International Development CommitteeWritten evidence submitted by Young Lives
Removing Barriers to Development for all Children Post-2015: Evidence from Young Lives, a Longitudinal Study of Children in Ethiopia, Andhra Pradesh India, Peru and Vietnam
Kirrily Pells, Young Lives, University of Oxford
1. Improving children’s life chances are central to the realization of the Millennium Development Goals (MDGs). Any evaluation of the process, therefore, needs to involve examination of progress made for the world’s poorest children to inform debates on what follows next. This submission is based on analysis of data gathered from children who have been growing up during the timeframe of the MDGs. and addresses three areas identified by the International Development Committee: lessons learned; targets, and the content of future goals.
2. This submission draws on Young Lives, a 15-year study of childhood poverty, which is following the lives 2,000 children born in 2000
3. Analysis from Young Lives suggests that the period of the MDGs have been associated with expansion of schooling and basic services, much of which has been pro-poor. There is however, evidence that not all children are benefitting equally. Children from the poorest households, from ethnic minorities or low-caste groups and from rural areas often have poorer outcomes in education, health and subjective well-being. In order to build on the foundation laid by the MDGs, a future framework needs to address inequality of opportunity.
Lessons Learned: What Matters for Healthy Child Development?
4. Poverty affects healthy physical and cognitive development and subjective well-being, and poses a threat to children in the present, as well as to their future adult lives and productivity. In line with the growing evidence base on the importance of the early years, Young Lives data show children who are stunted (an indicator of malnutrition), are also more likely to experience poorer later outcomes in cognition and psychosocial indicators (Dercon and Sanchez 2011; Le Thuc Duc 2009). 4 Across the four countries children who were stunted at the age of one had lower levels of cognitive ability at the age of five (Murray, 2012). Stunting also affects how children feel about themselves, with children reporting higher levels of shame or embarrassment (Dercon, 2008) and lower self-esteem or aspirations (Dercon and Sanchez 2011).
Improvement in children’s outcomes has not been equally shared
5. Recent economic growth is associated with average population improvements but does not appear to have translated into improved outcomes, such as lower stunting or higher literacy, for all children (Boyden and Dercon 2012). For example, Indian GNI per capita increased by 74.3% between 2002 and 2009 but the stunting rate of children aged 8 (comparing the two Young Lives cohorts) fell by 4 percentage points on average with the gains occurring among higher caste, other groups and the Backward Classes rather than among the (more disadvantaged) Scheduled Castes and Scheduled Tribes (Dornan 2011). Though the poorest children may have gained the least, outcomes are usually graduated, with the next 20% doing slightly better than the poorest 20% but still much worse than the least poor. For example, in Peru, children from the top 40% of households saw a nearly four times greater the reduction in stunting rates than children from the poorest 40% of households. The gains were statistically significant for the least poor three quintiles, but not significant for the poorest two quintiles. Disadvantage is established early in children’s lives and more is needed to break the link between background disadvantage and children’s later development.
6. However one important line of inquiry is physical recovery from early stunting. Paragraph 4 above noted the considerable evidence that early malnutrition, measured through stunting, has important later consequences. However panel data shows some children who were initially stunted (at age 1) physically recover by 5 years. Importantly analysis on data from Peru suggested those who had physically recovered from stunting had similarly vocabulary scores (a test of cognition) as those never stunted (Crookston et al 2011). Since prevention is better than cure, and since recovery is probably more common for those who were less stunted initially (Crookston et al 2010), this does not undermine the importance of improving early childhood conditions. It may, however, suggest hope for those children who have already experienced early life deprivations.
7. Children and their caregivers have high hopes for future, generated in part by increased access to schooling. Caregivers frequently expressed very positive attitudes towards both girls and boys education as a driver of social change (Pells 2011a). However, this is dependent on schools developing children’s skills and the availability of jobs in the right geographic and sectoral areas (World Bank 2012). Not all children are receiving the same quality of schooling. While more poor children were enrolled in school, literacy rates are low. For example, in Ethiopia, a comparison of children aged 8 in 2002 and children aged eight in 2009 shows greatest increase in school enrollment among children living in rural areas and for the poorest children (Woldehanna et al 2011). However, at the same time the ability of children to read and write without difficulty increased by only two percentage points with the gains occurring in groups with initially higher literacy levels (urban and the least poor). This indicates the importance of considering both household socio-economic status and the quality of schooling received by different groups.
Socio-economic disadvantage has cumulative, compounding, effects as children grow
8. Circumstances associated with household-based disadvantage continue to undermine children’s development. Figure 1 uses analysis of children’s test scores to show this for Ethiopia (but the pattern is similar for data from Andhra Pradesh, Peru and Vietnam, despite their different stages of economic development).
Figure 1
HOUSEHOLD WEALTH SHAPES CHILDREN’S TEST PERFORMANCE (ETHIOPIA)5
At age five poorer children typically did less well on the Cognitive Development Assessment (CDA) than better-off children and so were underrepresented in the high test score group and overrepresented in the low test score group (results were ranked so performance is relative to typical performance).
By the age of eight less poor children who scored badly at age five were typically doing better than poorer children who scored well at age five.
This pattern, of more able poorer children falling behind less able richer children is similar in each of the four counties (most acute in Ethiopia and Peru, where children from the low wealth/high score group fall below the high wealth/low score group, and less acute in Vietnam and India where the two groups converge).
Children from wealthier households who had a high test score initially tended to reduce their position slightly; those children from poorer households who performed poorly initially tend to improve slightly. (This overall convergence is likely to be due to the statistical phenomena of regression to the mean6).
9. This evidence demonstrates the importance of both household based anti-poverty strategies and interventions such as good quality early childhood care and education (ECCE) programmes. In all four countries, there are significant inequalities in access to ECCE and disparities in the quality of services available. For example, 95% of children from non-poor households in Peru attended pre-school at some stage but only 64% of the poorest children and between 54% and 76% of children from different ethnic minority groups (Escobal et al 2008). Qualitative research with children from ethnic minority groups in Peru has shown that these children start to feel excluded from the schooling system even before they enter primary school (Ames 2012). Disadvantage is therefore compounded.
Children’s opportunities are shaped by economic and community change
10. Against the backdrop of national economic growth, many households continue to experience multiple and recurrent adverse events or shocks, such as crop failure, food prices rises and family illness or death. The poorest households appear to have benefitted least from economic growth. They also face a disproportionate burden of individual and community wide shocks, and have fewer resources to cope with them. This in turn may perpetuate the transmission of disadvantage. Economic shocks can have long-term effects on children’s physical and cognitive development and well-being. Food shortages are also associated with poorer outcomes for children. For example, experiencing food shortages at age 12 was associated with poorer health and wellbeing outcomes at age 15 (after controlling for a range of factors, including ethnicity, location and household wealth):
were 60% less likely to have a healthy body mass index (BMI)-for-age in Peru
scored lower in cognitive achievement tests in Andhra Pradesh and Ethiopia7
reported lower self-rated health in Vietnam and Andhra Pradesh
reported lower subjective wellbeing in Ethiopia and Peru (Pells 2011b).
12. Of the children aged eight in 2009, one in three in Vietnam, nearly four in five in Andhra Pradesh, and nearly nine in ten in Ethiopia were in households that reported food price increases since 2006 (a period of global price spikes). Though households from all socio-economic groups reported food price increases, the poorest households are more vulnerable given they spend a higher proportion of their smaller budgets on food, as illustrated by Figure 2.8
Figure 2
HOUSEHOLD FOOD AND NON-FOOD CONSUMPTION, ANDHRA PRADESH, 2009
13. In summary, despite rising material standards and increased access to schooling and basic services over the period of the MDGs, large inequalities remain. Gaps between groups of children relate to household wealth, urban-rural location, belonging to an ethnic/language minority or low-caste group, gender and level of parental education. When these different sources of inequality are combined, negative impacts are compounded.
Implications: Targets and the Content of Future Goals
14. While recent economic growth, and policy development, has brought major benefits to many people, on-going disparities highlight equity concerns. Inequality of opportunity limits individuals flourishing to their full potential (Boyden and Dercon 2012). The key challenge of future goals is how to better link the driver of economic growth with the outcome of better human development. This has two key implications for the post-2015 agenda relating to targeting and the content of future goals.
Targeting: Addressing Inequality of Opportunity
15. Reporting of national averages within the MDG framework obscures the concentration of disadvantage observed in household level data. If the post-2015 agenda is to be refocused to increase the attention given to more marginalised groups, this will need to be reflected within measurement. Having an indicator on inequality or a tracker measure on a series of goals (eg not only the literacy rate, but the literacy rate of the poorer 20%) could play an important role in ensuring more equitable progress (Melamed 2012). Such an approach could monitor inequality across a number of areas, and could fit within either the existing or a new framework. The downside is that this approach could encourage a narrow targeting agenda, which is unlikely to yield strong public support, or decent quality, sustained, interventions. In addition, though the poorest children may do least well, it is also clear that poor outcomes are usually graduated. An alternative might be to use tracker measures, but with a slightly broader focus, of say 40%. A third option would be to have universal indicators, such as the current MDG 2 on primary school enrolment. However, though universal targets ought to focus attention on all children, policy makers may look to faster progress by focusing on those easiest to reach.
Content of future goals: better connecting growth to human development
16. If economic growth is not equitable it limits the potential to improve human development which affects long-term sustainable growth. It is not therefore just the rate of growth which is important but the way it is distributed that matters for poverty reduction (McKay 2009). This concern is both a social justice question of how to do the best for children, and a practical question of how to secure the human capital for more skilled and ‘healthier’ societies (World Bank 2012). This requires a focus which includes, but is broader than, money-metric indicators. While the existing MDG framework captures many areas of deprivation, including lack of food, safe drinking water and sanitation, access to education, health, information and communications, these are often not given as much prominence as growth in national planning income indicators.
17. The first implication of this may be give more prominence to other (human development) areas within the existing framework on which there has already been agreement. The second is the challenge for policy makers to develop more integrated responses to the multidimensional causes of poverty. International agreements such as the Rio principles of sustainable development and the social protection floor initiative illustrate a level of consensus on the importance of equity and on developing more effective systems of social policy.9
18. Third, the expansion of basic services and primary education has built an important foundation for child development. However, improvements in ‘process’ indicators such as enrolment have often been larger than ‘outcome’ child development indicators, and where there has been gains it has tended to be for the least marginalised children. If the future framework could be more outcomes-focused this could encourage better quality (as well as quantity) in service provision for children.
October 2012
References
Ames, P. (2012) ‘Language, culture and identity in the transition to primary school: Challenges to indigenous children’s rights to education in Peru’, in International Journal of Educational Development, 32: 454–464.
Boyden, J. and S. Dercon (2012) Child development and economic development: Lessons and future challenges, Oxford: Young Lives
Crookston, B., M. Penny, S. Alder, T. Dickerson, R. Merrill, J. Stanford, C. Porucznik and K. Dearden (2010) ‘Children Who Recover from Early Stunting and Children Who Are Not Stunted Demonstrate Similar Levels of Cognition’, in The Journal of Nutrition, 140(11): 1996–2001.
Crookston, B., K. Dearden, S. Alder, C. Porucznik, J. Stanford, R. Merrill, T. Dickerson and M. Penny (2011) ‘Impact of early and concurrent stunting on cognition’, in Maternal and Child Nutrition, 7: 397–409
Dercon, S. (2008) Children and the Food Price Crisis, Policy Brief 5: Oxford: Young Lives
Dercon, S. and A. Sanchez (2011) Long-term implications of under-nutrition on psychosocial competencies: Evidence from four developing countries, Young Lives Working Paper 72, Oxford: Young Lives
Dornan, P. (2011) Growth, Wealth and Inequality: Evidence from Young Lives, Policy Paper 5, Oxford: Young Lives
Escobal, J., P. Ames, S. Cueto, M. Penny and E. Flores (2008) Young Lives: Peru Round 2 Survey, Country Report, Oxford: Young Lives
Le Thuc Duc (2009) The Effect of Early Age Stunting on Cognitive Achievement Among Children in Vietnam, Working Paper 45, Oxford: Young Lives
McKay, A. (2009) ‘Relations between growth and the poorest’, Working Paper 126, Falmer: Chronic Poverty Research Centre
Melamed, C. (2012) Putting inequality in the post-2015 picture, London: Overseas Development Institute
Murray, H. (2012) Is school education breaking the poverty cycle for children? Factors shaping education inequalities in Ethiopia, India, Peru and Vietnam, Policy Paper 6, Oxford: Young Lives
Pells, K. (2011a) Poverty and Gender Inequalities: Evidence from Young Lives, Policy Paper 3, Oxford: Young Lives
Pells, K. (2011b) Poverty, Risk and Families’ Responses: Evidence from Young Lives, Policy Paper 4, Oxford: Young Lives
Woldehanna, T., R. Gudisa, Y. Tafere and A. Pankhurst (2011) Understanding Changes in the Lives of Poor Children: Initial findings from Ethiopia, Round 3 Survey Report, Oxford: Young Lives
Woodhead, M., P. Ames, U. Vennam, W. Abebe and N. Streuli (2009) Equity and Quality? Challenges for Early Childhood and Primary Education in Ethiopia, India and Peru, Working Paper 55, The Hague: Bernard van Leer Foundation
World Bank (2012) World Development Report 2013: Jobs, Washington DC: World Bank
1 Young Lives is core-funded from 2001 to 2017 by UK aid from the Department for International Development (DFID), and co-funded by the Netherlands Ministry of Foreign Affairs from 2010 to 2014.
2 As a pro-poor study Young Lives is not nationally representative and was not set up to directly monitor MDG targets. Data is collected on children and young people in 20 communities in each country. Alongside survey data Young Lives conducts qualitative research with a sub-sample of 50 children, their parents, teachers and community representatives, in each country. The recently published Changing Lives in a Changing World explores the experiences of 24 of these children and their families. This is available online at http://www.younglives.org.uk/files/books-and-book-chapterse/changing-lives-in-a-changing-world
3 www.younglives.org.uk
4 Stunting is defined as having a height for age below two standard deviations below the expected age (compared against WHO tables)
5 At age 5 children were tested with the CDA test. The CDA has ten questions exploring children’s understanding of quantities. At 8 children were tested on mathematics using a test out of 29 items exploring understanding of addition, subtraction and so on. At each point children were ranked. At age 5 high and low ability groups were further subdivided by material wealth (using a household wealth index, made up of service access, housing conditions and consumer durables). High wealth means children were in the least poor quintile; low wealth means children were in the poorest quintile. The chart shows each groups average rank at 5 and 8.
6 If a child does very well at first, next time it is more likely they will do the same or less well than that they do better so the group average rank position is likely to fall (and likewise in reverse for the low test group, whose average performance would improve).
7 This is a combined measure of two tests, one testing receptive vocabulary or school readiness, and the other testing maths. See K. Pells, ‘“Risky Lives”: risk and protection for children growing-up in poverty’, Development in Practice 22, 3, 2012
8 Households in Andhra Pradesh were grouped into quintiles (ranked by consumption level). The graph presents average spending level (on all items) as a line plotted on the right hand axis, and bars representing the percentage of household spending on food plotted against the left axis.
9 For the Rio Declaration on Environment and Development see http://www.unep.org/Documents.Multilingual/Default.asp?documentid=78&articleid=1163 and for the Social Protection Floor Initiative see http://www.ilo.org/wcmsp5/groups/public/---ed_norm/---relconf/documents/meetingdocument/wcms_183326.pdf