Child Labor in Africa and Asia: Household and Context Determinants of Hours Worked in Paid Labor by Young Children in 16 Low-Income Countries

Webbink, Ellen; Smits, Jeroen; Jong, Eelke de

doi:10.1057/ejdr.2014.19

Cited by 13 publications

(6 citation statements)

References 36 publications

(41 reference statements)

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“…They do not use models but a weighted count. Webbink et al (2015) provide a Tobit model of working hours in paid work but do not critically differentiate child labour from child work. Giri and Singh (2016) attempt to count child labourers in India by integrating economic activities and domestic chores and including 'nowhere children' 4 ; they do not make use of models but multiply the ratio of child labourers by the population.…”

Section: Differentiation Separating Child Labour From Child Workmentioning

confidence: 99%

A Bayesian Estimation of Child Labour in India

2020

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Child labour in India involves the largest number of children in any single country in the world. In 2011, 11.8 million children between the ages of 5 and 17 were main workers (those working more than 6 mo) according to the Indian Census. Our estimate of child labour using a combined-data approach is slightly higher than that: 13.2 million (11.4–15.2 million) for ages 5 to 17. There are various opinions on how best to measure the prevalence of child labour. In this study, we use the International Labour Organization (ILO)‘s methodology to define hazardousness and combine it with the most recent United Nations Children’s Fund (UNICEF)‘s time thresholds for economic work and household chores. The specific aims of this study are to estimate the prevalence of child labour in the age group 5 to 17 and to suggest a combined-data approach using Bayesian inference to improve the accuracy of the child labour estimation. This study combines the National Sample Survey on Employment and Unemployment 2011/12 and the India Human Development Survey 2011/12 and compares the result with the reported figures for the incidence of child labour from the Indian Census. Our unique combined-data approach provides a way to improve accuracy, smooth the variations between ages and provide reliable estimates of the scale of child labour in India.

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Section: Differentiation Separating Child Labour From Child Workmentioning

confidence: 99%

A Bayesian Estimation of Child Labour in India

2020

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“…Emerson and Souza (2011) explored whether working as a child labourer is harmful to individual’s adult earnings and found that paid child labour is associated with lower adult earnings partly because of the inability of child labourer to attain a high level of education. Webbink et al (2015) drew attention to the number of hours a child engaged in paid labour and found that poverty and other household-level factors mainly affect the variation in the hours of paid child labour. Emerson and Souza (2003) examined whether there is the intergenerational persistence of paid child labour empirically and found that children are more likely to be child labourers if their parents are and less likely to be paid child labourers if their parents are well educated, suggesting that paid child labour might produce the chain of poverty over generations.…”

Section: Review Of Literaturementioning

confidence: 99%

“…Previous studies on paid child labour (e.g. Webbink et al , 2015) did not assume parental migration explicitly as another possible measure of poverty reduction. Similarly, those on parental migration (e.g.…”

Section: Research Gapmentioning

confidence: 99%

Parental migration, paid child labour, and human capital

Shimada

2017

IJSE

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Purpose Households suffering from poverty often rely on parental migration and/or paid child labour for survival. The purpose of this paper is to investigate the effects of parental migration on paid child labour and human capital formation in a dynamic context, explicitly taking the effects of parental migration on child’s school and home education into account. Design/methodology/approach The author utilises a mathematical method. In particular, an overlapping-generations model is built, with agents who have a two-period life. The amount of paid child labour is determined as a solution of the utility maximisation problem. Findings Contrary to intuition, parental migration possibilities do not necessarily reduce paid child labour. In addition, parental migration possibilities do not necessarily raise human capital. Moreover, a trade-off might exist between alleviating paid child labour and raising human capital under parental migration possibilities. Research limitations/implications Migration possibilities are given exogenously evenly among potential migrants by the foreign country. However, in general, they depend on potential migrants’ human capital so that migration possibilities differ across agents. Practical implications Migration is usually considered effective in alleviating poverty. However, since it does not necessarily reduce paid child labour and raise human capital, migration should be regulated in some cases as a means to escape from poverty. Originality/value This paper deals with parental migration and paid child labour in an identical dynamic model. This paper assumes that human capital is built not only by school education but also home education, the amount of which changes with the duration of parental migration.

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“…There have been several studies on child labor. Webbink et al (2015) studied the number of hours children in Africa and Asia were involved in paid child labor from data on 169,000 children living in 16 countries. They found variations in children's work hours to get wages, mainly due to household-level factors with poverty still a major driving factor.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, research on child labor has commonly utilized micro-data at the household level (Tang et al, 2018;Menon & Rodgers, 2018;Posso, 2017;Webbink et al, 2015;Ali & Arabsheibani, 2017). To the best of our knowledge, none of the previous studies has used macro-data for the case of Indonesia.…”

Section: Introductionmentioning

confidence: 99%

What Causes Children to Work in Indonesia?

Sandra¹,

Majid²,

Dawood³

et al. 2020

JAFEB

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This study contributes to the existing literature by empirically exploring the causes of child labor in the Indonesian labor market. Factors identified include rate of poverty, average wages, education participation, and quality of education. This study utilized an aggregate data of 301 districts and cities across 34 provinces sourced from the National Labor Force Survey and the National School/Madrasah Accreditation Board of the Republic of Indonesia. Using a multiple regression analysis, the study found strong evidence of the positive effect of poverty on child labor. Conversely, the study documented the adverse impact of average wages on child labor in Indonesia. Similarly, the participation in the education system also contributed negatively to the child labor. Finally, the quality of education services is found to have a negative effect on child labor in Indonesia. The findings of this study suggest that, in efforts to reduce the involvement of children in the workforce, the poverty eradication program should be enhanced. The wages should be continuously improved, at least, in par with the changes in prices. Finally, the quality of education and its services ought to be further enhanced to attract more child student participation rates across junior high schools nationwide.

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Child Labor in Africa and Asia: Household and Context Determinants of Hours Worked in Paid Labor by Young Children in 16 Low-Income Countries

Cited by 13 publications

References 36 publications

A Bayesian Estimation of Child Labour in India

A Bayesian Estimation of Child Labour in India

Parental migration, paid child labour, and human capital

What Causes Children to Work in Indonesia?

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