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Analysis of Socio-Economic Determinants of Child Labour in Lagos
State, Nigeria.
AKINWOLERE, Bukola Comfort
1
, Prof. MAGAJI, Sule
2
, Dr. SANI Bariki Sabiu
3
1
Economics Department, School of Arts and Social Sciences, FCT College of Education Zuba-Abuja,
Nigeria.
2,3
Department of Economics, University of Abuja, Nigeria
DOI: https://doi.org/10.47772/IJRISS.2025.91100410
Received: 28 November 2025; Accepted: 03 December 2025; Published: 13 December 2025
ABSTRACT
The incidence of child labour persists in Lagos state, Nigeria despite the Child’s Rights Act 2003 that has been
domesticated by the state. As a result, the study analyzed the socio-economic determinants of child labour in
Lagos state, Nigeria. Both descriptive and inferential analyses were employed in the study. Specifically, Tobit
regression was utilized to analyze the quantitative primary data collected through structured questionnaire from
the study area. The findings revealed that increase in household income raises the probability of a child working
with 1% level of significance. The findings further indicated that the educational level of the household head has
no significant effect on child labour. The findings also indicate that the employment status of the household head
does not significantly influence the likelihood of children engaging in work. Moreover, the findings revealed that
the likelihood of the household head having dependents have a negative and insignificant impact the probability
of a child engaging in work. Furthermore, the findings highlight that a child's gender does not significantly
influence the likelihood of engaging in work. The study concluded that child labour in Lagos state is significantly
influenced by household income, parent's employment status, the parent’s educational level and the level of
dependency. The study recommended that affordable and accessible education in marginalized areas in order to
boost school enrolment and retention rates, as well as reducing the amount of time children spend in labour.
Keywords: child labour, household Income, child's gender, parent's education, employment status, household
dependents
INTRODUCTION
According to United Nations Children’s Fund (UNICEF, 2024), children all around the world often engage in
both paid and unpaid employment that is beneficial to them. However, children are categorised as child labourers
when they are too young to work or engage in risky activities that could jeopardise their physical, mental, social,
or academic development. Abdallah (2020) substantiates that Child labour is a multifaceted development issue,
and associated causes are differed. Olayinka (2022) consequently, as observed, eradicating the incidence of child
labour in any society will be difficult without figuring out its root causes. Child labour is often characterised as a
pernicious and evil act that has to be rigorously disallowed (Borko, 2017).
For the possible eradication of incidence of child labour globally, as it correlates with the Sustainable
Development Goals of eliminating all forms of child labour by 2025, policies must focus on the root causes of
child labour and offer practicable solutions in alignment with the peculiarity associated to their source in various
country or region.
Statement of the Problem
The persistent incidence of child labour Lagos state despite the legislation enacted to restrain it constitutes the
problem of interest for this research. Hence, there is a need to carry out a conscious and thorough investigation
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into its root causes so as to come up with the right approach and policies that will be sufficient and efficient in
eradicating the hazard of child labour and meet up with the Sustainable Development Goals to eliminate Child
labour by 2025. Based on literature reviewed regarding Socio-economic determinants of child labour, thorough
investigation of the socio-economic determinants of child labour in Lagos state Nigeria constitutes the problem
of interest for this research.
Aims and Objectives of the Study
The main objective of the study is to assess the Socio-economic determinants of child labour in Lagos state,
Nigeria. The specific objectives are to:
I. Examine the effect of household Income on child labour in Lagos state, Nigeria.
II. Determine the effect of parent level of education on child labour in Lagos state, Nigeria.
III. Investigate the effect of employment status of household head on child labour in Lagos state, Nigeria.
IV. Determine the effect of household dependency on child labour in Lagos state, Nigeria.
V. Examine the effect of child’s gender on child labour in Lagos state, Nigeria.
LITERATURE REVIEW
The Concept of Child Labour
Child labour is a deed to deprive children of their childhood, potential and dignity, which is hazardous to their
mental and physical development, endangering their physical and mental development (ILO, 2017). UNICEF
(2024) corroborates this by describing child labour as practices that compromises a child's physical, mental, social
and educational development. Children who engage in this act are usually subjected to mental harm, physical
injury, and verbal harassment by their employers and parents. Furthermore, they found it difficult to report their
victimisation to the designated authority due to the uncertainty of the outcome (Avasthi & Avasthi 2016). Musa,
Magaji, and Ahmed (2022), child labour is any economic activity involving children that is risky enough to
exploit them and interfere with their well-being.
According to the International Labour Organization (ILO) Minimum Age Convention of 1973, Number 138 (1),
child labour is defined as any employment performed by a person under the legal minimum working age. UNICEF
(2024) highlighted that child labour is being determined as any work that exceeds a minimum number of hours
considering the age of the child and hours spent per day on work either economically or non-economically. The
minimum of number of hours includes at least one hour of economic work and 28 hours of household labour per
week for kids between the ages of 5 and 11. While, it entails at least 14 hours of economic employment or 28
hours of household work per week for children aged 12 to 14.
Parental Employment Status
NBS and ILO, (2022) reveals that employment status of the household head is another indicator of socio-
economic determinant of child labour. Heads of households who are unemployed or who are outside the labour
market altogether are more likely to be in situations that will resort to their children engaging in child labour.
Parikh and Sadoulet, (2005) suggest that incidence of child labour in a family depends on the status of the
occupation of the parents. There is link between status of employment of parents and child labour (Owoyomi,
2018)
Household Income
Musa and Magaji (2023) assert that household income is one of the significant indices that determine incidence
of child labour in the family. They opine that high household income eliminate poverty in the family and reduces
child labour. Khan, and Mawon, (2022) investigated “Child Labour from Child’s Perspective”. He found out that
most children claimed that they were driven into labour because of insufficient household income, while some of
the children quit schooling and start to work at the tender age based on the inability to pay school fees.
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Parental Education
Victor (2018) suggests that parental educational background is also one of the key factors that can influence a
child’s educational attainment, protect him/her from the economic violence of child labour and engender overall
sustainable child development, provided the parents are well-educated. Victor (2018) expatriates that parents that
supply more labour and achieve less education as children grow up to be poor as adults; consequently, such
conditioning is sometimes or more often passed to the children, thereby perpetuating child labour across
generations or better still, propelling intergenerational poverty of child labourers.
Household Dependency
Children growing up in larger families often find themselves in situations where they have to work, as their
families face the challenge of supporting more dependents. This struggle is made even harder when elderly
relatives don’t have pensions or financial support, placing additional pressure on the household and pushing
children into the workforce to help make ends meet, NBS and ILO (2022).
Gender Issues in Child Labour
Putnick and Bornstein (2016) noted that girls performed greater labor rates inside the home and greater work
undertaken by boys outside the home. Notwithstanding, gender differential in participation rates differ from one
country to another. According to Fikre and Abebe (2021), child labour is significant influence by child’s gender,
girls are more likely to engage in child labour than boys.
Conceptual Framework
Theoretical Framework
Rational Choice Theory
Rational choice theory, also referred to as choice theory or rational action theory, provides a framework for
understanding and modeling social, economic, and individual behaviors. As a dominant paradigm in
microeconomics, it extends its influence to fields such as political science, sociology, and philosophy. The theory
emphasizes that individuals make decisions based on a systematic evaluation of costs and benefits to maximize
their personal advantage. Notably popularized by Gary Becker, a Nobel laureate in Economics, the concept posits
that when faced with multiple options, individuals tend to choose the one they believe will yield the best overall
outcome (Elster, 1989). This approach has been described as a unified framework for understanding human
behavior and is seen as a rigorous model of social action (Becker, 1976; Rogowski, 1997). Rational choice theory
offers valuable insights into decision-making processes by assuming individuals act in their own self-interest to
maximize utility, it operates under conditions that rarely exist in reality. The theory's premise of 'all things being
Household Income (N)
1-999; 1000-1999, 2000-2999;
3000-3999, 4000-4999
Employment Status of Household head :
formal sector (public sector or private sector);
Informalsector/selfemployed;unemployed/none
Gender of the Child: Male, Female or
Prefer not to say
Parental level of education None; Primary;
Secondary; ND /NCE; BSc/HND;
Postgraduate
Household- dependency 1-5, 6-10, 11-15
Child Labour
working hours of the child
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equal' is often not applicable in complex social contexts where values, beliefs, and situational factors significantly
influence decisions. Consequently, individuals may not strictly adhere to the rational model; instead, they often
navigate choices based on intuition or experience to achieve what they perceive as the best outcomes. This
subjectivity suggests that human decision-making can encompass both rational and irrational elements depending
on the circumstances (Friedman, 1953).
METHODOLOGY
Research Design
This study is a survey research design. Check and Schutt (2012) defined survey research as the collection of
information from a sample of individuals through their responses to questions. This research employs the
combination of descriptive statistics and the Tobit Regression model. The descriptive analysis is used to explain
the characteristics of the demography of the various area of interest of the study. At the same time, the Tobit
explains the impacts of selected economic variables on child labour.
Sample Size and Sampling Procedures
The data of Socio-economic determinants of child labour in Lagos state is obtained from three selected LGAs
states using stratified sampling techniques. All the Local Government Areas were grouped according to their
senatorial district (Zone A, Zone B and Zone C). From the selected three (3) LGAs, 4 wards were selected from
each of the LGA; thus, we have 12 wards (i.e., 4 wards multiplied by 3 LGAs each) using purposive sampling
method. The selection covered both rural and urban areas since Olayemi et’al (2016) revealed that incidence of
child labour is more in urban areas as a result of large number of households moving from rural area to urban
area. Thirty-two households were selected per each ward while extra one household was selected in the ward
which appear with more incidence of child labour which gives the total number of households as 385.
The study adopts Cochran’s Sample Size Formula as identified by Smith (2021) to determine sample size. The
reason being that Cochran’s Sample Size can be used when the population is unknown.
At 5% significance level, the Z-score is equal to 1.96. Smith (2021) suggested standard deviation (Std Dev) of
0.5 as the most lenient number that ensures a sample that will be large enough.
(Per each state)
Table 3:1 Sample Size
State
Selected LGAs
No of Wards in
selected LGAs
Selected Wards
No of selected child and
household-head per Ward
Sample
size
Lagos
Total
Zone A =Lagos- Central
(Surulere)
12
1. Iponri /Eric moore
32
128
2. Yaba/Ojuelegba
32
3. Orile
32
4. Ikate
32
Zone B
=Lagos-East
(Ikorodu)
19
1. Isele
32
128
2. Ijede
32
3. Erikorodo
32
4. Odogunyan
32
Zone C =Lagos-
West(Oshodi Isholo)
11
1. Shogunle
32
129
2. Mafoluku
32
3. Oshodi
33
4. Ejigbo
32
385
Source: Researcher’ Compilation, (2024)
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The table 3.1 shows the three selected LGAs which include; Surulere LGA from senatorial district zone A,
Ikorodu LGA from senatorial district zone B and Oshodi Isolo LGA from senatorial district zone C. In Surulere
LGA, four wards were selected which include; Iponri/Eric moore, Yaba/Ojuelegba, Orile and Ikate. In Ikorodu
LGA, four wards were selected which include; Isele, Ijede, Erikorodo and Odogunyan. In Oshodi Isholo LGA,
four wards were selected which include; Shogunle, Mafoluku, Oshodi, and Ejigbo.
Nature and Source of Data
The pre-tested of the administration of structured questionnaires for this study were carried out among 20 children
between 5-14 age group and their household heads within the area of Mafoluku, Oshodi, Lagos state, Nigeria.
Albeit, these selected twenty were not part of the data for the main study. The reason for the pre-testing was to
ensure that the questions are clear, straight to point, complete and applicably structured. However, at the end of
pre-testing, questionnaires were restructured to completely address the main and specifics objectives of the study.
The data used for this study was collected from primary source between august, 2023 to February, 2024. The
questions were made up of both open-ended and close-ended. The data were obtained from the selected local
government areas through the administration of structured interviews/ questionaires to the child between 5-14
years and his or her household-head using purposive sampling method to ensure that only predominantly children
in child labour and their various household head were the respondents. Which in line with the assertion of
Lichand, and Wolf (2023) that computed data on child labour should be based on surveys with adult and children.
Model Specification
This study is hinged on rational choice theory as the theoretical framework. It is a framework designed to
understand the social and economic determinants of child labour. The Censored Tobit regression model which
was introduced by James Tobin in 1958 is used to analyze the Socio-economic determinant of child labour in
Lagos state, Nigeria. The reason being that Tobit regression is a kind of regression analysis that is used when
dependent variable is censored or truncated.
The model used for this study is adapted from Musa, Magaji, and Ahmed (2022) on the analysis of the basic
infrastructures affecting child Labour in North-Eastern Nigeria. Their model is given as;
Where:
= Constant Parameter of the Equation
= Coefficient of the Independent Variable
= Distance of Schools from household in kilometers (km)
= Distance of Hospitals from household in kilometers (km)
= Access to Electricity
= Access to Clean Pipe borne Water
= Error Term
Their variables are replaced with household income, parental level of education, employment status of the
household head, household dependency sex of the child, and gender of the child because of its direct relevance
to the subject and objectives of the study and as such, the model is given as follows:
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Where:
= Child labour
= Constant Parameter of the Equation
1,
2,
3,
4,
5,
6
= Coefficient of the Independent Variables
= Household Income
= Parental level of education
= Employment status of household head
= Household Dependency
= Sex of the child
DATA PRESENTATION, ANALYSIS AND INTERPRETATION OF RESULTS
Table 4.1: Model Specification Test
Children engaged in work
Children working 3-4Hrs
Prob. > │t│
Children working 5Hrs & Above
Prob. > │t│
Linktest
_hat
0.000
0.000
0.000
_hatsq
0.015
0.001
0.000
Source: Author’s Computation, 2024, STATA Version 16
Table 4.1 shows the model specification test to check if specification error exists in the model, in order to avoid
bias and spurious regression. The result shows that the predicted value (hat) for the model is significant meaning
that the model is correctly specified given a significant value of the predictors (hatsq), this is determined by the
p-values less than 0.05.
Table 4.1: Cronbach Alpha Reliability Test
Reliability Test
Cronbach's Alpha
Value
.6257
Source: Author’s Computation, 2024, STATA Version 16
Table 4.1 shows the value of the Cronbach alpha for the data collected. The result reveals the alpha value as 0.63
in data collected from Lagos state, implying 63% reliability and internal consistency rate. This suggests a
moderate reliability in the dataset.
Estimated Result for Socio-Economic Determinants in Lagos state
Variable
Children engaged in work
Children working 3-4Hrs
Children working 5Hrs & above
-.2843***
(0.001)
[0.0838]
-.04909
(0.299)
[0.0472]
-.1282*
(0.097)
[0.0769]
.0140
(0.792)
[0.0531]
-.0382
(0.364)
[0.0421]
-.0766
(0.263)
[0.0684]
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-.0679
(0.394)
[0.0795]
-.0863
(0.101)
[0.0524]
-.1268
(0.139)
[0.0855]
-.0087
(0.958)
[0.1639]
.1717
(0.130)
[0.1132]
.2669
(0.149)
[0.1846]
-.1275
(0.309)
[0.1252]
-.0289
(0.740)
[0.0873]
-.0559
(0.695)
[0.1422]
-.1362
(0.153)
[0.0951]
-.0989
(0.149)
[0.0684]
-.1561
(0.164)
[0.1118]
-.0247
(0.593)
[0.0461]
-.0352
(0.297)
[0.0337]
-.0729
(0.185)
[0.0548]
.0962
(0.561)
[0.1656]
.0753
(0.534)
[0.1211]
.0123
(0.950)
[0.1977]
.0449
(0.544)
[0.0740]
.0665
(0.179)
[0.0494]
.1073
(0.183)
[0.0805]
.8409***
(0.000)
[0.2156]
-.5739***
(0.000)
[0.1363]
-.914***
(0.000)
[0.2215]
.0509
(0.521)
[0.0793]
.1336***
(0.013)
[0.0537]
.2018***
(0.021)
[0.0873]
.0352
(0.225)
[0.0289]
.0570***
(0.004)
[0.0196]
.1006***
(0.002)
[0.0319]
.0869
(0.269)
[0.0785]
.0497
(0.320)
[0.0499]
.0766
(0.347)
[0.0814]
-.2348
(0.534)
[0.3775]
-.5406
(0.0.112)
[0.3395]
-1.2108**
(0.027)
[0.5436]
.0185
(0.922)
[0.1883]
-.1524
(0.237)
[0.1287]
-.2643
(0.207)
[0.2093]
.0395
(0.465)
[0.0539]
.0832**
(0.058)
[0.0437]
.1111
(0.119)
[0.0711]
.4989***
(0.000)
[0.0993]
.1638**
(0.015)
[0.0669]
.1221
(0.263)
[0.1089]
.0277***
(0.005)
[0.0099]
.0205***
(0.004)
[0.0070]
.0304***
(0.008)
[0.0114]
Note: Robust standard errors are in parentheses [-] and P-value (-), P-value significance *10%; **5%; ***1%
Source: Author’s Computation, 2024, STATA Version 16
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Policy Implications of the Findings
The analyses of this study are channeled toward evaluating the socio-economic determinants of child labour in
Lagos state, Nigeria, with specific interest in the implications of household income, educational level of
household head, employment status of the household head and household dependency of the household on child
labour. These findings conform with the assertions of Dasgupta and Mukherjee (2022) and Musa et al. (2022b)
that revealed that children’s age, children’ gender, children relationship with the household head, household
head’s education, household head’s employment and poverty which is measured by households’ income and
family size.
Policy Implications Findings on the Effect of Household Income on Child Labour
The results indicate that daily household income has a negative and significant effect on children engaging in
work with P value of (0.001). The implication of this is that when household income increases, ceteris paribus,
child labour is expected to reduce. This further justify the assertions of Oluyemi et al., (2016) and Ozoh and
Chinecherem (2017) that poverty as a result of low income in many families is a strong determinant of child
labour among developing countries.
Policy Implications Findings on the Effect of Child’s Gender on Child Labour
The gender of the child has no significant effect on child labour in Lagos state. The probability value is greater
5% significant level. This further implies that either a child is male or female does not necessarily influence the
probability of engaging in work and does not also influence the hours of work that a child can put in any work
activity in the states. This is contrary to the study of Hailu and Temesgen (2020) in Ethiopia.
Policy Implications Findings on the Effect of Birth order of the child on Child Labour
Concerning the effect birth order of the child-on-child labour, the findings further juxtaposed that irrespective of
the position of a child in the family, he or she can still be involved in child labour. Although, both first born and
second born are found more in child labour. This suppose the assertion of Shirazi and Jalbani (2004) who claimed
that birth order can affect the dynamics of child labor believing that firstborn children might be expected to
contribute more substantially to family finances compared to their younger siblings due to cultural expectations
or parental beliefs that younger children are often viewed as more vulnerable and less capable of contributing to
family income, whereas older children may be considered more suitable for work responsibilities.
Policy Implications Findings on the Effect of Education Level of child on Child Labour
The education level of the child has no significant effect on child labour in Lagos state. The probability value is
greater 5% significant level. This further implies that either a child level of education does not certainly influence
the probability of engaging in work and does not also influence the hours of work that a child can be engaged.
This is contrary to the assertion of Begum, Iqbal and Hina (2018) who posited that there is a negative relationship
between child’s level of education and child labour.
Policy Implications Findings on the Effect of Employment status of the Parents
The result shows that the employment status of the household head has no significant influence on the probability
of children engaging in work in Lagos state. In contrast to the Akinola, Onipede, and Michael (2019), the
employment status of the parents has a negative relationship with child labour and are statistically significant.
Contrary to theoretical assumptions, findings showed that the employment status of the household head does not
really affect the probability of a child involved in child labour. This might be traced to the meagre income of the
household head which does not really commensurate with the employment status thereby making the employment
of no real impact in the family upkeep.
Policy Implications Findings on the Effect of Living Status of Parent on Child Labour
On the effect of parents of the child being alive or not on child labour, the estimate shows that parents of the child
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being alive or not has no significant influence on the probability of children engaging in work, regardless of the
hours used. This suggests that the possibility of a child’s parent being alive or not does not exactly affect the
probability of engaging in work. This negates the assertion of Borko (2017) loss of parents drive children into
child labour.
Policy Implications Findings on the Marital Status of the parents on Child Labour
The study found that the marital status of the parents determines the child being involved in child labour. The
married status of parent lessens the incidence of child labour. This is in line with the findings of Orisa-Ubi and
Kpe-Nobana (2019) which believed that children from broken home and family instability are characterized with
incidence of child labour.
Policy Implications Findings on the Effect of Child’s Relationship with the HouseholdHead
In conformity with the findings of Ifeanyichukwu, Ezeano, and Nnadozie (2018), this study established that the
relationship between the child and household heads can determine if the child will be involved in child labour or
not. This further confirmed that the child with a cordial relationship with the house hold head tends to have a
lesser risk to child labour than a child with a non-cordial relationship with the household head.
Policy Implications Findings on the Effect of Gender of the Household head
The gender of the household head also influenced the incidence of child labour in Lagos state Nigeria. The
implication is that where the household head is a male, the possibility of a child labour reduces. This corroborates
with Clott (2015) who claimed that female-headed households might confront greater financial difficulties,
consequentially leading to incidence of child labor in the family.
Policy Implications Findings on the Effect of Parental Education on Child Labour
Contrary to Dasgupta and Mukherjee (2022), it was also discovered from the findings of this study that the higher
education level of the household heads and that of their spouses does not really lessen the incidence of child
labour in the family.
Policy Implications Findings on the Effect of Household Dependency on Child Labour
With the increasing household dependency of the household head as established in the study, an increase in the
possibility of the household head having dependents increases the frequency of child labour in the study area.
This buttresses the assertions of Harasty and Ostermeier (2020) and Borko (2017) that the contributions of
poverty to child labour is significantly outweighed by those of the child household dependency. The implication
of this is that when the number of dependents increase, the burden of the household held will increase leading to
increased rate of child labour.
Policy Implications Findings on the Effect of a Child Joggle Between School and Work
As shown in the findings, the children joggle between school and work which invariably increased the days of
children’s absenteeism in school per week. In a way, both combining school and work and being absent in school
have significant effect on child labour in Lagos state. This is in support with the findings of the Abdu, Rabiu, and
Usman (2020) which opined that reduced school attendance and poor performance accelerate incidence of child
labour.
Policy Implications Findings on the Effect of Age of the Household Head on Child Labour
Likewise, the age of the household held influenced the incidence of child labour amongst the children in Lagos
state. This is in tandem with the findings of Adeoye et al (2017) which argued that the age of the household head
is a key determinant that drives the involvement of children engaging in work activities.
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CONCLUSION AND RECOMMENDATIONS
Conclusion
This study investigated the impact of household factors on child labour in Lagos state with an emphasis on
household income, gender of the child, the household head's employment status, and the educational levels of
both the household head and their spouse.
Household income is a key factor in affecting child labour outcomes. Higher household wealth is connected with
a lower likelihood of children engaging in child labour. Nonetheless, the gender of child was shown to have no
substantial influence on the likelihood of children working. This implies that, while gender may not be a direct
predictor of child labour, it can influence labour intensity in specific settings. More so, the household head's
employment status had no significant effect on child labour. A higher educational level of the family head was
positively connected with a higher likelihood of children working for shorter periods of time (3 to 4 hours),
implying that education may lessen the intensity of child labour. Furthermore, the spouse's education level
influenced child labour.
Recommendations
The following recommendations are given based on the findings about the determinants of child labour in Lagos
state Nigeria.
1. There should be conscious efforts by the government of Lagos state directed toward increasing household
income through economic empowerment, as higher income correlates with a decrease in protracted child
labour. In contrast, initiatives must address the paradoxical relationship between rising wealth and more
child labour. This may entail investigating social norms, economic dependencies, and cultural variables
that maintain child work, even in affluent households.
2. Education appears as an important instrument in fighting child labour, demanding strong steps to improve
access and quality. Expanding inexpensive and accessible education in marginalized areas can boost
school enrolment and retention rates, reducing the amount of time children spend in labour. Conditional
cash transfer programs should be created or strengthened to incentivize families to put their children's
education first.
3. Key priority social protection and intervention programmes should be improved. Universal child benefits
can lessen the financial pressures that lead to households relying on child labour, whereas emergency
support programs can avoid increases in child labour during economic downturns or crises. Income-
generating efforts, such as microfinance access and parental vocational training, can also provide families
with additional sources of income, lessening their reliance on their children's labour contributions.
4. There is need for developing long-term job possibilities for parents. Decent work initiatives, backed by
governmental and private sector investments, can generate jobs with secure wages, minimizing the need
for children to labour. Skills development efforts suited to local labour market demands can improve
parents' employment opportunities while guaranteeing long-term economic stability.
5. Collaboration among governments, non-governmental organizations, and the corporate sector can boost
the effectiveness of these interventions. Businesses should be encouraged to undertake corporate social
responsibility by eliminating child labour from supply chains and investing in community development
projects. Such partnerships can also assist fund education, social protection institutions, and vocational
training, resulting in a more comprehensive strategy to eliminating child labour.
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