1. Monitoring education inequality at the global level…
Monitoring education inequality at the global level
Manos Antoninis and Marcos Delprato,
EFA Global Monitoring Report
UKFIET conference
Oxford, 17 September 2015

2. Questions Monitoring education inequality: how?
 TAG / IAEG-SDG to propose education monitoring framework  2016 GMR to ‘interpret’ education monitoring framework e.g. turn target 4.5 “into one or two flagship indicators”?
So far we report inequality by country – easy on the eye but not easy to communicate for a global agenda
If all education indicators reported by three characteristics (sex, location, wealth) there are 135 different cases to report… – desirable but not easy to communicate
Education inherently unequal: what can be considered success?
Education inequality predictable: what information do we get?

3. Income and health Income distribution Ways to assess inequality trend
World Bank
Concept 1 = all countries
Concept 2 = all countries, weighted
Concept 3 = all individuals
Health Similar issues to education
WHO Health Equity Monitor

4. Education Learning outcomes Participation and attainment
e.g. OECD PISA
Participation and attainment
e.g. World Inequality Database on Education
Key messages? Compared with rich 20%, poor 20% are:
four times as likely to be out of school (OOSCI)
five times as likely not to complete primary (GMR)
six times as likely not to be literate (GMR WEF)
 How can we summarize information?

5. Analysis of education inequality
Analysis: 78 low and middle income countries
eight education indicators
four inequality measures
three individual characteristics
two points in time ( and )

6. Choice of characteristic
At least three options
Ratio by gender, location and wealth
e.g. East Asia and the Pacific

7. Choice of characteristic
At least three options
Ratio by gender, location and wealth
e.g. East Asia and the Pacific

8. Choice of characteristic
At least three options
Ratio by gender, location and wealth
e.g. East Asia and the Pacific

9. Change over time Compare trends
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa and all LICs/MICs

10. Change over time Compare trends
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa and all LICs/MICs

11. Change over time Compare trends …but weight by population?
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa
…but weight by population?

12. Change over time Compare trends …but weight by population?
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa
…but weight by population?
Different conclusions may arise…

13. Change over time Compare trends …but weight by population?
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa
…but weight by population?
Different conclusions may arise…

14. Change over time Compare trends …but weight by population?
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa
…but weight by population?
Different conclusions may arise…

15. Change over time Compare trends …but weight by population?
Ratio by wealth (poorest vs. richest 20%)
e.g. Sub-Saharan Africa
…but weight by population?
Different conclusions may arise…

16. Assessment of change over time (1)
Concentration curve
Distribution of education indicator, e.g. lower secondary completion rate, if we stack individuals by wealth in South/West Asia

17. Assessment of change over time (1)
Concentration curve
Distribution of education indicator, e.g. lower secondary completion rate, if we stack individuals by wealth in South/West Asia …and sub-Saharan Africa

18. Assessment of change over time (1)
Concentration curve
Distribution of education indicator, e.g. lower secondary completion rate, if we stack individuals by wealth in South/West Asia …and sub-Saharan Africa

19. Assessment of change over time (1)
Concentration curve
Distribution of education indicator, e.g. lower secondary completion rate, if we stack individuals by wealth in South/West Asia …and sub-Saharan Africa

20. Assessment of change over time (2)
Analysis of the determinants
For the three indicators, being male, living in urban areas or belonging to the richest 40% helps predict a positive outcome.
Has the strength of the effect changed between 2000 and 2010?
Ever been to school
Children in school
Adolescents in school
Male
-26%
-2%
-3%
Urban
Richest 40%

21. Assessment of change over time (2)
Analysis of the determinants
For the three indicators, being male, living in urban areas or belonging to the richest 40% helps predict a positive outcome.
Has the strength of the effect changed between 2000 and 2010?
Ever been to school
Children in school
Adolescents in school
Male
-26%
-2%
-3%
Urban
-13%
+46%
+16%
Richest 40%

22. Assessment of change over time (2)
Analysis of the determinants
For the three indicators, being male, living in urban areas or belonging to the richest 40% helps predict a positive outcome.
Has the strength of the effect changed between 2000 and 2010?
Ever been to school
Children in school
Adolescents in school
Male
-26%
-2%
-3%
Urban
-13%
+46%
+16%
Richest 40%

23. Choice of education indicator
Completion rates (0-100%)
Ratio by wealth By level of indicator and by country
Inequality measure tracks indicator value
Years of education (0-)
Concentration index By level of indicator and by country

24. Choice of inequality measure
Summary inequality measure…
e.g. range, ratio, odds ratio, concentration index
e.g. South and West Asia

25. Choice of inequality measure
Summary inequality measure…
e.g. range, ratio, odds ratio, concentration index
e.g. South and West Asia
or measure education poverty?
‘leave no one behind’
e.g. East Asia and the Pacific

26. Choice of inequality measure
Summary inequality measure…
e.g. range, ratio, odds ratio, concentration index
e.g. South and West Asia
or measure education poverty?
‘leave no one behind’
e.g. East Asia and the Pacific

27. Choice of inequality measure
Summary inequality measure…
e.g. range, ratio, odds ratio, concentration index
e.g. South and West Asia
or measure education poverty?
‘leave no one behind’
e.g. East Asia and the Pacific

28. Operational target? Headline figure?
Which education indicator, which inequality measure, which characteristic? And which level of that inequality measure counts as ‘progress’…
Country counts?
Model the relationship between the inequality measure and the education indicator Determine a level of inequality that is ‘too high’ for the level of education indicator and list countries exceeding that level…

29. Next steps For the international community: ensure coordination
Across SDGs
Coordinate global approach to monitoring equity across sectors (link data, promote surveys, build country capacity/demand etc.)
Agree on indicators
In the education sector:
Standardize and report data through new inter-agency group
Use more datasets in addition to DHS and MICS
Work with countries
For the 2016 GMR: deliver clear message
Develop and interpret regional and global averages
Continue debate on alternative formulations of target 4.5

30. Conclusions Focus on equity: easier said that done?
Summary measures can be powerful but:
…should not state the obvious
…should have an appeal to policy makers
…should lead to conclusions whether progress is made
Closer collaboration is needed if consensus is to be reached