1. Measuring inequalities in learning for the Sustainable Development Goals: Lessons for policy Pauline Rose, Ben Alcott, Sonia Ilie and Ricardo Sabates REAL Centre, Faculty of Education University of Cambridge

3. Data sources Sample-based household surveys assessing children in and out of school: Citizen-led assessments Annual nationwide annual survey of children’s literacy and numeracy in India, Pakistan, Kenya, Tanzania and Uganda Sample size ranges from 87,000 in Uganda to 655,000 in India Young Lives Longitudinal study of children and young people in Ethiopia, India (Andhra Pradesh), Peru, Viet Nam Cohort of ~1000 children born around 1994; surveyed at age 8, 12, 15 & 19 Photo courtesy of Uwezo Uganda

4. House type Electricity Mobile phone Television Wealth Measuring wealth-based inequalities

5. Wide learning gap between rich and poor children 5

6. Steep progress needed to achieve basic learning for all Source: Author calculations based on ASER and UWEZO, 2012

7. Poorest girls are more likely to be out of primary school

8. In rural Pakistan, the poorest girls who are out of school have no chance of learning

10. In rural India, learning gaps widen in early years Source: Authors’ calculations based on ASER, India By age 11 only around 7% of poor girls have achieved the basics

11. Poorer children are far more likely to keep up when they get similar schooling opportunities Models: (1) OLS, (2) school fixed effects, (3) class fixed effects Source: Uwezo 2013, child ages 10–13

12. Poorer children are far more likely to keep up when they get similar schooling opportunities Models: (1) OLS, (2) school fixed effects, (3) class fixed effects Source: Uwezo 2013, child aged 10–13

13. Poorer children are far more likely to keep up when they get similar schooling opportunities to the rich Models: (1) OLS, (2) school fixed effects, (3) class fixed effects Source: Uwezo 2013, child ages 10–13

14. Wealth and early learning: the strongest determinants of university access Source: Authors’ calculations based on Young Lives data Richest children who are learning at age 8 Poorest children who are learning at age 8

15. Wealth and early learning: the strongest determinants of university access Source: Authors’ calculations based on Young Lives data Richest children who are learning at age 8 Poorest children who are learning at age 8 Richest children who are NOT learning at age 8

16. Wealth and early learning: the strongest determinants of university access Richest children who are learning at age 8 Poorest children who are learning at age 8 Richest children who are NOT learning at age 8 Poorest children who are NOT learning at age 8 Source: Authors’ calculations based on Young Lives data

17. Policy lessons to leave no one behind SDG monitoring Tackle disadvantage early Use data! Track progress from the early years Identify and implement policies associated with disadvantage in early years Use data to inform policy at local, national and global levels

18. Measurement lessons to leave no one behind + indicators Linkage Higher-order Comparative measures of wealth; include disability Link households and schools, panel data Add non-cognitive and advanced skills