Child Labour & Social Programming | Focus on Educational Strategies
May. 18, 2021•0 likes•342 views
Download to read offline
Report
Science
Child Labour & Social Programming | Focus on Educational Strategies
Guest Lecture on Child Labour by Valeria Groppo, King’s College London, 19 February 2021
Child Labour & Social Programming | Focus on Educational Strategies
1. CHILD LABOUR & SOCIAL PROGRAMMING
FOCUS ON EDUCATIONAL STRATEGIES
Valeria Groppo, Guest Lecture on Child Labour,
King’s College London
19 February 2021
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. 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. 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. 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. 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. 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. • 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. SOCIAL PROGRAMMING & CHILD LABOUR
OVERVIEW (e.g. Dammert et al 2018, Idris et al, 2020)
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. 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. 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. 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
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. 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. 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. 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. 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
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. 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. 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. 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. 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. 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. 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. 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)
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. 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.
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. 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.