006||Language||10.0 ||45.6||0.22|
|Viet Nam ||2006||Ethnicity||93.8 ||95.7||0.98|
- Multiple Indicator Cluster Surveys (MICS), 2005-2006.
- Disparities in primary school attendance by ethnicity, language or religion
- Caste, ethnicity, and school attendance in Nepal
- Education disparity in South Asia
- Education disparity trends in South Asia
Friedrich Huebler, 15 March 2009, Creative Commons License
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