Poverty and Gender Inequalities: Evidence from Young Lives more

Policy Paper 3 Poverty and Gender Inequalities: Evidence from Young Lives September 2011 Kirrily Pells Acknowledgements I am grateful to Abhijeet Singh for assistance with the quantitative data analysis for this paper, to Paul Dornan, Ginny Morrow and Caroline Knowles for helpful comments and to Isabel Tucker for careful editing. My thanks are due particularly to the data gathering teams in Andhra Pradesh, Ethiopia, Peru and Vietnam who carried out the data collection, upon which the report is written. An earlier version of this report was produced as a background paper for Plan International’s Because I am a Girl report 2011. I am grateful for comments from Nikki van der Gaag, Sharon Goulds and Keshet Bachan. The report is available at http://www.plan-uk.org/what-we-do/ campaigns/because-i-am-a-girl/research Readers are encouraged to quote or reproduce material from Young Lives papers in their own publications. In return, Young Lives requests due acknowledgement and a copy of the publication. Young Lives is a 15-year study of childhood poverty in Ethiopia, the state of Andhra Pradesh in India, Peru and Vietnam, following the lives of 3,000 children in each country. It 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. The full text of all Young Lives publications and more information about our work is available on our website. http://www.younglives.org.uk © Young Lives, 2011 The Author Kirrily Pells is Policy Officer at Young Lives. She completed a PhD focusing on rights-based approaches with children and young people in post-conflict situations, with a case study on Rwanda. This was followed by a postdoctoral fellowship at the School of Advanced Study, University of London. She has been a consultant for Save the Children UK, CARE International and the UK Foreign and Commonwealth Office. She is currently focusing on gender, risk and resilience and linking research with policy and practice. Young Lives Policy Paper 3: September 2011 Page 1 Contents Findings 1. 2. 3. Introduction About Young Lives Education: beyond primary enrolment 3.1 School trajectories: the impact of socio-economic context 3.2 Quality of education: from parity to equality 3.3 High aspirations shared by children and parents 3.4 Children face many obstacles in reaching their goals 2 3 5 6 6 8 11 13 4. Domestic life and intra-household dynamics 4.1 Gendered nature of children’s work 4.2 Age, location, household composition and shocks all affect children’s time use 4.3 Reproduction of gendered roles through children’s work 4.4 Intra-household decision-making: poverty exacerbates differences 15 15 17 19 20 5. Subjective well-being 5.1 Close association between poverty and children’s well-being 5.2 Intersecting inequalities affect subjective well-being 22 22 24 6. Conclusions and policy discussion 6.1 Building on enrolment: from parity to quality 6.2 Socio-economic change and addressing new sources of inequalities 6.3 Intersecting inequalities and improving life chances 27 27 28 28 References Appendix 1 29 31 www.younglives.org.uk/what-we-do/our-policy-work Page 2 Poverty and Gender Inequalities Findings 1. Analysis of Young Lives data offers a more nuanced picture of gender dynamics than that which is often presented in international policy debates, showing inequalities affecting both boys and girls at different ages through intra-household dynamics, sociocultural context and economic pressures. 2. National trends show that gender parity in primary school enrolment has been achieved in Vietnam and Peru but not Ethiopia and India (UNICEF 2010). Young Lives data show a more positive picture with gender parity within its samples across all four countries. Children’s trajectories beyond primary school reveal different patterning with Young Lives boys more likely to leave school earlier in Vietnam and girls in Andhra Pradesh. 3. While girls’ enrolment in school has increased, this does not necessarily mean that girls are receiving a quality education. Boys are performing better than girls in cognitive achievement test scores in Andhra Pradesh and Ethiopia. However, in Vietnam girls have a higher average performance in cognitive achievement tests. 4. Maternal education is an important factor associated with whether children leave school early. Across the countries for both cohorts, the level of maternal education appears to be a significant factor, with the percentage of children in school increasing with each level obtained. For example, in Andhra Pradesh only 68 per cent of children in the Older Cohort whose mothers received no formal education were in school, compared to 92 per cent whose mothers had received secondary education. This suggests that there is a history of disadvantage, where poorer men and women tend to marry each other, resulting in poorer households also having mothers with lower levels of education. 5. Children and parents share high aspirations for education outcomes yet cite many obstacles in realising these goals. While some challenges are shared between girls and boys, such as the lack of suitable employment or training opportunities and the constraints placed on the household by poverty, others are gender-specific, for example issues of marriage and social status. Processes of social change are creating new opportunities for girls but at the same time this entails social risk for girls and their families, whose livelihoods and social reputation may be at stake if they are out of step with the wider community. 6. Children’s time use is gendered in terms of tasks allocated to boys and girls. This suggests a way in which gendered roles are reproduced. Boys spend more time in unpaid work on family farms or businesses and girls spend longer caring for others and on domestic tasks. Children in rural areas spend more time in paid and unpaid work and children in urban areas spend more time in school and studying. Other factors which influence children’s time use are age sibling order and shocks. 7. Limited resources mean that parents are often forced to choose between sons and daughters in education expenditure. Rather than discrimination per se, parents base their decisions on the current realities of the labour market, as well as sociocultural norms. The fast growth of the low-fee private sector is increasing gender inequalities and creating debt traps. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 3 8. Poverty has a large impact on children’s subjective well-being, with poor children being much less likely to report having a ‘good life’ than non-poor children. In Vietnam, poor children are four times more likely to report experiencing a bad life than non-poor children. Poverty and inequalities can be compounded by different challenges faced by children living in urban and rural environments, a sense of feeling stigmatised, and gender-specific concerns of physical safety. 9. To improve gender equality and improve life chances for both poor girls and boys, policy interventions should target broader structural inequalities, between urban and rural environments and between households with different levels of consumption, especially the poorest households. 1. Introduction Starting with children as the means of breaking cycles of poverty and inequality has become increasingly central to international strategies to eradicate poverty. This is illustrated by targets on children’s education, mortality and health encompassed in the Millennium Development Goals (MDGs). More recently there has been increasing focus on adolescents, as demonstrated by the World Bank’s 2007 World Development Report and the most recent UNICEF State of the World’s Children report (published for 2011). Particular attention has been directed towards adolescent girls. The UNICEF report, for example, argues that ‘adolescence [here defined as being between 10 and 19 years old] is the pivotal decade when poverty and inequality often pass to the next generation as poor adolescent girls give birth to impoverished children’ (UNICEF 2010: 3). While analyses of gender inequalities have become mainstreamed within many poverty reduction strategies and policies (Chant 2011: 1) and encompassed within the MDGs, the focus has been predominantly on the inequalities between men and women, rather than between girls and boys (Jones and Chant 2009: 185–6). This has been challenged by the proliferation of initiatives focusing on girls, especially adolescent girls, such as Plan International’s Because I Am A Girl campaign and annual report; the Girl Hub funded by DFID and the Nike Foundation; and the Coalition for Adolescent Girls, founded by the United Nations Foundation and the Nike Foundation, which publishes the Girls Count series (Greene et al. 2009; Levine et al. 2008; Temin and Levine 2009).1 Among these initiatives there is a general consensus that gender dynamics in childhood and adolescence in the developing world are a much under-researched area, and all of them seek to combine research with advocacy calling for policies and resources to target adolescent girls as ‘the soundest way to break the intergenerational transmission of poverty’ (UNICEF 2010: 4). The emphasis is placed largely on girls’ future roles as mothers, supported by reference to research which argues that girls who stay in school for longer, will marry and have children later, thus decreasing the risk of maternal and child mortality and morbidity (Jones et al. 2010; Levine et al. 2008; Lloyd and Young 2009; Temin and Levine 2009; UNICEF 2010: 4). Alongside arguments around gender inequalities are economic analyses which have demonstrated that each year of education brings a higher earnings increment for women 1 For further information about Plan International’s Because I am a Girl campaign and reports see http://plan-international.org/girls; for Girl Hub see http://www.girlhub.org; and for the Coalition for Adolescent Girls see http://www.coalitionforadolescentgirls.org. www.younglives.org.uk/what-we-do/our-policy-work Page 4 Poverty and Gender Inequalities than men (Aslam et al. 2008). It is argued that women reinvest 90 per cent of their incomes back into the household compared to men, who reinvest 30–40 per cent (Jones et al. 2010: 5). However, one of the challenges of research in this area is that it is often reliant on a ‘time bias’, namely, measures of the situation of adult men and women, projected onto children, rather than measuring the current situation of children (Knodel and Jones 1996: 687; Jones et al. 2010: 1). Where research does focus on differences between boys and girls, a picture is painted of girls facing consistent disadvantages in life chances across education, health and well-being because of institutionalised gender bias as ‘from infancy, girls may be subject to lower parental investments in their care and nurture, and from early childhood to higher demands on their time and labour’ (Jones et al. 2010: 110). Young Lives is in a unique position to inform this debate, having collected three rounds of survey data on two cohorts of children since 2002. This report draws together Young Lives survey and qualitative data to analyse gendered differences between boys and girls and focuses on three key areas: education and aspirations, domestic life and intra-household dynamics, and subjective well-being. A couple of caveats are important to bear in mind. Firstly, although they reflect a wide range of cultural, economic, geographical, political and social contexts, only four countries are covered by the Young Lives study (Ethiopia, the Indian state of Andhra Pradesh, Peru and Vietnam). Secondly, Young Lives is a study of childhood poverty and so does not capture all aspects of children’s experiences. What follows is therefore a gender analysis of a poverty study, rather than a gender study. Here gender analysis is understood as examining the differences between life chances for boys and girls and how these relate to broader socio-economic processes and inequalities. Young Lives data reveal a nuanced picture regarding gender and inequalities between boys and girls, with differences not as large as often assumed in advocacy initiatives (Dercon and Singh forthcoming). Drawing on descriptive and analytical evidence the following five arguments are made. ●● The longitudinal nature of the study highlights the ways in which gender dynamics differ when children are at different ages and accumulate over time. Both boys and girls can encounter disadvantages relating to their gender, which impacts on their life chances. Disaggregating the data by gender and location (urban/rural), gender and household consumption level, and gender and ethnicity/caste suggests that gender is one of several variables (and not the most significant) which impact on children’s experiences and life chances. Gender inequalities often intersect with other markers of disadvantage, such as belonging to an ethnic minority group, which can compound the extent of the inequality. The specific patterning of inequalities varies between the study countries, primarily because of socio-economic factors, as well as between different outcomes in education, time use and subjective well-being within the countries. ●● ●● ●● ●● The findings suggest that in improving gender equality, policy interventions, such as improvements to education quality or social protection programmes, should target broader structural inequalities between urban and rural environments and between households with different levels of consumption, and, in particular, support the poorest households. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 5 This paper accompanies a series of detailed country reports which analyze the first three rounds of survey data (Escobal et al. 2011; Galab et al. 2011; Le Thuc et al. 2011 and Woldehanna et al. 2011) and two policy papers (Dornan 2011 and Pells 2011). This paper focuses in-depth on child-level outcomes which are the result of the broader trends in consumption growth, wealth and inequality discussed in policy paper five (Dornan 2011). This report begins with an overview of the Young Lives study and emerging findings on gender, before exploring each of the three key areas in depth. The report concludes by considering the implications for policy. 2. About Young Lives Young Lives is a longitudinal study of childhood poverty which has been collecting both survey and qualitative data on around 12,000 children since 2002 in four countries (Ethiopia, the Indian state of Andhra Pradesh, Peru and Vietnam). The study comprises: ●● An Older Cohort of around 1,000 children in each country (fewer in Peru) born in 1994/5. Household- and child-level data were collected on this group when they were 8, 12 and 15 years old. In-depth qualitative information was collected on 25 Older Cohort children in each country in 2007 and 2008 when they were 13 and 14 years old. A Younger Cohort of around 2,000 children in each country born in 2001/2. Survey data were collected on this group when they were 2, 5 and 8 years old. Qualitative information was collected with 25 Younger Cohort children per country in 2007 and 2008 when they were 6 and 7 years old. Survey and qualitative data were also collected at the household level from caregivers and at the community level in the form of interviews and focus group discussions. ●● ●● Young Lives has also carried out various qualitative sub-studies, plus a school component in Ethiopia in 2009 and in Andhra Pradesh in 2010. The focus of the Young Lives study is pro-poor, meaning it focuses on children growing up in poorer populations. The data therefore are not nationally representative, nor should they be compared simplistically between the Young Lives countries, since the samples of children are drawn differently. What such panel data can be used to highlight are some of the disparities within the samples, how change over time is affecting children and what similar (or different) processes are going on in each of the Young Lives countries. All the names of Young Lives children referred to in this report are pseudonyms. (For further information see the technical notes section of Young Lives website http://www.younglives.org.uk/our-publications/technical-notes) www.younglives.org.uk/what-we-do/our-policy-work Page 6 Poverty and Gender Inequalities 3. Education: beyond primary enrolment Achieving gender parity in primary school enrolment features both among the eight MDGs and the six Education For All (EFA) goals. Huge advances have been made globally in reaching this goal (with the notable exceptions of some countries in the Middle East, North and West Africa and West and South Asia) (UNICEF 2009: 18; UNESCO 2010: 20) and the experiences of Young Lives samples across the four countries reflect this achievement. At the same time there is growing recognition that while enrolment is crucial, it is only part of the story (UNESCO 2010). Looking beyond enrolment indicators reveals a much more complex picture around gender differences and education, discussed in this section in relation to educational trajectories, the quality of the education received, the learning environment, and aspirations to higher education and work. 3.1 School trajectories: the impact of socio-economic context National trends show that gender parity has been achieved in Vietnam and Peru but not Ethiopia and India (UNICEF 2010). Young Lives data show a more positive picture with gender parity within its samples across all four countries. Within the Young Lives samples children’s trajectories beyond primary school reveal different patterning, illustrating how gender dynamics play out according to age and socio-economic context. Tables 1 and 2 compare different patterns (rather than levels, owing to the pro-poor nature of the samples) of school enrolment of Young Lives children in the Older Cohorts in Vietnam and Andhra Pradesh. Table 1 shows that in Vietnam the boys are less likely to be in school, with 23 per cent leaving between the ages of 12 and 15 years old (at the aged of 12, 96.7 per cent of boys and girls were enrolled), nearly a third more than girls (16 per cent) and most markedly among ethnic minorities. This could be due to the higher wage-earning potential of boys as opposed to girls, or to boys doing less well in exams (UNESCO 2010: 67; Grant and Berham 2010: 87). This disparity is intensified by poverty, as only 40 per cent of poor boys are in school at the age of 15 (although enrolment among girls from poor backgrounds is still only 52 per cent).2 Table 1. 14–15-year-olds enrolled in school by location, ethnic group and living standards, Vietnam (%) VIETNAM Boys Overall Urban Rural Above poverty line2 Below poverty line Majority ethnic group Minority ethnic groups 72.2 86.0 69.1 73.7 40.0 76.3 46.0 Girls 80.0 90.6 77.7 81.6 52.0 83.8 54.7 2 The poverty line used here is 50 per cent of the median household consumption level within the Young Lives sample, calculated separately for each country. The distribution of the samples also varies between countries. For example, the distribution or range of household consumption levels is much larger in Vietnam, and there are a smaller number of very marginalised households included in the Young Lives sample. In Andhra Pradesh, the distribution of household consumption levels is more compressed, resulting in a smaller difference between those classified above and below the poverty line. Throughout this report ‘poor’ refers to those households below this relative poverty line and ‘non-poor’ to households above the poverty line. Due to the pro-poor nature of the sample the ‘non-poor’ households still do not necessarily have high levels of consumption. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 7 In contrast, Table 2 indicates that in Andhra Pradesh there is a different trend, with a higher drop-out rate among girls. Yet among children from households from below half the median consumption level (classified as poor) girls are more likely to be in school than boys. This illustrates how gender and poverty intersect to disadvantage different groups of children. This is also highlighted by the large gap in enrolment figures relating to boys and girls from the Scheduled Castes. While Young Lives data show a slight bias towards girls from the Scheduled Tribes being enrolled at age 15, this may not be typical across Andhra Pradesh, reflecting instead the sentinel site sampling methodology. Table 2. 14–15-year-olds enrolled in school by location, caste and living standards, Andhra Pradesh (%) 3 ANDHRA PRADESH Boys Overall Urban Rural Above poverty line Below poverty line Scheduled Castes Scheduled Tribes Backward Castes Other 2 81.0 86.4 78.8 81.9 71.8 82.5 74.4 79.4 85.4 Girls 74.0 82.9 71.0 74.2 83.3 67.3 76.9 71.7 84.7 In line with other studies we have also found that the level of maternal education is an important factor associated with whether children leave school early (Levine et al. 2008: 20–1; UNICEF, 2009: 18–19). Across the countries for both cohorts, the level of education reached by caregivers (the majority in our samples being women) appears to be significant, with the percentage of children in school increasing with each level obtained.4 For example, in Andhra Pradesh only 68 per cent of the Older Cohort whose mothers received no formal education were in school, compared to 92 per cent whose mothers had received secondary education. More analysis is required to understand what underlies this association but it suggests that there is a history of disadvantage, where poorer men and women tend to marry each other, resulting in poorer households also having mothers with lower levels of education (see also Pells 2011). The disparity in access to education between children in the poorest quintile and the richest quintile is a global pattern. The 2010 United Nations Millennium Development Goals Report examined 42 countries and found that twice as many girls of secondary school age from the poorest 60 per cent of households were out of school, compared with girls from the wealthiest 40 per cent of households. A similar disparity existed for boys of the same age (cited in UNICEF 2010: 67). This has led to criticisms of policies which focus on gender differences to the neglect of socio-economic factors (Knodel and Jones 1996: 684). Multiple factors intersect, to cause children to leave school. The following account is typical in that it illustrates how poverty is compounded by adverse events, to which poor people may be more vulnerable, as well as gender-specific factors, in this case Latha’s future marriage prospects. Keeping Latha in school would not address the risks faced by the household. 3 ‘Other’ refers to children from higher castes or other religions. 4 The term ‘caregiver’ has been used in recognition of the fact that children are not always cared for by their biological parents. Where a quotation has been attributed to a caregiver, this individual is either a relative or guardian but not the biological parent of the child. www.younglives.org.uk/what-we-do/our-policy-work Page 8 Poverty and Gender Inequalities Why Latha left school Latha, aged 15, lives in rural Andhra Pradesh and is from a Backward Caste. She studied until seventh grade, when she left school, two years ago. Her mother explains the multiple reasons leading to this decision: “... our position was not good, our son passed away. We were in sorrow,” and so Latha was required to work in the fields on a groundnut plantation. Studying beyond seventh grade would have meant Latha travelling to school in another village and her mother was concerned about her daughter’s reputation: “It would have been better, if she had continued her studies but again this is … all right. If she studies here and there, goes to towns, friendships are formed. That may happen. So, we stopped.” Latha’s mother also stressed the importance of teaching her daughter both domestic and field work in preparation for marriage: “If we give her away to another’s house, there they will scold her if she does not do the work saying, ‘Who taught you the work? Did your mother and father not teach you?’” She feels proud that other community members have commented that Latha is being taught well by her parents. Although she is keen for her daughter to be married, she will not force her: “We cannot pressurise. We cannot say you should marry – only if they like.” 3.2 Quality of education: from parity to equality While there is a positive story of increasing enrolment, this does not necessarily translate into girls receiving a high-quality education. The fifth Education For All goal urges a shift from gender parity in enrolment to gender equality, namely that boys and girls receive the same quality of education. Using two educational outcome measures (tests of receptive vocabulary5 and maths) as a proxy for quality, we found that Young Lives boys were performing better than girls in India and Ethiopia, and Young Lives girls were performing better than boys in Vietnam. There was little difference in Peru. These trends are illustrated by Figures 1 and 2. Figure 1. Distribution of maths scores, 14–15-year-olds, Andhra Pradesh Boys .08 Girls Proportion of children 0 0 .02 .04 .06 5 10 Number of correct responses 15 20 5 Recognising the cultural specificity of the PPVT as a test developed in English for US populations, Young Lives adapted and translated the test and local teams replaced unfamiliar items. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 9 The graphs show the distribution of test scores of the Older Cohort sample, according to gender and the number of correct answers answered. This means that the further right the child is on the graph, the higher the score obtained, and that the higher the line is, the greater the number of children with that score. The higher number of girls on the left of Figure 1 (Andhra Pradesh) and the right of Figure 2 (Vietnam) illustrate how girls are outperforming boys in Vietnam and the reverse in India. These are just two examples of how performance seems to be impacted by policy and sociocultural processes that result in boys and girls experiencing school differently, which impacts on learning outcomes and future trajectories into work and higher education. Figure 2. Distribution of maths scores, 14–15-year-olds, Vietnam Boys .08 Girls Proportion of children 0 0 .02 .04 .06 5 10 Number of correct responses 15 20 Young Lives findings from Vietnam mirror an emerging global picture of more boys leaving school and performing less well in middle- and higher-income countries (World Bank 2011: 1–3). Grant and Behrman’s (2010) analysis of the gender gap in current school enrolment and grade completion across the educational cycle from 6–18-year-olds in 38 developing countries reveals that boys are more likely to be enrolled in school than girls (except in Latin America and south-east Asia). Once in school, however, girls make equal or better progress than boys except for 16–18-year-olds in south Asia and west Asia/north Africa. Gender is not the only factor associated with differing learning outcomes, as across the four Young Lives countries maths test scores rise in a linear fashion according to household consumption level. Globally it is observed that on average ‘gender gaps in education and health are small compared to gaps in outcomes across ethnicity, socio-economic class or geographical location’ (World Bank 2011: 5). Within Young Lives data the gap in achievement between the first (lowest) and fifth (highest) quintile is larger than differences in achievement between boys and girls. Moreover, the gender gap (whether bias towards boys or girls) stays fairly consistent across the quintiles, challenging a double disadvantage hypothesis (i.e. that gender differences are compounded by poverty). This is indicative of an ‘inverse care law’, whereby poorer children often attend schools with fewer resources and receive a poorer- www.younglives.org.uk/what-we-do/our-policy-work Page 10 Poverty and Gender Inequalities quality education (UNESCO 2010: 23). Another reason for the association between household consumption and test scores is that enrolment figures mask the amount of time children are absent from school because of outside pressures. As demonstrated in section three, poorer children spend less time in school including because of the need to engage in paid or unpaid work to support their household. There are gender-specific factors which may affect children’s experiences at school and in turn their learning outcomes. In Ethiopia and Andhra Pradesh girls may be absent each month because of menstruation and the lack of adequate sanitation facilities and gender-segregated toilets at school: “We do not have bathrooms there. They have started but the construction is not yet completed and I don’t like that aspect in the school. It is very difficult for us, particularly girls, and those who come from neighbouring villages. During the monthly cycles it is more difficult, so some girls don’t come to school on those days.” (Rural girl, aged 15, Andhra Pradesh) Caregivers also described keeping girls at home during menstruation: “Suppose if she gets the menstrual cycle at school, she returns home. She will take a bath and keeps her things separately for two or three days … She says, ‘I should be outside. I should not come into the house.’ … It is our system; we do not allow them in the house.” (Mother, rural Andhra Pradesh) The caregiver went on to elaborate how, although her daughter wants to go to school during menstruation, she is not allowed due to cultural practices concerning beliefs of impurity. Violence at school is another factor impacting upon children’s experiences. Corporal punishment by teachers was reported by both boys and girls in all Young Lives study countries, although at a higher prevalence by boys. The following case study illustrates how the school environment can impact differently on boys and girls and how, through disciplinary measures, it reproduces gender-stereotyped behaviour, which may contribute to a broader culture of violence. Violence at school In Peru, both boys and girls reported corporal punishment by teachers: Peter: [About the assistant] He hits you, he shouts at you, he punishes you … Javier: He doesn’t like you to answer him … Peter: … he slaps you. Diego: He doesn’t like disorder in school. Interviewer: Are you OK with his attitude? Diego: No, but he starts hitting us. Javier: He beats us with a stick. Interviewer: Where does he hit you? Javier: On the foot. Sergio: On the rear. Peter: The thigh, the thigh. Dante: The hand. Cecilia: Sometimes we also get beatings. Dora: With a huge stick, like this [imitates the whizz of a moving stick]. Interviewer: Where, here? [points at her hand] Dora: Yes, the hand. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 11 Violence at school continued Boys discussed how they became ‘used to’ violence and said that hiding pain in front of their peers was an important part of being considered ‘cool’: Interviewer: What do you think of being chased or hit with a stick? [silence] Is it OK – is useful or not? Felipe: It doesn´t hurt. Interviewer: It doesn´t hurt? Javier: It depends on who is hitting you. Interviewer: For example? Sergio: When they hit you on the hand [it hurts]. Felipe: When others get hit, they run. I stay there and take it, but it doesn´t hurt. Peter: Yes, right? Felipe always stays there, standing. Felipe: You get used to it. As Rojas (2011) argues, ‘in this way peer relations end up reproducing the authoritarian and masculine system of the school, where power relations are closely associated with the control of physical strength’. Interviewer : Why do you beat up your classmates? [hacer poste or ‘the pole’: several students carry a student in, open his legs wide and run against a pole to hit his genitals] Peter: For revenge. Dante: It´s a joke … Peter: Sometimes for fun. Interviewer: Sometimes for fun? Javier: When some of us are bored, we beat them up. Peter: Beating, beating. Interviewer: When is revenge needed? Felipe: When somebody gets the rest punished … Sergio: When one pays, everyone else pays. When it rains we all get wet. Quotations taken from Rojas (2011) 3.3 High aspirations shared by children and parents Contrary to claims that parents with low levels of education have low aspirations for their children (Appadurai 2004), across the countries in the Young Lives study, caregivers frequently expressed very positive attitudes towards girls’ schooling. Women in particular were keen for their daughters to have opportunities denied or unavailable to them when younger: “In the past girls married at the age of 15 but now things have changed. Girls can marry at the age of 20 and even 30. My wish for my daughter is that she should marry after she has become self-reliant; I wish her to complete her education, then to have her own work and then to marry a person whom she loves and with whom she wants to live.” (Caregiver [grandparent], aged 70, rural Ethiopia) Figure 3 displays the percentage of children aged 14–15 years old who, when asked ‘Ideally, what level of education would you like to complete?’ replied “University”. It demonstrates the high level of children’s aspirations, and these are not necessarily tied to the stage of the country’s economic development, with children in Ethiopia reporting at a similar level to those in Peru. Gender differences are largest in India and Vietnam, and mirror the same pattern in differences in enrolment and educational achievement, with boys aspiring higher in India and girls in Vietnam. www.younglives.org.uk/what-we-do/our-policy-work Page 12 Poverty and Gender Inequalities Figure 3. 14–15-year-olds who would ideally like to complete university 90 Boys 80 70 60 Percentage 50 40 30 20 10 0 Girls Andhra Pradesh Ethiopia Peru Vietnam Figure 4 displays the aspirations of caregivers of the Younger Cohort of children (who were aged 8 at the time of data collection). The trends have largely similar patterns to those in Figure 3 although the gender differences are smaller than in the children’s reporting and in Peru there is a reverse of the trend, with a slight bias towards higher aspirations for sons. Both Young Lives children and caregivers in Andhra Pradesh seem to have lower aspirations than in the other three countries but may either reflect a more realistic assessment of the situation, given the many obstacles to reaching university, or cultural specificity in the way that the question was asked. Figure 4. Caregivers of 8-year-olds who would ideally like their children to complete university 90 Sons 80 70 60 Percentage 50 40 30 20 10 0 Daughters Andhra Pradesh Ethiopia Peru Vietnam Although the question is asked about an ideal situation, when the follow-on question ‘Given your current situation, do you expect that your child will reach that level of education?’ was asked, again children and caregivers were overwhelmingly positive. Over 94 per cent of www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 13 caregivers in Andhra Pradesh, Ethiopia and Peru believed their children could achieve this level, with no differentiation between sons and daughters. In Vietnam the percentages were lower (but still high overall), with a small gender difference as 83 per cent of caregivers expected their sons to reach that level and 87 per cent their daughters – mirroring the other Vietnam-related indicators, which point to better outcomes for girls. Though it may seem unrealistic, this positive view of schooling contradicts a ‘poverty of aspiration’ among both children and caregivers. 3.4 Children face many obstacles in reaching their goals Despite this optimism both children and parents describe many obstacles that they currently face, or anticipate when attempting to realise these goals. As with leaving school, multiple factors intersect, some gender-specific, others affecting both boys and girls. Six principal obstacles emerged from analysis of the qualitative data gathered in India and Ethiopia: marriage, dowry-related concerns, physical security, health, lack of opportunities after vocational training or higher education, and poverty, which underpins the other five. The following story illustrates the fears often shared by girls and their mothers about early marriage in rural Ethiopia and how this interlinks with other factors. At the same time it demonstrates the positive and supportive role that male family members can play. The threat of early marriage Ayu lives in a rural area in Ethiopia. She is 10 years old. Ayu would like to become a teacher and be able to support her parents financially. She does not want to marry until later as she feels that “education is better for me”. She worries about the state of her health. “Sometimes the illness [malaria] is strong and I am absent from school on these days. This disappoints me. I have a strong fear that the illness may continue deteriorating rather than improving and this may hamper my education and other aspects of my life.” Ayu also fears that her parents may force her to get married but her mother wants her daughter to have opportunities that were denied to her because of her own early marriage: “Education is the most important thing to change her life; it is the best alternative for girls at the present. This is my wish but I do not know her father’s intention … He has a strong interest in marrying them [her daughters] to somebody, and getting the bride wealth from the family of the husband. If one of my daughters is taken tomorrow, the next day the families of the husband will bring a huge amount of money (1,000 birr at the beginning, and five cattle and additional money will come at the next time). … Sometimes the girls may be taken while they play with their friends or go the house of neighbours to pass on a message.” However, Ayu’s mother feels that Ayu’s uncles will help her persuade her husband not to marry Ayu until she has completed her schooling. She also explains that Ayu’s “brothers, particularly the elder one … advise her to be strong in her education” and says they persuaded Ayu to continue at school when she considered leaving in order to work to support the household. For the coming year Ayu will go to school locally but after that her mother believes that “it will be better for her to continue in a town”. This brings additional concerns as she fears her daughter being raped or being exposed to illness but also feels reassured that “she [Ayu] will not face any problem because her brothers, her uncles and her grandmother are there”. Processes of social change are taking place, bringing opportunities, particularly in formal education, with children able to study longer than their parents. At the same time, being on the cusp of a wave of change entails a degree of social risk for families, whose livelihoods and social reputation may be at stake if they are out of step with the wider community (Boyden and Crivello, forthcoming). Although not without implications for boys, the competing tensions centre more frequently around girls. In Ethiopia poverty may lead families to marry daughters www.younglives.org.uk/what-we-do/our-policy-work Page 14 Poverty and Gender Inequalities in order to receive the bride wealth. In India, dowries (although legally prohibited) are frequently paid by the bride’s family, and poverty here too plays a role in deterring girls from formal education as some caregivers fear that educated girls may entail a higher dowry: “If she were educated – I mean even if she were to have passed the tenth grade – people would be apprehensive [in making an offer of marriage] … they would say that educated girls didn’t know how to work manually. With this excuse they would demand maybe 50,000 rupees as a dowry. From where can I get such a huge amount of money?” (Mother, rural Andhra Pradesh) Interlinked with this are caregivers’ fears that others may doubt the reputation of their daughters if they have spent time away from home studying in towns or boarding in hostels, because of the potential for interaction with boys, which may reduce their marriage prospects (Jones et al. 2010: 5–6; Levine et al. 2008: 5; UNESCO 2010: 26). A male community member in Ethiopia expressed it like this: “Some families are worried about their daughters and inclined to give them for marriage at an early age because of the fear that they have about their daughter, in order not to expose her to sexual abuse.” Concerns about marriage dowries are not unique to girls. Boys also stated a sense of responsibility towards wage earning, to enable their sisters to marry, as illustrated by Govindh, aged 12 from rural Andhra Pradesh: “Mother goes to work daily for wages. My father goes to work only sometimes. If there is no work he comes back. He is not that good at work.” He describes the situation at home as “not good” and says that the family does not receive help from relatives. Consequently he feels responsibility for securing enough money for his sister’s marriage and wants “to take more responsibility than my parents”. Another factor hindering both boys and girls in achieving their aspirations is the lack of training opportunities and suitable jobs available after education. (Levine et al. 2008: 6–7): “There are many young people who trained in different activities but they do not have job opportunities. There is no spare land in this kebele [local administrative unit] even for young people who are trained in different activities to get involved in some kind of business. They are interested in work but they do not have opportunities.” (Female community member, urban area, Ethiopia) This leads some parents to question the value of keeping children in school: “… even if she were educated it is still not possible to get a job … So what’s the point in getting schooled? No schooling can get her a job” (mother, rural Andhra Pradesh). In this case both the son and daughter had left school in order to assist the mother in earning enough to support the household. At present it is not certain how these processes of social change will play out – whether girls will be able to build on increased access to primary school and make successful transitions to secondary school and beyond. World Bank research has shown that female participation in the labour force has not increased at the same rate as school enrolment rates, and even when girls achieve the same as boys at school, more young men make the transition into paid work than young women (Buvinic et al. 2007). www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 15 Key messages ●● Gender parity in primary school enrolment has been reached in Young Lives samples across all four countries. Children’s trajectories beyond primary school reveal differing patterns according to the intersection between gender and socio-economic context. At the secondary level Young Lives data from Ethiopia, Peru and Vietnam show that girls are more likely to be in school, with the reverse trend in Andhra Pradesh. Children leave school because of the intersection of multiple factors. While there is a positive story of increasing girls’ enrolment, including at the secondary level, once in school, girls face a range of challenges relating to the quality of the school environment and the quality of education received, and their future trajectories to higher education or better-paid employment are heavily influenced by broader socio-economic factors. Children and parents share high aspirations yet cite many obstacles in realising these goals. While some challenges are shared between girls and boys, such as the lack of suitable employment or training opportunities and the constraints placed on the household by poverty, others are gender-specific, for example issues of marriage and social status. Processes of social change are creating new opportunities for girls but at the same time this entails social risk for girls and their families, whose livelihoods and social reputation may be at stake if they are out of step with the wider community. Process indicators such as school enrolment rates are important but should be accompanied by indicators of quality, to monitor differences in schooling received and the learning environment, for boys and girls, as well as ethnic minorities and other marginalised groups. This includes taking measures which will reduce obstacles to girls’ learning, for example, providing gendersegregated toilets and locating schools near to communities in order to cut down the time needed to travel or for hostels. More broadly, flexibility in the schooling system would enable poor girls, as well as boys, to better manage competing demands on their time: the need to support the household through paid or unpaid work and to attend school. Finally, in order for children and parents’ high aspirations to be reached it is important that school equips children with the skills needed to access the labour market, vocational training and higher education. ●● ●● ●● 4. Domestic life and intra-household dynamics Children’s life chances are strongly influenced by the economic status of their household and the impact which this has on intra-household decision-making processes. Understanding these factors is important for understanding children’s trajectories not just through school but also into work and establishing households of their own. This section explores the gendered nature of children’s time use and work and examines whether parents differentiate between sons and daughters and, if so, in what domains and why. 4.1 Gendered nature of children’s work Children’s time use is gendered in terms of tasks allocated to boys and girls and the amount of time spent on those tasks (Bourdillon et al. 2010: 71; Jones et al. 2010: 2; Ritchie et al. 2004). This is illustrated by the following graph which shows the average daily number of hours children in the Older Cohort in Ethiopia spend on each activity. (Averages only include those children engaged in each activity, not all children in the cohort, and should therefore be interpreted with caution. Time use for children not in school would look very different, for example.) www.younglives.org.uk/what-we-do/our-policy-work Page 16 Poverty and Gender Inequalities Figure 5. Daily time use, 14–15-year-olds, Ethiopia (for those engaged in each activity) 7 Boys 6 Girls 5 Average hours 4 3 2 1 0 Caring for family members Domestic chores Farming Paid work At school Studying at home The chart shows some clear differences, with girls typically spending longer caring for others and on domestic tasks and boys spending more time on unpaid work for family farms or businesses: “Male children do not collect firewood. Only female children are involved in the collection of firewood … Boys do not do daily [household] chores. That is mainly the activities of females … The male children keep the cattle. I do not like to send my daughter to keep cattle. She helps me in the home.” (Mother, rural Ethiopia) While Figure 5 and the quotation from the caregiver above illustrate that the tasks undertaken are gendered, the amount of time spent on paid and unpaid work is similar for boys and girls, in Ethiopia. Boys and girls spend a similar amount of time in school, which is the highest amount for any activity, but girls have less time for studying – a factor which may impede their progress at school. A higher percentage of girls in both cohorts strongly agree with the statement ‘Other people in my family make all the decisions about how I spend my time’ in both Ethiopia and Peru. This difference is compounded by poverty, with the largest gender gap occurring in the poorest quintile (by household consumption); for example, in Peru 62 per cent of girls from the poorest quintile strongly agree with the statement and 50 per cent of boys do. Time use data from India tell a different story, with the burden of paid and unpaid work falling disproportionately on girls, who spend nearly an hour and a half more working than boys. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 17 Ramya’s experience of work Ramya is 15 years old and lives in rural Andhra Pradesh. Two of her elder sisters were married the previous year and the family needs to repay loans taken out for their dowries. Ramya works in the family’s cotton and tobacco fields as well as performing household chores. She takes pride in helping around the home: “It’s our home. If done [sweeping] it looks good, clean. It’s our home, hence it should be clean and tidy, and it is our job and should be done by us only. That’s why I like to do it. Everybody at home has to take one responsibility.” She dislikes the long hours spent in the fields, from 7am till 7pm, and the impact that this has on her schooling: “We are not regular at school. We have to obey our parents and go to the field. If we are not regular teachers scold us.” Ramya also describes the differences between herself and her younger brother: “He doesn’t go to the fields; sometimes he comes with us during the holidays but doesn’t do any work. He just comes and walks around the fields, nothing much. But at his age I used to go to the field and do work. … He is the youngest of us all – the only son after four girls. He is pampered a lot as he is the only son … When the work is hard I compare that he is not going but I have to go, but I don’t say anything. I like him as a small brother.” Children’s time use and how this shapes and is shaped by their trajectories is an underresearched area (Jones et al. 2010: 39). Analysis of Young Lives data supports some general patterns which have been observed already, such as the gendered nature of children’s work, that children spend more time on paid and unpaid work as they get older, and that children in rural areas do more paid and unpaid work (Bourdillon et al. 2010; Ritchie et al. 2004). However, the Young Lives data also add more nuance to the picture. For example, it is not necessarily the poorest children who are working, as families with more assets and land need labour. For example, Ramya’s household is in the fifth (highest) quintile of the household consumption level distribution in Young Lives sample and own land. This might explain the enrolment figures for the Older Cohort in Andhra Pradesh, which show that more girls from households below rather than above the relative poverty line are enrolled in school. 4.2 Age, location, household composition and shocks all affect children’s time use As Figure 6 illustrates, gender is not the only factor shaping children’s time use. Trends across the study countries show that children living in rural as opposed to urban areas spend more time spent on household work, caring responsibilities, and unpaid and paid work. The reverse is the case for time spent in school and studying. The difference in time spent in school and studying is larger between children in urban and rural environments than between boys and girls. The same is the case for paid work. As with Figure 5, the graph shows averages for children engaged in each activity, not all children in the cohort. www.younglives.org.uk/what-we-do/our-policy-work Page 18 Poverty and Gender Inequalities Figure 6. Daily time use, 14–15-year-olds, Andhra Pradesh (for those engaged in each activity) 12.00 Household Chores 10.00 8.00 6.00 4.00 2.00 0.00 Tr ib es es M al e Ru ra l Po or ba n No npo or Fe m al es as s Ca st Ur as t Ot he rC es e Paid Work School and Study Sc he du le d Sc he du le d Other factors which influence children’s time use include the age of the child, sibling order, the situation of other family members and shocks.6 Young Lives data show that Older Cohort children tend to spend more time than Younger Cohort children on paid work and household chores, and less time in school and studying. Gender differences are also less marked at younger ages, but become more pronounced after girls reach menarche:7 “In the past she herded cattle but since she matured [menarche] she has not herded cattle.” (Caregiver, rural Ethiopia). This is linked with caregivers’ fears for their daughters’ reputations and in turn the reputation of the household, as discussed in the previous section. Changes for girls in adolescence Kareena is 12 and from a Muslim community in Hyderabad, Andhra Pradesh. She describes the changes in her life which followed menarche: “When I was small I used to go anywhere but now it is restricted. Mother gave me restrictions ...: ‘Take care of your younger siblings, and do not go outside – you have to stay in the house only … you have to wear a burkha when you go outside. You should not talk to anybody, now you are a grown-up child. You should not play outside the house.’” Kareena’s mother explains why she will not allow her outside: “The locality is not good. Not only that, boys will make comments about her.” Household composition, birth order and sibling composition shape the allocation of household tasks. In Ethiopia oldest girls typically have a heavier burden of tasks than brothers or younger sisters (Heissler and Porter 2010). Shocks and adverse events also impact on children’s time use, and the increased burden of work may fall disproportionately on children, particularly girls (World Bank 2011: 33). Analysis of Round 2 data showed that the time children work in Andhra Pradesh increased by two hours on average if the household suffered loss of income. Girls living in rural areas were most affected in time use terms (Kruitikova 2009). The story of Latha, recounted earlier, is an illustration of this. 6 Shocks include economic shocks (e.g. increase in input prices, decrease in output prices, death of livestock, loss of income and loss of land), environmental shocks (e.g. drought, flooding, crop disease and pests, and crop failure) and family illness and death. 7 Menarche is the first occurrence of menstruation. www.younglives.org.uk/what-we-do/our-policy-work Ba ck wa rd Cl Young Lives Policy Paper 3: September 2011 Page 19 However, changes to the household, such as shocks, or household composition, can also result in children having to perform untypical tasks, as illustrated by the following two stories. Gendered roles in Ethiopia Seifu is one of five siblings living in an urban area in Ethiopia. He has two older sisters, one brother and one younger sister. While the older girls do most of the household chores Seifu looks after his little sister. His mother describes how he likes caring for his sister and carries her around. Tufa lives in rural Ethiopia and is 12 years old. He lives with his parents and five siblings. Tufa used to go to school but he left two years ago: “Some years ago, my parents stopped me from joining school and said that I must herd cattle; the other children were allowed to learn but I was not allowed to. There were no other children who could keep cattle except me at home; the rest of my brothers and sisters were allowed to go [to school]. I asked my parents to allow me to be registered but they refused to send me to school.” Unlike Seifu, Tufa dislikes caring for his younger siblings. His mother reports: “He complains that he is the only one who carries and looks after the babies. He says, ‘Why is it only me who should care for the baby? Do you think that I am a girl?’ He says, ‘You should recognise I am a boy.’ He says, ‘Let the girls carry the children.’” This illustrates the more complex nature of intra-household dynamics and allocation of tasks, where gender intersects with many other factors. 4.3 Reproduction of gendered roles through children’s work The gendered nature of household tasks suggests that time use is a way in which gendered roles are reproduced. Despite some examples of children performing untypical tasks, caregivers reported boys refusing to carry out tasks which they believed were “the work of women”. For example, a mother in Andhra Pradesh stated that her son was happy to harvest groundnuts but “if asked to sweep” he would say “Will the work of women be done by boys?” Similarly tensions between mothers and daughters are created when girls challenge gender norms. Conflicts between aspirations and expectations Santhi is from one of the Scheduled Tribes living in Andhra Pradesh. She has a strong ambition to become a doctor: “Since my childhood, I had the desire to become a doctor. I can help all if I become a doctor. Doctors treat some people differently. If people get an illness doctors should treat them well, help them all equally. That is my wish.” Santhi spends a lot of time studying at home in the evenings and prefers to help her father with his teaching preparation rather than do household chores. “Sometimes I do help my mother. If I feel like helping I will help her. I don’t do it every day but I help my father. He is a teacher, so I help him in preparing his teaching material. I enjoy doing that work. I don’t like household work. My sister helps my mother – she does all that work, I don’t.” This causes conflict with her mother who feels that Santhi ‘does not bother about others’ and is neglecting her responsibilities to the family. She compares Santhi unfavourably to her other two children: “[The] younger daughter shares everything [chores] with her brother. Those two are alike. Even if she does not know how to do it she will come forward to do it. This girl [Santhi] evades work. She is a work thief.” www.younglives.org.uk/what-we-do/our-policy-work Page 20 Poverty and Gender Inequalities Conflicts between aspirations and expectations continued Santhi’s mother also expresses her frustration with her daughter’s refusal to conform to social norms in her dress: “If I ask her to wear bindi [forehead ornamental decoration] because she is a mature girl, she replies, ‘What happens if I don’t wear bindi?’ … When I bought bangles and bindi, she used to wear them neatly. Then slowly she stopped. She won’t wear them … she won’t think ... ‘I am a girl, I should dress up well, wear bindi and go to school.’” This has longer-term implications as different social expectations for boys and girls are formed at an early age. The roles of men and women Yaswanth is 12 years old and lives in rural Andhra Pradesh. He expresses his views on the respective roles of men and women. Interviewer: After your marriage will you send your wife to work? Yaswanth: No, I want her to be at home. She shouldn’t work. Interviewer: Why? Yaswanth: She has to cook at home. Because I see my mother – is she not at home? It is enough if she will be at home. It is enough if she cooks. 4.4 Intra-household decision-making: poverty exacerbates differences Despite children’s different tasks within the home, many caregivers felt that they treated their children equally: “My children are all the same to me. I have never made a difference among them” (caregiver, rural Ethiopia). Some expressed preference for their sons as they would look after them in old age, whereas other caregivers favoured their daughters because of the help they provided around the home. As one caregiver in rural Ethiopia put it: “I give more attention to her than the rest of our children because the boys can walk everywhere and they can enjoy everywhere, but she is always at home helping her family so we love her very much.” Despite the positive attitude to girls’ education discussed earlier, because of limited resources parents felt forced to choose between sons and daughters in educational expenditure. Rather than discriminating per se, parents based their decisions on the current realities of the labour market, as well as sociocultural norms (Jones et al. 2010: 48; Kabeer 2000). Gender differences in education decisions In India the mother of a boy in the Younger Cohort said that educating her son was more important as ‘boys need to have a job to settle well in life’ whereas minimal education is sufficient for girls. This also affects decisions over whether to send children to private school, as is illustrated by the following interview with the caregiver of a child in the Younger Cohort in India. Interviewer: Which school do you plan to send him to? Mother: Private school at Dharur, or a better school. Interviewer: Did you not just say that it was expensive? Mother: Yes, but we have to send him somehow. Interviewer: Why not Swapna then? Mother: She will not study much anyway, maybe up to class 10 in this village. Once she is married she will go away. This school is OK for her. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 21 Figure 7 illustrates a bias towards boys in education-related expenditure in Andhra Pradesh. It shows expenditure for all children in households in the Older Cohort, not just the child included in the Young Lives sample. Expenditure is separated by the children’s ages to create a picture of spending by age. As far as school expenditure in the other countries is concerned, we do not find a significant gender-based pattern. Figure 7. Mean expenditure on school fees and extra tuition, Andhra Pradesh, by gender and age of children (rupees) 10000 Boys Girls 8000 Expenditure 6000 4000 2000 0 5 10 Age of child Note: Covers all in children aged 5–17 in households of Young Lives Older Cohort children. 15 20 The difference in educational expenditure in Andhra Pradesh may be exacerbated by the fast-growing private sector, particularly low-fee unlicensed schools. In the first round of survey data collection (2002) 11 per cent of boys and 9 per cent of girls aged 8 in rural areas, were receiving private education. In 2009 39 per cent of boys and 23 per cent of girls in the Younger Cohort, aged 8, were in a private school. This illustrates not only the growth of private education, especially in rural areas, but that the gender gap is widening. Given that the private education sector (which offers English tuition) is highly regarded, this may mean that boys are able to obtain better-paid jobs when older. Although it is not clear whether the quality of education is higher in the private sector, parents believe this to be the case and feel compelled to invest in children where possible: “It is more [the school fees and related expenses] but we have to cut down our spending and educate the children … it is like capital, and compulsory … It is the only thing that we can give to them” (mother, rural Andhra Pradesh). This puts a large strain on household finances, with parents reporting taking out loans to pay fees. These debt traps will inevitably impact on equality and in turn on poverty reduction (UNESCO 2010). www.younglives.org.uk/what-we-do/our-policy-work Page 22 Poverty and Gender Inequalities Key messages ●● Across Young Lives countries, time use is gendered as girls spend more time caring for others and performing household chores while boys carry out more unpaid work on family farms and in family businesses. Gender differences are less marked at younger ages and become more pronounced after girls reach menarche. Young Lives data show interlinkages between gender dynamics between men and women, and those between girls and boys. Care must be taken not to project women’s time poverty (having to work in the home and to earn a livelihood) onto girls. In Young Lives data girls and boys spend a similar amount of time on paid and unpaid work, in all countries except Andhra Pradesh. Projection of time poverty does not take account of processes of social change between generations and differences due to age. There are however, longer-term implications, with time use a way in which gendered roles within the household are reproduced and intergenerationally transmitted. Poverty, geographical location and shocks can put a disproportionate burden on children’s time. In some cases this falls on girls, in other cases it may lead to boys performing untypical tasks, with household composition, birth order and sibling composition all shaping the allocation of work. Gender-sensitive social protection schemes can help buffer households against shocks, as well as providing employment opportunities for women. It is important that childcare is a component of such schemes in order not to increase the time spent by children, especially girls, in caring for siblings in the absence of their mothers. Poverty can create or exacerbate intra-household decision-making, which may disadvantage girls, as seen with educational expenditure in Andhra Pradesh. While the end result is discrimination, the frequent starting point for parental decision-making is the realities of the labour market and sociocultural norms. Policies addressing intra-household dynamics and disparities in time use need to consider how these are shaped by the intersection of structural inequalities, in terms of poverty and poor access to services, and socio-cultural norms. Improvements in the infrastructure of services such as water and electricity reduce the time needed for household chores. ●● ●● ●● ●● 5. Subjective well-being Young Lives is collecting data on children’s subjective well-being to understand how children experience poverty. We examined a range of indicators and this section explores the different ways in which poverty impacts on children’s perceptions of themselves and others and looks at whether there are differences between boys and girls. Care must be taken in interpreting these results as there may be differences in reporting between boys and girls that are due to gendered expectations of well-being and gender differences in what is acceptable to report. The recurring theme across the indicators is that poverty has the largest impact on children’s subjective well-being but that poverty can be compounded by geographical location (urban or rural environment) ethnicity or caste, or gender. However, girls in the Older Cohort report significantly lower levels of trust in those around them in Vietnam, Ethiopia and Peru, compared with boys (Dercon and Singh forthcoming). 5.1 Close association between poverty and children’s well-being Young Lives uses a ladder exercise to collect data on children’s perceptions of their own well-being. Children are asked to position themselves on a ladder where the 9th step represents the best possible life for them and the first step the worst. Figure 8 groups together children who positioned themselves on steps 1 to 3 as children who consider that they have a bad life and children who placed themselves on steps 7 to 9 as children who consider that they have a good life. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 23 Figure 8. Subjective well-being, Vietnam (both cohorts) 50 45 40 35 Percentage 30 25 20 15 10 5 0 All Male Female Urban Rural Non-poor Poor Minority group Majority group Good life Bad Life The chart shows little difference between boys and girls but stark divergences between children living above and below the relative poverty line and between majority and minority ethnic groups. Poor children are four times more likely to report experiencing a bad life than non-poor children. To a lesser extent there is an urban–rural difference, with children in rural areas slightly more likely to report a bad life than those living in urban areas. This suggests that poverty has a greater impact on children’s subjective well-being than gender. A similar pattern occurs in Andhra Pradesh (Figures 9 and 10), with a higher percentage of poor children and children from the Scheduled Castes reporting a bad life. Figure 9. Subjective well-being, Andhra Pradesh (Younger Cohort) 40 Good life 35 30 Percentage 25 20 15 10 5 0 Bad Life es es e e n al Po o or ss e s No d le ck wa r du du Sc he Sc he www.younglives.org.uk/what-we-do/our-policy-work Ba Ot he le d rC as te al al ba Ru r po st Fe m Ca Tr ib M Ur d Cl a n- s r Page 24 Poverty and Gender Inequalities Figure 10. Subjective well-being, Andhra Pradesh (Older Cohort) 40 Good life 35 30 Percentage 25 20 15 10 5 0 Bad Life es as se s e Ru ra l Po o or e n s Ur ba npo Fe m Ca Tr ib No d le ck wa rd du du Sc he Sc he Figures 9 and 10 display the ladder position of the Younger Cohort (Figure 9) and Older Cohort (Figure 10). Older children tend to position themselves in the middle of the ladder and higher percentages of younger children place themselves at either end. A greater percentage of poor children in the Older Cohort, however, place themselves at the bottom end of the ladder in comparison with the Younger Cohort. This may suggest that, with age, poverty becomes an increasingly negative factor influencing children’s subjective well-being, or that children become increasingly aware of poverty and inequalities. In Andhra Pradesh, as with Vietnam, there is little difference between boys and girls, with the exception of girls in the Older Cohort, where a higher percentage consider that they have a good life, than do the cohort’s boys. 5.2 Intersecting inequalities affect subjective well-being Children were also asked to agree or disagree with the statement ‘I am proud of my clothes’. In both Ethiopia and Peru there was little difference between boys and girls but there was a gap between urban and rural areas, with children in rural areas less likely to agree with the statement than their urban counterparts. Responses in both countries were also linked with household consumption level, with the percentage of children agreeing with the statement increasing with each quintile of household consumption. Poverty also affects the way in which children feel treated by others. We asked children to agree or disagree with the sentence: ‘When I am at the shops/market I am usually treated by others with fairness and respect.’ In Ethiopia 75 per cent of boys in the Older Cohort agreed with the statement compared with 70 per cent of girls; in urban areas the gap was narrower and the percentage of children agreeing higher (79 per cent of boys and 76 per cent of girls) while in rural areas the gap was wider (73 per cent of boys and 67 per cent of girls). This suggests that poverty, the rural environment and gender may intersect to create feelings of inferiority. The impact of poverty and stigma on children’s subjective well-being is illustrated by the following two stories drawn from the qualitative data. Both boys and girls report a sense of feeling stigmatised or marginalised but here relate it to their poverty and ethnic or caste status rather than their gender. www.younglives.org.uk/what-we-do/our-policy-work Ba Ot he le rC d Cl as te M st e al al s r Young Lives Policy Paper 3: September 2011 Page 25 Dual discrimination in Peru Eva is 13 years old and in her second year of secondary education. She lives in a Quechua rural village in Peru with her parents and siblings and commutes every morning to attend school in the district capital. It takes about 30 minutes by car. Sometimes, on her way back, she has to walk, and the return trip may take about three hours if there is no public transport available. Eva reported not having any friends at school. During school breaks she plays with a cousin. The reason for this, she says, is that she is marginalised by her schoolmates because she comes from a rural village. Her classmates used to call her names and call her indigenous. She says she doesn’t care, she just wants to study and go [get] ahead, but she also reported mistrusting friends because they may not be loyal. Other girls in Eva’s village consider her too arrogant. Even her mother said she misbehaves with local girls, showing off and trying to act superior, and refuses to speak Quechua at home. Eva doesn’t use the traditional shawl local women and girls use in the village any more, but wears modern sports clothes, like the town’s young people. Although Eva is aware on the one hand of the discrimination against her for being rural and indigenous, on the other hand she also discriminates against the local girls in her home village, and internalises the discourse of inferiority associated with rurality and ethnicity by refusing to wear traditional clothes and to speak her indigenous language. Thus, although resisting in one way such a discourse of inferiority through pursuing education and “going ahead”, Eva also reproduces it in her relations with other girls in her village who have remained in the local school and are more attached to their indigenous traditions. Taken from Ames and Rojas (2010) How Subbaiah feels about his caste Subbaiah lives in rural Andhra Pradesh. He is from the Backward Caste which makes him feel inferior to other children in the community: Interviewer: Compared to other children how do you feel? Subbaiah: Inferior because of my caste. Interviewer: Only by caste or any other aspects? Subbaiah: Fine, except caste. Subbaiah says that other children make comments about his caste status and his mother explains that there are many people from higher castes in the community so she does not send her son to visit the neighbours as: “They may say something and the child may feel bad. In order to avoid all this I advise my children not to go to the neighbour’s house.” Although the data show children in urban areas reporting higher levels of well-being, there are some specific fears reported by children, and particularly girls, living in urban areas: “I prefer to go to school in the morning, because in the afternoons it is more dangerous— when I come back it is darker. I mean it is dangerous – in the streets there is always danger – but in the morning it is not so dangerous. It is less likely that something happens to you [in the morning], but in the streets at night, there are more adult people, drunken people. I don’t know, it is more dangerous.” (Susan, Older Cohort, urban Lima) We asked children to agree or disagree with the statement: ‘I feel safe when I go out of the house on my own.’ In Ethiopia girls in the Older Cohort are half as likely to strongly agree with the statement compared with boys (16 per cent as opposed to 31 per cent). This difference is greater in urban environments. While boys in urban areas are slightly more likely to strongly agree with the statement than boys in rural areas (34 per cent compared to 29 per cent), the trend is reversed for girls, with only 13 per cent of girls in urban areas strongly agreeing. There is a similar picture in Peru where 54 per cent of Older Cohort boys agree with the statement compared to 36 per cent of girls. Feelings of safety are also linked with household consumption levels in Peru. Children in families with higher consumption levels are more likely to say they do not feel safe even though they may be less at risk than those from poorer www.younglives.org.uk/what-we-do/our-policy-work Page 26 Poverty and Gender Inequalities households. It should be born in mind that there may be cultural factors at play in that it may be less acceptable for girls to leave the house on their own, particularly in Andhra Pradesh and Ethiopia, and which may therefore influence children’s responses. Dercon and Singh (forthcoming) used regression analysis controlling for a whole series of socio-economic factors to examine gender bias within 13 indicators, covering nutrition, education achievement and aspirations, subjective well-being and psychosocial competencies such as agency, trust and pride. In line with the findings in this paper, Dercon and Singh found ‘striking heterogeneity in bias and its direction across countries, stages in a child’s life cycle and the indicator involved.’ Some of these results are attached in Appendix 1. Regarding the psychosocial data, across Ethiopia, Peru and Vietnam girls at age 15 report significantly lower trust in members of their immediate society than boys. In Andhra Pradesh and Ethiopia, boys at the same age have a greater sense of agency, that is, the ability to shape the direction of his or her life. This may reflect the fears expressed by girls and caregivers of abduction and rape following menarche: “[When] girls start to have their first menstrual period there is some behavioural change, like fear, hiding, worry, confusion, feeling uncomfortable because parents do not talk openly about this matter. This is also an important change for the parents because at this time their worry and concern about their girls increases.” (Female community member, rural site, Ethiopia) These findings illustrate how poverty and inequality affect outcomes for children not only in objective terms, such as length of schooling received, but also subjective well-being. Poverty and inequality may be experienced differently by boys and girls. Key messages ●● Young Lives data show a close association between poverty and children’s subjective well-being, with poor children much less likely to report having a ‘good life’. There are small differences between boys and girls but stark differences between children living above and below the relative poverty lines and between majority ethnic groups and minority groups or marginalised caste groups. Poverty and inequalities can be compounded by different challenges faced by children living in urban and rural environments, a sense of feeling stigmatised or marginalised and gender-specific factors such as physical safety. Children appear to become increasingly aware of poverty and inequalities with age. Poverty and inequality may be experienced differently by boys and girls, with girls reporting significantly lower levels of trust in Ethiopia, Peru and Vietnam than boys. As poverty underpins the sense of feeling marginalised by different groups of children, tackling the root cause (poverty) would be a better place for intervention rather than the symptom (poorer subjective well-being). ●● ●● www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 27 6. Conclusions and policy discussion The close interrelationship between gender inequalities and poverty, with either a potential cause or consequence of the other, has resulted in ‘gender mainstreaming’ becoming central to poverty reduction strategies. Progress has been mixed, with advances in some regions of the world and in some sectors offset by stagnation or negative trends in others (World Bank 2011). Recognition of the importance of early intervention, particularly in education and health, for shaping future trajectories has meant increasing focus being directed towards inequalities in access to services and in parental investment between boys and girls. These are important in order to break the intergenerational transmission of poverty and inequalities. At the same time it is generally acknowledged that gender is one of a series of inequalities, including poverty, geographical location, ethnicity or caste status, which can impact upon children’s life chances (ibid.). This raises the question of whether gender differences are the best place to start when attempting to address unequal outcomes between children, or whether it is better to start with broader structural inequalities whilst retaining gender analysis as a central component (Jones and Chant 2009: 195; Knodel and Jones 1996). Analysis of Young Lives data has an important role to play in this debate, offering a more nuanced picture of gender dynamics than that which is often presented, and showing inequalities affecting both boys and girls at different ages through intra-household dynamics, sociocultural context and economic pressures. The patterning of gender inequalities in education and aspirations, time use and work, and subjective well-being, and the extent to which they exist, also varies between the four countries included in the Young Lives study. Andhra Pradesh is the exception, providing a more consistent pattern of gender differences biased against girls. Both these findings are reflective of the global picture, which shows different regional trends and much faster movement towards gender parity in primary school enrolment compared to other indicators in heath and access to better paid employment (World Bank 2011). Building on Young Lives findings on the intersecting nature of inequalities, the following policy messages seek to address poverty and broader structural inequalities in order to improve life chances for poor girls, as well as poor boys. 6.1 Building on enrolment: from parity to quality Although girls’ enrolment rates tell a positive story, it is not clear that there have been the same increases in the quality of education received by girls or boys, as is illustrated by Young Lives test scores (see Figures 1 and 2). Learning outcomes can also be influenced by challenges faced in the school environment such as lack of gender-segregated toilets or forms of corporal punishment, as well as by differing attitudes and expectations for boys and girls, including those of teachers. It remains to be seen whether girls are able to translate school attendance and attainment into better-paid jobs, higher-status position in society or improved bargaining power within the household, particularly given the persistence of gender differences in time use (Jones et al. 2010: 2). Building on the success of increased enrolment suggests that equal attention should now be given to the quality of education received as well as the learning environment. This would benefit girls as well as boys. In order for children and parents’ high aspirations to be met, it is important that school equips children with the skills needed to access the labour market, vocational training and higher education. www.younglives.org.uk/what-we-do/our-policy-work Page 28 Poverty and Gender Inequalities 6.2 Socio-economic change and addressing new sources of inequalities Rates of social change are also being affected by economic growth leading to different patterning and types of gender inequalities in urban and rural environments. Despite the ongoing economic crisis, all the countries in the Young Lives study are continuing to grow in terms of GDP and yet poverty is persisting. While absolute poverty has declined, there is a mixed picture on relative poverty or inequality (Dornan 2010). This raises questions over how inequalities may be narrowed or widened over time and how their patterning and type may change. Economic development alone will not solve inequalities, and factors such as the private education sector may work in the opposite direction, as illustrated by the growing gender inequalities in education in Andhra Pradesh. Familial perceptions of risk associated with social change tend to have a greater influence on girls’ trajectories. Understanding the sociocultural factors affecting the uptake of schooling is essential in ensuring that service provision meets the needs of poorer children, such as ensuring that schools are close to communities, thereby reducing the need for girls to travel long distances, and making them more flexible, in order to meet the needs of both girls and boys working within or for the household (Levine et al. 2008: 6, 13). 6.3 Intersecting inequalities and improving life chances Disaggregation of data, including by gender, is the first stage in understanding how poverty impacts upon children differently (Levine et al. 2008). This is essential to inform policies to ensure that services are reaching the poorest children. Disadvantages based on urban or rural location, ethnicity or caste or poverty levels are larger and more consistent than differences according to gender. These factors however may compound gender inequalities (UNESCO 2010: 23). This emphasises the need not only for gender-disaggregated data, but for other factors such as location, ethnicity and household consumption levels to be considered alongside gender. Our analysis also suggests that in seeking to improve gender equality, policy interventions, such as improving school quality or social protection programmes, should target broader structural inequalities, between urban and rural environments and between households with different levels of consumption, especially the poorest households. www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 29 References Ames, P. and V. Rojas (2010) Change and Opportunity: The Transition from Primary to Secondary School in Rural and Urban Peru, Working Paper 63, Oxford: Young Lives Appadurai, A. (2004) ‘The Capacity to Aspire: Culture and the Terms of Recognition’ in V. Rao and M. Walton (eds.) Culture and Public Action, Stanford University Press, Palo Alto, California, pp 59-84. Aslam, M., G. Kingdon and M. Söderbom (2008) ‘Is Female Education a Pathway to Gender Equality in the Labor Market? Some Evidence from Pakistan’ in M. Tembon and L. Fort (eds.) Girls’ Education in the 21st Century: Gender Equality, Empowerment and Economic Growth, Washington DC: World Bank: 67–92 Bourdillion, M., D. Levison, W. Myers and B. White (2010) Rights and Wrongs of Children’s Work, New Brunswick NJ: Rutgers University Press Boyden, J. and G. Crivello (forthcoming) Political Economy, Perception and Social Change as Mediators of Childhood Risk in Andhra Pradesh, Working Paper, Oxford: Young Lives Buvinic, M., J. C. Guzmán and C.B. Lloyd (2007) ‘Gender Shapes Adolescence’, Development Outreach 9.2: 12–15 Chant, S. (ed.) (2011) International Handbook of Gender and Poverty: Concepts, Research, Policy, Cheltenham: Edward Elgar Publishing Cueto, S., J. Escobal, M. Penny and P. Ames (2011) Tracking Disparities: Who Gets Left Behind? Initial Findings from Peru, Young Lives Round 3 Survey Report, Oxford: Young Lives Dercon, S. and A. Singh (forthcoming) ‘From Nutrition to Aspirations and Self-Efficacy: Gender Bias over Time among Children in Four Countries’ Dornan, P. (2010) Understanding the Impact of Crisis on Children in Developing Countries: Round 3 Preliminary Findings, Oxford: Young Lives Galab, S., S.V. Kumar, P.P. Reddy, R. Singh and U. Vennam (2011) The Impact of Growth on Childhood Poverty in Andhra Pradesh: Initial Findings from India, Young Lives Round 3 Survey Report, Oxford: Young Lives Grant, M.J. and J.R. Behrman (2010) Gender Gaps in Educational Attainment in Less Developed Countries, Population and Development Review 36.1: 71–89 Greene, M., L. Cardinal and E. Goldstein-Siegel (2009) Girls Speak: A New Voice in Global Development, Washington DC: International Center for Research on Women Heissler, K. and C. Porter (2010) Know Your Place: Ethiopian Children’s Contributions to the Household Economy, Working Paper 61, Oxford: Young Lives Jones, G. and S. Chant (2009) ‘Globalising Initiatives for Gender Equality and Poverty Reduction: Exploring “Failure” with Reference to Education and Work Among Urban Youth in The Gambia and Ghana’, Geoforum 40: 184–96 Jones, N., C. Harper and C. Watson (2010) Stemming Girls’ Chronic Poverty: Catalysing Development Change by Building Just Social Institutions, Manchester: Chronic Poverty Research Centre Kabeer, N. (2000) ‘Inter-generational Contracts, Demographic Transitions and the ‘Quantity–Quality’ Tradeoff: Parents, Children and Investing in the Future’, Journal of International Development 12.4: 463–82 Knodel, J. and G.W. Jones (1996) ‘Post-Cairo Population Policy: Does Promoting Girls’ Schooling Miss the Mark?’, Population and Development Review 22.4: 683–702 Krutikova, S. (2009) Determinants of Child Labour: The Case of Andhra Pradesh, Working Paper 48, Oxford: Young Lives Le Thuc, Duc, Nguyen Thang, Nguyen Van Tien, Mai Thuy Hang, Vu Thi Thu Thuy (2011) How Do Children Fare in the New Millennium: Initial Findings from Vietnam, Young Lives Round 3 Survey Report, Oxford: Young Lives www.younglives.org.uk/what-we-do/our-policy-work Page 30 Poverty and Gender Inequalities Levine, R., C. Lloyd, M. Greene and C. Grown (2008) Girls Count: A Global Investment and Action Agenda, Washington DC: Center for Global Development Lloyd, C. with J. Young (2009) New Lessons: The Power of Educating Adolescent Girls, New York: Population Council Morrow, V. and U. Vennam (2010) ‘Combining Work and School: The Dynamics of Girls’ Involvement in Agricultural Work in Andhra Pradesh, India’, Children and Society 24.4: 304–14 Ritchie, A., C.B. Lloyd and M. Grant (2004) Gender Differences in Time Use Among Adolescents in Developing Countries: Implications of Rising School Enrollment Rates, Working Paper 193, New York: Population Council Rojas, V. (2011) “Grades are Sacred… We’d Rather be Beaten with a Stick”: Students’ Perceptions of Discipline and Authority in a Public High School in Peru, Young Lives Working Paper 70, Oxford: Young Lives Temin. M. and R. Levine (2009) Start with a Girl: A New Agenda for Global Health, Washington DC: Center for Global Development UNESCO (2010) Reaching the Marginalized: EFA Global Monitoring Report 2010, Paris: UNESCO UNICEF (2009) The State of the World’s Children 2010: Celebrating 20 Years of the Convention on the Rights of the Child, New York: UNICEF UNICEF (2010) The State of the World’s Children 2011: Adolescence – An Age of Opportunity, New York: UNICEF Woldehanna, T., R. Gudisa, Y. Tafere and A. Pankhurst (2011) Understanding Changes in the Lives of Poor Children: Initial Findings from Ethiopia, Young Lives Round 3 Survey Report, Oxford: Young Lives World Bank (2006) World Development Report 2007: Development and the Next Generation, Washington DC: World Bank World Bank (2011) World Development Report 2012: Gender Equality and Development, outline report, https://www-wds.worldbank.org/external/default/WDSContent Server/IW3P/IB/2010/11/03/000334955_2 0101103062028/Rendered/PDF/576270WDR0SecM1e0only1910BOX353773B.pdf (accessed 25 March 2011) www.younglives.org.uk/what-we-do/our-policy-work Young Lives Policy Paper 3: September 2011 Page 31 Appendix 1 The table is taken from Dercon and Singh (forthcoming) and is the results of regression analysis which sought to analyse determinants of various indicators of child development (the first column of the table). Each regression model contained a series of socio-economic and demographic controls, including the gender of the child. The table documents where statistically significant differences in these outcomes were associated with gender across the cohorts and countries (together with the direction of this difference). ** means significant at least at 95% confidence interval, * means significant at least at 90% , + means significant between 80 and 90%. Ethiopia YC R3 (8 yrs) PPVT raw score Math score (arithmetic) raw score Enrolment (dummy) Child’s desired education (years) Parent’s desired education (years) Child Ladder of Life Trust (standardized) Pride (standardized) Inclusion (standardized) Agency (standardized) HFA (z-score) Female ** Female * NA Female ** Female * Male * Male ** Female ** (Male) + Male ** Male ** NA Male ** Female ** Male ** R3 = Round 3 India YC R3 (8 yrs) Male ** OC R2 OC R3 (12 yrs) (15 yrs) Male ** Male * Male ** Male ** Male ** NA Male ** Male * Male ** Male ** Male ** NA Female ** NA Female ** YC R3 (8 yrs) Male ** Male ** Peru OC R2 OC R3 (12 yrs) (15 yrs) (Male) + YC R3 (8 yrs) Vietnam OC R2 OC R3 (12 yrs) (15 yrs) OC R2 OC R3 (12 yrs) (15 yrs) Male ** Male * Male ** (Female) + Male ** (Male) + NA Female ** Female ** NA NA Female ** Male*** Female ** Male * Female ** Male *** Female ** Female ** Female ** NA Female ** Male ** (Male) + Female ** NA Female ** Female ** Female ** NA Male ** Female ** Female * NA Female ** (Female) + (Female) + Female ** (Female) + OC = Older Cohort YC = Younger Cohort R2 = Round 2 www.younglives.org.uk/what-we-do/our-policy-work © Young Lives 2011