Renu Singh's presentation at UNICEF Innocenti's Inception Scoping Workshop for Evidence on Educational Strategies to Address Child Labour in India & Bangladesh, held in New Delhi in November 2019.

1. Scoping the linkages between child labour,
schooling & marriage in India
Renu Singh
Young Lives India
Inception Scoping Workshop: Evidence on Educational
Strategies to Address Child Labour in India & Bangladesh
13-14 Nov 2019, New Delhi, India

2. Child Labour, Child Marriage & Schooling
in India: Key Facts and Figures
India accounts for a third of the global child brides
6.9 million boys and 5.1 million girls were reported as being married before their respective
legal age (Census, 2011)
10.12 million children in India in the age group of 5-14 years are working and constitute
3.9% of the total child population in the same age group (Census, 2011)
4.98 million children under the age of 14 years who are working (National Sample Survey
(NSSO) 66th Round)

3. Context
As in many other countries, in India, the largest number of children are working in unpaid
family agricultural work.
Over 56% of child labour aged between 7-14 years, work in the agricultural sector, whereas,
unpaid family work amounts to 54% for this age group.
Net Enrolment Rates (NER) of children in primary and upper primary level classes has
increased to 87.3 and 74.7 respectively as a result of RTE Act.
Furthermore, out-of-school children in 6-14 age group has reduced from 32 million in 2001 to
6.04 million in 2013-14, however the NER at upper primary level remains 72.7 and at
secondary level drops to 51.3.
Thus, it appears the country is not yet able to ensure that all children complete a full cycle of
elementary education, with many children dropping out after 14 years of age.

4. Policy Context
Although evidence shows that incidence of both child labour and child marriage are
declining (Census, 2011; NSSO, 2011-12), both child marriage and child labour continue to
be practiced across the country despite legislations expressly prohibiting the same:
• Child and Adolescent Labour (Prohibition and Regulation) Act, 1986, amended in 2016
• Convention on the Rights of the Child and ILO Convention 138 (regarding admission of
age to employment) and Convention 182 (regarding worst forms of child labour)
• Prohibition of Child Marriage Act, 2006 (PCMA, 2006) prohibits girls and boys from
getting married before the attainment of legal age
• Right to Free & Compulsory Education Act, 2009 (RTE Act) making education a
fundamental right for all children in the age group 6-14 years.

5. Objective & Methodology
Aim:
• Unpack links between schooling and child labour
• Focus on pathways between child labour prevalence, educational outcomes (access and
achievement) and marriage in India
Existing evidence in this context already undertaken:
• Initial exploration of 160 research papers, systematic reviews, studies and reports
examining one or more of three dimensions (child labour, schooling, and marriage)
• 120 studies on prevalence, extent and overall issue of child labour in India identified
• 40 studies reviewed extensively that examined interlinkages between child labour and
education. No quantitative studies examined linkages between child labour and child
marriage in India. However, four mixed methods papers based on longitudinal data (IHDS
and Young Lives data) that studied all three themes.

6. Identified Key Questions
What is the existing evidence on linkages between child labour, schooling, and marriage? How does
this vary across age, gender, geography, employment sector and social group (by caste, class, religion
and disability)?
How do variations in schooling and work pathways determine later transitions into adulthood
(employment, marriage, childbearing)?
What are the causal pathways or intersecting drivers of child labour and educational access/outcomes
with marriage? Does schooling promote better employment opportunities and marital partners? Does
work improve children’s likelihood of financing and completing their education and getting married?
How do these hypotheses vary by young peoples’ lived contexts?
What are the gaps in the evidence, especially at the sub-national levels, on the linkages between child
labour, schooling and marriage? What other research questions should we further investigate? Are
there specific areas (geographic, employment sector, etc.) that should be focused on?
What methodologies (primary/secondary data collection, analyses) and resources (existing datasets,
relevant projects, stakeholder networks, studies) should one consider to address these research gaps?

7. Datasets Available in India
Dataset Definition of Child Labour
Census, 2011
All persons engaged in ‘work’ as defined in the Census are considered workers and are categorised as ‘main’ and
‘marginal’ workers. Main workers are defined as those who have worked for the major part of the reference period, which
is 6 months or more. Marginal workers are those who have not worked for the major part of the reference period (<6
months). Provides information on those classified as non-workers but seeking work. Children falling under this category
are “at risk” of becoming child labour, however the estimates for child labour does not include this category.
IHDS-2
(2011-12)
Nationally representative sample of 41,554 households spread over 33 States and union territories. IHDS has separate
modules for different types of work (e.g. on the household farm, wage labour, household nonfarm businesses) and asks
which household members participated in each type of work during the previous year. In the present study anyone who
worked for 30 days and above (at least 240 hours in the previous year across all types of work) is in the labour force.
However, children who worked for below one week and below one months are also shown.
NSSO 68th
Round
(2011-12)
An individual is defined as being employed according to Usual Principal Status (PS), if they engage in the NSS definition
of economic activity for most of the year. All children who are not attending any educational institutions as usual principal
activity status of work (UPAS defines such work as one in which a person mostly stays engaged in a year) are termed as
child labour in this data set.
Young Lives
Captures the following categories of children’s work across two cohorts - Older cohort (born in 1994-95) and Younger
cohort (born in 200-2001) at age 8, 12, 15 (YC and OC), 19, and 22 (OC only): paid work outside the household, unpaid
work for the household (on family farm, cattle herding, shepherding or other family business), domestic chores (fetching
water, firewood, cleaning, cooking, washing or shopping) and time spent caring for other household members (younger
siblings, elderly or ill household members). For this paper, only paid work considered as contributing to child labour.

8. Summary of evidence available in data sets examined
Census IHDS-2 NSSO (68th round) Young Lives
Child Labour
Younger Cohort
(at age 15)
Older cohort
(at age 15)
Sample size (age 5-14 years) 10128663 1495 6518 1451 780
Adolescent workers 15-19 years 15-18 years 15-18 years Data available Data available
By gender 5-19 years 5-18 years 5-18 years Data available Data available
By social grouping 5-19 years 5-18 years 5-18 years Data available Data available
Paid work 5-19 years 5-18 years 5-18 years Data available Data available
By employment sector Data available but categories are different across datasets
Marginal/Main worker 5-19 years 5-18 years 5-18 years Data available Data available
Unpaid work Data not available 5-18 years 5-18 years Data available Data available
Combining school and work Data not available Data available Data available Data available Data available
Geography (Rural/Urban)
5-19 years 5-18 years 5-18 years Data available Data available
Census available at district level
Age at marriage for child labour Data not available Data not available Data not available Data available Data available
Marital status for child labour Data not available Data available Data available Data available Data available
Education status of child labour Literacy data available
Data provides highest
levels of education
attained
Data provides highest
levels of education
attained
Data provides highest
levels of education
attained
Data provides highest
levels of education
attained
Income of child labour Data not available Data available Data available Data available Data available
Time use data of child labour Data not available Data not available Data not available Data available Data available
Spouse’s educational
qualification of child labour
Data not available Data not available Data not available Data available Data available
Spouse’s income of child labour Data not available Data not available Data not available Data available Data available
Age of mother at birth of child
who is a child labourer
Data not available Data not available Data not available Data available Data available

9. RESEARCH QUESTION 1:
What is the existing evidence on linkages
between child labour, schooling, and marriage?
How does this vary across age, gender,
geography, employment sector and social group
(by caste, class, religion and disability)?

10. Research Question 1 (Census)
Census Preliminary Analysis
While Census, 2011 provides cross-sectional data related to work status (5-14 years), it does not
provide information on marital status of child labour. However, marriage data for children aged 5-9, 10-
14 and 15-18 (girls) and 15-21 (boys) can be used to see linkages between child labour and marital
status.
Same applies to education, since information available related to literacy status and enrolment for
children aged 5-14 years. Absence of retrospective question (e.g. to 15-19 year olds ‘Did you engage in
paid work before the age of 14 years?’) makes determining linkages very difficult. Census allows
analysis by State/district and rural/urban location as well as social categories, disability and gender.
Census reports total of 10.12 million child labour in India (5-14 years) of which 4.3 million are main
workers while 5.78 million are marginal workers.
Critical: In 5-14 age group, Census data reveals that 3.9 million children are non-workers but seeking
work. This population is at high risk of becoming child labour.

11. Research Question 1 (Census)
While 2% of the children aged 5-9 years, and 6% of the children aged 10-14 years are
working while 4.15% of the boys and 3.63% girls of age group 5-14 years are workers.
Census 2011 reveals that among the child workers, 75% belonged to the age group 10-14
years and 25% were from the age group 5-9 years. There is an increase in the share of girls
amongst child labour from 44% in 2001 to 56% in 2011.
There also exists a lot of inter-State variation in the proportion of working children in the age
group of 5-14 years e.g. Kerala has only 3% working children compared to 32% working
children in the age group 5-14 years in Gujarat.

12. Research Question 1 (NSSO)
NSSO Preliminary Analysis
NSSO 68th Round allows us to link child labour in the age group 5-14 cross-sectionally with
educational level/s, literacy and marital status. Analysis of data by State, social caste groups
and urban/ rural locations and gender is possible from the given data.
Although NSSO data is rich from the perspective of a household data source, it’s limitations
with regard to the measures for child work must be noted. In rural areas child work is often
highly seasonal and may be misreported. If it occurs in conjunction with schooling, there is
potential for ambiguity when the principal and secondary activity statuses of children are
recorded.
As per NSSO 68th Round (2011-12) child labour prevalence was 6.95 % in India among 5-14
years old (7.5 % girls and 6.5% for boys) with boys having a larger share (53.4%) than girls
(46.6%) and was the highest in the State of Uttar Pradesh (14.2%).

13. Research Question 1 (IHDS)
IHDS Preliminary Analysis
Both IHDS-2 and Young Lives longitudinal data sets allow one to analyse linkages between
child labour, schooling and marriage across time and also desegregate the analysis by
gender, caste, rural and urban locations. It is important to highlight that while IHDS-2 is
spread across various States, the Young Lives data is limited to two Southern States i.e.
Telangana and Andhra Pradesh.
IHDS-2 provides information on marital status as well as caste, religion, location and
educational level of respondent. It reports 7.6% of its sample children engaged in paid work
amongst 5-14 years old with highest prevalence in Himachal Pradesh.

14. Research Question 1 (Young Lives, OC Age 12)
15.5
7.3
3.4 1.7
72.1
9.7 8.4
3.7 4.5
73.7
0
10
20
30
40
50
60
70
80
Paid work & school Only paid work Unpaid work &
school
Only unpaid work Not working (full time
school)
Male Female
%ofchildren

15. Paid Work At 12 & Marital Status of Girls
at 19 (Young Lives)
Devi Sri, a Backward Class girl was married at
the age of 15, after completing Grade 9. She
said that she had been combining work and
school since Grade 7. Her first job, in flower
harvesting, required her to work over the
weekends and holidays, while she washed
clothes on Sundays as well as fed her family’s
livestock and washed the dishes.
She reported that while her father was not in
favour of the children doing hard labour, her
mother felt that we [were] poor and she sent us
for work, to make as much money as we could.”
69.3
22.7
8.1
36.8
52.9
10.3
Single Married before
18
Married at 18 and
after
Paid Work at 12***
Not Engaged In Paid Work
Engaged in Paid Work
%ofchildren

16. Research Question 1: Qualitative
Findings Young Lives
The practices of child marriage is rooted in patriarchy and gender discrimination, and the
treatment of boys remains distinctly different from girls, starting from a very young age.
Ramya’s mother said that while she took her two daughters to work on the farm even while
they were attending school, she did not do the same to her son. When asked to explain this
discrimination she suggested that
..girls are healthier. That’s why. When the girls are working anyway why should he work?
And he is the only son we have. That’s why we did not let him work on the farm.

17. Research Question 1 (Young Lives)
1.00
0.91
0.72
0.24***
1.00
0.37***
0
1
2
3
0 Hour (Ref) 1 Hour 2 Hours 3 & more hours No (Ref) Yes
Hours Spent on Household Chores (R2) Paid Work (R2)
OddsRatio
Odds Ratio Predicting Likelihood of Completion of Secondary Education

18. Research Question 1: Activity Status (Young
Lives, 22 years)
14.8
27.9
59.1
38.2
14.1
5.9
12.0
27.9
Male Female
Unmarried
Only studying Working full time Studying and working Not studying and not working
1.9 0.7
91.6
48.1
1.9 0.7
4.7
50.4
Male Female
Married

19. RESEARCH QUESTION 2:
How do variations in schooling and
work pathways determine later
transitions into adulthood
(employment, marriage, childbearing)?

20. Research Question 2 (Young Lives)
A complex mix of factors, including poverty, gender, caste, ethnicity, parental ill-health, and attitudes to
work, appear to intersect to explain why children took up paid work.
An analysis of the older cohort data when the index children were 7-8 years and 11-12 years old,
reveals that children in households affected by a crop/natural disaster shock increase the hours worked
per week by 1.8 hours, equivalent to a 28% increase relative to the average.
Analysis revealed that children who have better reading skills were found to work less.
A mixed-methods paper to determine what factors shape the trajectories of girls aged 19 years into
early marriage in Andhra Pradesh and Telangana identified a multitude of factors including paid work at
age 12.
While 57% of the girls who had not completed primary education got married by 18, only 6% of girls
who had completed higher secondary education or higher levels of education were married by that age.
Being out-of-school at 15 is a very strong predictor of being married before 19

21. Young Lives: Age of Marriage

22. Research Question 2: Top 3 reasons for
leaving school (girls, 22 years)
28.8
20.6
17.8
43.2
11.1
8.6
31.3
17.5
8.8
0
10
20
30
40
50
Marriage Domestic
work
Long
absence
from school
Marriage Domestic
work
Long
absence
from school
Marriage Domestic
work
Long
absence
from school
%ofchildren

23. Research Question 2: Top 3 reasons for
leaving school (boys, 22 years)
%ofchildren
26.9
21.2
13.5
34.8
17.4
13.0
21.2
20.0
10.6
0
5
10
15
20
25
30
35
40
Long
absence from
school
Paid work Domestic
work
Long
absence from
school
Paid work Domestic
work
Paid work Long
absence from
school
Banned from
school
Before Upper-primary Before Secondary Before Higher Secondary

24. Research Question 2 (Young Lives)
Young Lives evidence shows that girls’ participation in paid work at the age of 12 is significantly
associated with the age at which they got married. The descriptive analysis found that 53% of girls who
did paid work at the age of 12 were married at 18, compared to 22% who remained unmarried at 18
years of age.
276
212
243
0
50
100
150
200
250
300
Single at 22 Early marriage Married
between 19-22
Marital Status**
Daily earning (INR) at Age 22
37.5
93.7
62.5
6.3
0
20
40
60
80
100
Single Married
Enrolment of Girls by Marital Status***
Not Enrolled at age 19 Enrolled at age 19

25. RESEARCH QUESTION 3:
What are the causal pathways or intersecting drivers of child
labour and educational access/outcomes with marriage? Does
schooling promote better employment opportunities and
marital partners? Does work improve children’s likelihood of
financing and completing their education and getting married?
How do these hypotheses vary by young peoples’ lived
contexts?

26. Research Question 3
Across diverse contexts, research shows that, on average, more education is associated with later
marriage and later childbearing. However, it is difficult to determine causal pathways. A recent evidence
review conducted on child marriage in South Asia, including India highlighted that the evidence on the
causal relationship between child labour and education is mixed, and that causality can be difficult to
establish.
While education and age at marriage and pregnancy are positively correlated in many settings,
evidence of a causal relationship remains limited.
Existing evidence of the strength of the relationship between marriage, childbearing and education is
mixed and largely observational, limiting the opportunity to draw causal inferences.
Quasi-experimental approaches and use of statistical methods aimed to adjust for endogeneity might
be the best option to estimate causal relationships between education, marriage and childbearing.

27. Research Question 3
Longitudinal studies such as Young Lives do provide the information on the trajectories of young people
as they enter family formation and parenthood. Round 5 of the Young Lives survey found that 56% of
young women and 11% of young men were married by 22-years with 28% girls married and 13%
having given birth, before the legal age of 18 years.
Though Round 5 found that 28% of young married women and 12% of unmarried ones were neither
studying nor working, it will be important to analyse the labour market opportunities as well as spousal
partner characteristics in Round 6 (2020), when the older cohort will be around 26 years old.
There remains very limited comparative research available on the most cost-effective strategies for not
only keeping girls in school and out of marriage but improving educational outcomes for girls.
The relationships between child marriage, pregnancy and child labour will undoubtedly be influenced by
a host of underlying factors, including poverty, cultural and gender norms and related factors, which will
be context specific. However, research often fails to capture this evidence, e.g. ‘How child labour might
be viewed in diverse contexts?’, nor does it necessarily account for the range of different work carried
out by children across and within country contexts.

28. Young Lives- Qualitative Research
Intergenerational Transmission of Poverty
Bhavana’s mother, who did not complete her primary schooling, was married at the age of
12. Bhavana was made to leave school after Grade 2 following the death of her father and
the family migrating for seasonal work to Mumbai.
Her mother believed: “Even if educated and the girl went to school…it would make no
difference and there would be no change in our life. It makes no difference whether educated
or not educated…even if she were to be educated, still it not possible to get a job; she might
still have to work; there are no jobs around. Then what’s the point in getting schooled? No
schooling can get her a job. She has to work…that’s all. We were wise enough [to] let them
[her children] drop out of school. We are not sure of any job – anyway there are many
jobless here. Who is getting jobs? I haven’t seen a single person from this village getting a
job and feeding others.’
Interviewer: Do you find any difference in the work done and the life between you and your
mother?
Bhavana: I saw my mother since my childhood…she has been doing hard work without
taking a break even for a day…It is same [for me...I am also working in the same way.

29. RESEARCH QUESTION 4:
What are the gaps in the evidence, especially at the sub-
national levels, on the linkages between child labour,
schooling and marriage? What other hypotheses or research
questions should we further investigate as part of this project?
Are there specific areas (geographic, employment sector, type
of child labour etc.) that we should focus on?

30. Research Question 4
Various gaps in available evidence related to links between child labour, schooling and marriage:
1. Research on how poor-quality education pushes children out of the classroom and into the workforce;
2. In-depth studies on the gendered nature of new opportunities for paid employment among children
including time use data that captures paid and unpaid work
3. Census identifies children in 5-14 age group who are non-workers but seeking work. Research focused
on understanding their reasons for seeking work need to be better understood
4. Research on children working in family enterprises as well as children combining school and work
5. Children in domestic work remain a neglected population. Need to learn more about their condition
6. Indebtedness in families related to dowry, crop failure etc leading to children taking up paid work
7. Focused research on inter-linkages between child labour, schooling and early marriage for boys
8. Examination of wage difference in young women who had entered paid work before the age of 14 and
married early through a longitudinal study
9. Need for demographic surveys to collect information on social, cultural, and economic and the
contextual factors that shape gender norms that influence timing of marriage
10. Identification and evaluation of current interventions targeting child labour, child marriage and schooling
together
11. Significant “within-country” variation in rates of child marriage, child labour and educational achievement

31. RESEARCH QUESTION 5:
What methodologies (primary/secondary data
collection, analyses) and resources (existing
datasets, relevant projects, stakeholder
networks, studies) should we consider to
address these research gaps?

32. Research Question 5
An evidence gap map (EGM) found a lack of uniformity and comparability among variables, scales and indicators used to measure
interventions. Useful to provide homogeneity in definitions, variables and indicators to allow for greater comparability across data
sources, e.g. by working with communities of evaluators
Experimental and quasi-experimental studies specially designed to integrate interventions to address issues related to unravelling
‘what works’ to combat child labour, school drop-out and child marriage very useful.
Examine role of parental and child aspirations as well as relevance of education and social protection schemes to tackle child labour,
early marriage and schooling through a well-designed mixed methods survey. Why some parents go to great lengths to keep
daughters in school, whilst others pull them out for marriage or work needs to be studied to determine most effective interventions.
Survey data tends to portray children as either in or out of school. Must undertake qualitative studies to shed light on more dynamic
realities, since the educational trajectories of working children are seldom continuous or linear.
Child marriage and child labour are closely linked with educational attainment but directionality of the relationships, and extent to
which these relationships are causal, is less clear.
Given this limitation, future studies should gather detailed longitudinal data on girls and young women, examining outcomes and life
course trajectories, not only prior to marriage but also after marriage. Such data would enable sequencing of life events for girls,
including timing of school completion or dropout, marriage. Having data over time on the same individual enables temporal ordering
of life events in the analysis, helping address data limitations.

33. We owe them
There is no trust more sacred than
the one the world holds with
children. There is no duty more
important than ensuring that their
rights are respected [and] that their
welfare is protected…
- Kofi Annan