Peer-reviewed article
A Bayesian Estimation of Child Labour in India
Jihye Kim, Wendy Kay Olsen, Arkadiusz Wiśniowski ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study estimates the prevalence of child labour in India among children aged 5 to 17 years. Using a combined-data approach with Bayesian inference, the researchers analysed data from multiple national surveys and census records. Their estimate of 13.2 million children engaged in child labour is slightly higher than the 2011 Census figure of 11.8 million main workers. The study applies standardised definitions of hazardousness from the International Labour Organization and time thresholds from UNICEF to improve measurement accuracy.
Key points
- Estimated 13.2 million children aged 5–17 in India engaged in child labour (range: 11.4–15.2 million)
- This is higher than the 2011 Census figure of 11.8 million main workers
- Study combined National Sample Survey on Employment and Unemployment 2011/12 with India Human Development Survey 2011/12
- Applied ILO methodology for defining hazardousness and UNICEF time thresholds for economic work and household chores
- Bayesian combined-data approach helps smooth variations between ages and improve reliability of estimates
Limitations
This is a statistical estimation study that does not evaluate interventions or measure outcomes over time. It describes the scale of the problem at a single point in time (2011/12) and cannot tell us about the effectiveness of child labour prevention programmes or changes in child labour rates.
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.