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Child Labour & Social Programming | Focus on Educational Strategies



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Child Labour & Social Programming | Focus on Educational Strategies

  1. 1. CHILD LABOUR & SOCIAL PROGRAMMING FOCUS ON EDUCATIONAL STRATEGIES Valeria Groppo, Guest Lecture on Child Labour, King’s College London 19 February 2021
  2. 2. • International Conventions • The global context • Social programming and child labour • Zooming into educational strategies • Demand-side • Conditional cash transfers • Tanzania PSSN, child work & schooling • School feeding • Supply-side • School infrastructure • Demand- and supply-side mix • Multi-component interventions addressing child labour • Summary of key take-aways • COVID-19 & child labour • 2021 International Year for the Elimination of Child Labour Outline
  4. 4. International Conventions International labour standards define child labour by its consequences: it encompasses work that is: • mentally, physically, socially or morally dangerous and harmful to children, and/or • interferes with their schooling. Two main forms: • Work below the minimum age • Worst forms of child labour DEFINITION Source: ILO (2008). ILO • Convention 138 on minimum age of employment • Generally no lower than the age at end of compulsory education • ‘Light work’ may be permitted • Convention 182 on worst forms of child labour UN • Convention on the Right of the Child • Article 32 (child’s right to be protected from economic exploitation and from performing any work that is likely to be hazardous or to interfere with education or health) KEY INTERNATIONAL CONVENTIONS
  5. 5. A closer look at worst forms of child labour a) All forms of slavery or practices similar to slavery, such as the sale and trafficking of children, debt bondage and serfdom and forced or compulsory labour, including forced or compulsory recruitment of children for use in armed conflict; b) the use, procuring or offering of a child for prostitution, for the production of pornography or for pornographic performances; c) the use, procuring or offering of a child for illicit activities, in particular for the production and trafficking of drugs as defined in the relevant international treaties; UNCONDITIONAL WORST FORMS Source: ILO (2008). d) work which, by its nature or the circumstances in which it is carried out, is likely to harm the health, safety or morals of children • work which exposes children to physical, psychological or sexual abuse; • work underground, under water, at dangerous heights or in confined spaces; • work with dangerous machinery, equipment and tools, or which involves the manual handling or transport of heavy loads; • Exposure to hazardous substances, agents or processes, or to temperatures, noise levels, or vibrations damaging to their health; • work for long hours or during the night HAZARDOUS WORK
  6. 6. Child labour based on international labour standards Age group Children’s work Non-harmful work Worst Forms of Child Labour (WFCL) Hazardous work Unconditional WFCL Forms of work excluded under Convention 138 flexibility clauses Light work Excessively long hours in econ activities or chores Hazardous work, other than long hours Trafficked children, children in forced and bonded labour, […] prostitution and other illicit activities. Children at or above the general minimum working age Age 15-17 WFCL Children within the age range specified for light work Age 12-14 Children below minimum age specified for light work Age 5-11 Work below minimum age Source: adapted from ILO (2008).
  8. 8. Global child labour • Since 2000, child labour is on a declining trend • Still, 152 million children globally engage in child labour (1 in 10 children) • SDG 8.7 calls for elimination of child labour in all of its form by 2025 • ‘Business as usual’ (2012-16 rate) would leave still 121 million • Fastest progress (2008-12 rate) still not enough • Unconditional worst forms of child labour not captured • COVID-19 Source: ILO (2017). Global Estimates of Child Labour. The figures refer to children aged 5 to 17 years. 16 14.2 13.6 10.6 9.6 0 2 4 6 8 10 12 14 16 18 0 50 100 150 200 250 300 2000 2004 2008 2012 2016 Million Prevalence (%) TRENDS Million Percentage
  9. 9. Geographical child labour distribution (2016) Source: ILO (2017). Global Estimates of Child Labour. The figures refer to children aged 5 to 17 years. ABSOLUTE NUMBERS 47% 41% 7% 4% 1% Africa Asia and the Pacific Americas Europe and Central Asia Arab States PREVALENCE 19.6 7.4 5.3 4.1 2.9 0 5 10 15 20 25 Africa Asia and the Pacific Americas Europe and Central Asia Arab States
  10. 10. • India and Bangladesh home to majority of child labourers in South Asia (Khan & Lion 2015) • Hazardous forms of child labour remain an issue in both countries, e.g. producing bricks, mining & collecting mica • Child labour concentrated in ‘hotspots’ (see example for India) Child labour in India & Bangladesh Source: V.V. Giri National Labour Institute and UNICEF (2015).
  11. 11. SOCIAL PROGRAMMING & CHILD LABOUR OVERVIEW (e.g. Dammert et al 2018, Idris et al, 2020)
  12. 12. Main public policies and programmes that may impact child labour POVERTY REDUCTION / EDUCATION OBJECTIVES CHILD LABOUR OBJECTIVE • Social protection • Cash or in-kind transfers • Public works programmes • Microcredit / microinsurance • Reducing demand-side barriers to education • Reducing school fees (Tang et al 2020) • Merit-based scholarships • Other (Gallego et al 2018, Mitra & Moene 2020) • Reducing supply-side barriers to education • Building schools, ECD facilities, WASH in schools • Pedagogy (e.g. Teaching at the Right Level’) • Skills / empowerment programmes (Edmonds et al 2020) • Regulations • Ban on child labour (Bharadwaj et al 2020) • Multi-component interventions (‘cash plus’) that combine: • Economic support, plus services (e.g. education, child protection) and/or awareness raising
  14. 14. Conditional cash transfers Features • Regular transfers targeting poor households • Amount generally varies with household size • Requirement: minimum level of school attendance Objectives • Reduce poverty and vulnerability • Improve schooling outcomes • Seldom child labour is cited (exception: Nepal, Edmonds & Shrestha 2014) Mechanisms • Cash benefits → income effect → ↑ schooling and ↓ need for child labour → ↑ household investment in productive assets → may ↑ demand for child labour/chores • Conditionalities → ↓ opportunity cost of schooling → ↑ schooling and ↓ need for child labour OVERVIEW & THEORETICAL FRAMEWORK
  15. 15. Conditional cash transfers Evidence • CCTs tend to reduce child work • Latin America: Mexico Progresa (Parker & Todd 2017), Nicaragua Red de Proteccion Social (Dammert 2009), Nicaragua Atencion a Crisis (Del Carpio et al, 2016) • Africa: Tanzania Productive Social Safety Net - PSSN (de Hoop et al, 2020) • South Asia: Nepal (Edmonds & Shrestha 2014, worst forms of child labour; Datt & Uhe, 2019) Gaps • Geography: limited evidence for Sub-Saharan Africa and South Asia (India, Bangladesh) • Type of economic activities • Child labour vs. child work; exposure to work-related hazards • Household chores • How impacts are moderated by contextual factors, e.g. social norms LITERATURE
  16. 16. Child labour impacts of Tanzania’s Productive Social Safety Net (PSSN) J. de Hoop, M. W. Gichane, V. Groppo, S. Simmons Zuilkowski, on behalf of the PSSN Youth Evaluation Team CONTEXT Tanzania, Handeni district, endline data collection, 2017. Nearly 30% of Tanzanian children engage in child labour (ILO 2016) Tanzania Social Action Fund (TASAF) • Introduced in 2000, progressively scaled up • Objectives: increase income and consumption, improve ability to cope with shocks, improve education • Components during study period: (1) cash transfer; (2) public works • Coverage: national, 15% population (6 million people) in 2016
  17. 17. 17 Tanzania’s PSSN programme
  18. 18. Child labour impacts of Tanzania’s Productive Social Safety Net (PSSN) - Continued MIXED METHODS Tanzania, Handeni district, endline data collection, 2017. • Quantitative: cluster RCT • Villages receiving PSSN • Control (delayed receipt of programme) • Qualitative • IDIs & FGDs with children/caregivers • Photovoice Tanzania, Handeni district, endline data collection, 2017
  19. 19. PSSN Evaluation timeline 2014-2015 Targeting & location selection • Eligibility: extreme poverty; ‘ability to work’. • Eight mainland PAAs, plus one in Zanzibar • 102 villages May- July 2015 Baseline Survey (quant) August 2015 Random assignment (lottery) • PSSN (61 villages) • Control (delayed treatment, 41 villages) September- October 2015 First cash transfer in PSSN villages April- June 2017 Endline Survey (quant) September -October 2017 Qualitative data collection 19
  20. 20. PSSN determined a change in child work type -0.006 -0.002 0.038** -0.005 -0.019** -0.04 -0.02 0 0.02 0.04 Any economic activities Farm work for the household (excl. livestock) Livestock herding for the household Household non-farm business Paid work outside the household N = 3,516 children aged 5-17 years *p <0.1, **p <0.05 20
  21. 21. PSSN impacts on child work, by gender Any economic activities Farm work for the household (excl. livestock) Livestock herding for the household Household non-farm business Paid work outside the household N = 3,516 children (1,728 female, 1,788 male) aged 5-17 years *p <0.1, **p <0.05 0.004 0.005 0.035* -0.002 -0.008 -0.016 -0.008 0.04** -0.007 -0.031*** -0.04 -0.02 0 0.02 0.04 0.06 Female Male 21
  22. 22. Qualitative insights on PSSN & child work “The PSSN programme has given children time to rest for some days without involvement in casual works. In the previous time, children were forced to work every day or every week so as to get their needs, but now as we are assured of providing them with school requirement so they may spend even a week without working in casual labours.” - Caregiver FGD participant “On one hand, I get more time now. If I want, I can spend more time because we have labourers who work in our farms, my grandfather use PSSN money to employ casuals [day labourers] to help us in farming. On the other hand, [PSSN] money has reduced my time to search for casual works because if I fail to get money, I can use [PSSN] money. I was spending one day per week for casual works before PSSN, but after PSSN I spend one day per month on casual works.” - Child FGD participant “PSSN has not changed what I have been doing before. I am still doing charcoal business, herding cattle and sometimes selling sisal poles. The activities have neither increased nor decreased because of PSSN.” - 15-year-old-boy 22
  23. 23. 0.009 -0.002 -0.032 -0.04 -0.02 0 0.02 0.04 Any hazard Ever been hurt or suffered from illnesses/in juries Number of days of main activities missed due to most serious illness/injury PSSN did not affect child hazards, health N = 3,516 children aged 5-17 years 23
  24. 24. PSSN summary of impacts • PSSN had beneficial effects on child work, with substitution effects stronger for male and older children • PSSN improved child education (results not shown) • Important to monitor unintended effects of programmes that expand household productive capacity • Important to use mixed methods • Complementary interventions could be considered to enhance education improvements • Information to caregivers on the importance of education and the risks related to child labour
  25. 25. School feeding Features • Lunches delivered at school OR take-home ratios • Conditional by definition Objectives • Reduce poverty and vulnerability • Improve schooling outcomes Mechanisms • School feeding → income effect & reduced opportunity cost of schooling → ↑ schooling and ↓ need for child labour OVERVIEW & THEORETICAL FRAMEWORK
  26. 26. School feeding Evidence • Bangladesh (Ravallion & Wodon 2000): Food-For-Education (take-home) reduced child participation in economic activities; impacts on child work, however, much weaker than schooling impacts • Burkina Faso (Kazianga et al 2012): take-home rations (reduced girls’ work) vs. school feeding (no impact) – not clear if same value, so no indication of relative effectiveness of programme type • Mali (Aurino et al 2019, conflict setting): school feeding decreased girls’ participation in farm work (less compatible with school participation) vs. general food distribution (increased boys’ work) Gaps • Geography: e.g. India Mid-Day, the largest school feeding programme in the world (Chakraborty & Rajshri 2019, learning impacts) LITERATURE
  28. 28. School infrastructure Features - Examples • School construction; improvement of WASH facilities in schools • Early Childhood Education facilities Objectives • Improve schooling outcomes • Improve ECD outcomes, maternal labour force participation Mechanisms • School construction → ↓ indirect schooling costs (transport) → ↑ schooling and ↓ need for child labour → ↓ transport time → may free up time to engage in work (school-going children) • WASH in schools may reduce the risk of child labour, especially for girls (through to improved menstrual hygiene and school attendance) • ECD → ↑ maternal labour force participation → ↓ need for child labour → safe spaces for children → ↓ exposure to child labour (e.g. mica mining) + ↑ stimulation OVERVIEW & THEORETICAL FRAMEWORK
  29. 29. School infrastructure Evidence • Mixed picture • Ghana (Vuri 2011) – lower distance to school decreases work, but increases household chores • Tanzania (Kondylis & Manacorda 2012) – no effect on child labour • Burkina Faso BRIGHT programme did not influence child participation in work outside the household (de Hoop & Rosati 2014, Kazianga et al 2013), but work increased for boys without female siblings who did not benefit of take-home rations (de Hoop & Rosati 2014) Gaps • Mechanisms that drive differences in impacts by gender need to be better understood LITERATURE
  31. 31. Multi-component interventions Features - Examples • Promoting Child Rights in Cotton Farming Areas of Pakistan (CRCF) • CCTs + Advocacy & awareness raising • School supply; vocational training • India National Child Labour Project (Mukhopadhaya et al 2012) • School enrolment in non-formal education (special schools run by NCLP), for later integration in the formal system • School meals in both types of schools • Conditional in-kind transfers & empowerment (Buchmann et al 2018) Objectives • Eliminate child labour • Improve education • Delay marriage OVERVIEW
  32. 32. Multi-component interventions Evidence • Mostly descriptive • India NCLP (Mukhopadhaya et al 2012) – promising findings, including high rates of lunch provision, adequate schooling availability; special consideration to the most vulnerable segments of society • Mostly on outcomes other than child labour (e.g. child marriage, Buchmann et al 2018) Gaps • Experimental or quasi-experimental studies (e.g. programme’s staggered expansion may allow to exploit spatial and temporal variation in child exposure to estimate impacts) • Qualitative studies assessing implementation challenges LITERATURE
  33. 33. Summary of the evidence on educational strategies & child labour EVIDENCE GAPS • Wider evidence base on conditional cash transfers • tend to reduce child labour, but • results are context-specific • School feeding appear a promising strategy, as building schools, WASH in schools • Limited evidence on multi-component interventions (‘cash plus’) interventions • Emerging evidence on skills development and child work / youth decent work • Geographical coverage • South Asia (India) • Analyses of impacts on child labour (as defined by international conventions) • Demand side • Reducing fees • Providing information • Supply side • Pedagogical approaches • Non-formal education • Teaching at the Right Level • Inclusive education (e.g. with respect to migrant children)
  34. 34. COVID-19 & CHILD LABOUR
  35. 35. COVID-19 & child labour CHANNELS OF IMPACTS POLICY RESPONSES • Increased poverty • Increased unemployment • Reduced migration and remittances flows • School closures • Learning losses • Loss of nutritional support • Health shocks (household level) • Expansion of social protection • Increasing benefit levels/coverage of cash transfers • Protect workers in the informal economy (e.g. migrants) • Health insurance • ‘Family-friendly policies’ (e.g. paid parental sick leave) • Access to credit • Decent work for adults • Access to education, especially when schools reopen • Back-to-school campaigns • Teaching at the Right Level & blended learning modalities • Monitoring labour standards Source: ILO & UNICEF (2020)
  36. 36. 2021 International Year of Child Labour KEY INITIATIVES • Updated Global Estimates of Child Labour (June) • Pledges by • Civil society • Private companies • CSOs • Advocacy • Learning events / webinars (#EndChildLabour2021). • Create the foundation for the V Global Conference on Child Labour (VGC) which will take place in 2022 in South Africa. • Stakeholders will share their experiences and will make tangible commitments towards ending child labour in all its forms by 2025.
  37. 37. Thank you! Social Policy Specialist UNICEF Office of Research - Innocenti 37
  38. 38. References Aurino, E., Tranchant, J. P., Sekou Diallo, A., & Gelli, A. (2019). School feeding or general food distribution? Quasi-experimental evidence on the educational impacts of emergency food assistance during conflict in Mali. The Journal of Development Studies, 55(sup1), 7-28. Bharadwaj, Prashant, Leah K. Lakdawala, and Nicholas Li. "Perverse consequences of well intentioned regulation: Evidence from India’s child labor ban." Journal of the European Economic Association 18, no. 3 (2020): 1158-1195. Buchmann, N., Field, E., Glennerster, R., Nazneen, S., Pimkina, S., & Sen, I. (2018). Power vs Money: Alternative Approaches to Reducing Child Marriage in Bangladesh, a Randomized Control Trial. Chakraborty, T., & Jayaraman, R. (2019). School feeding and learning achievement: Evidence from India's midday meal program. Journal of Development Economics. Dammert, A., xa, & C. (2009). Heterogeneous Impacts of Conditional Cash Transfers: Evidence from Nicaragua. Economic Development and Cultural Change, 58(1), 53-83. Dammert, A. C., de Hoop, J., Mvukiyehe, E., & Rosati, F. C. (2018). Effects of public policy on child labor: Current knowledge, gaps, and implications for program design. World Development, 110, 104–123. de Hoop, J., Gichane, M. W., Groppo, V., Zuilkowski, S. S. (2020). Cash Transfers, Public Works and Child Activities. Mixed-method evidence from Tanzania. UNICEF Office of Research – Innocenti Working Paper WP-2020-03. de Hoop, J., & Rosati, F. C. (2014). Does promoting school attendance reduce child labor? Evidence from Burkina Faso's BRIGHT project. Economics of Education Review, 39, 78-96. Del Carpio, X. V., Loayza, N. V., & Wada, T. (2016). The Impact of Conditional Cash Transfers on the Amount and Type of Child Labor. World Development, 80, 33-47. Edmonds, E., Feigenberg, B., & Leight, J. (2019). Advancing the Agency of Adolescent Girls. Edmonds, E. V., & Shrestha, M. (2014). You get what you pay for: Schooling incentives and child labor. Journal of Development Economics, 111, 196-211. Gallego, F., Molina, O., and Neilson, C. (2018). Choosing a Better Future: Information to Reduce School Drop Out and Child Labor Rates in Peru Kazianga, H., de Walque, D., & Alderman, H. (2012). Educational and Child Labour Impacts of Two Food-for-Education Schemes: Evidence from a Randomised Trial in Rural Burkina Faso. Journal of African Economies, 21(5), 723-760. Kazianga, H., Levy, D., Linden, L. L., & Sloan, M. (2013). The Effects of "Girl-Friendly" Schools: Evidence from the BRIGHT School Construction Program in Burkina Faso. American Economic Journal: Applied Economics, 5(3), 41-62. Kondylis, F., & Manacorda, M. (2012). School Proximity and Child Labor: Evidence from Rural Tanzania. The Journal of Human Resources, 47(1), 32-63. Idris, I., Oosterhoff, P. and Pocock, N. (2020) Child Labour in South Asia: Assessing effectiveness of interventions. London: Foreign, Commonwealth and Development Office. International Labour Organization (2008). Report III: Child Labour Statistics. Report No. ICLS/18/2008/III, ILO, Geneva. International Labour Organization (2016). Tanzania national child labour survey 2014: Analytical Report. Geneva.
  39. 39. References - continued International Labour Organization (2017). Global estimates of child labour: Results and trends, 2012-2016, ILO, Geneva. International Labour Organization and United Nations Children’s Fund (2020). ‘COVID-19 and Child Labour: A time of crisis, a time to act’, ILO and UNICEF, New York, 2020. Mitra, S., & Moene, K. O. (2019). Wheels of power. Long-term effects of targeting girls with in-kind transfers. Mukhopadhaya, P., Bhattacharya, U., & MacMillan, C. (2012). Education for child labour: evaluating the national child labour policy in West Bengal, India. Journal of contemporary Asia, 42(4), 651-675. Parker, S. W., & Todd, P. E. (2017). Conditional Cash Transfers: The Case of Progresa/Oportunidades. Journal of Economic Literature, 55(3), 866-915. Ravallion, M., & Wodon, Q. (2000). Does Child Labour Displace Schooling? Evidence on Behavioural Responses to an Enrollment Subsidy. The Economic Journal, 110(462), 158-175. Samantroy, E., Sekar, Helen R., and Pradhan, Sanjib (2016). States of workers in India. Mapping trends. V.V. Giri National Labour Institute and UNICEF. Tang, C., Zhao, L., & Zhao, Z. (2020). Does free education help combat child labor? The effect of a free compulsory education reform in rural China. Journal of Population Economics, 33(2), 601-631. Vuri, D. (2010). The Effect of Availability of School and Distance to School on Children's Time Allocation in Ghana. LABOUR, 24(s1), 46-75.