A Bayesian Estimation of Child Labour in India

Jihye Kim (), Wendy Olsen () and Arkadiusz Wiśniowski ()
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Jihye Kim: University of Manchester
Wendy Olsen: University of Manchester
Arkadiusz Wiśniowski: University of Manchester

Child Indicators Research, 2020, vol. 13, issue 6, No 5, 1975-2001

Abstract: Abstract 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.

Keywords: Child labour; Bayesian estimation; Combining data; India; Time threshold (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s12187-020-09740-w

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