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Child labour measurement: Whom should we ask?

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  • Sarah A. JANZEN

Abstract

Funding decisions to support vulnerable children are tied to child labour statistics, hence the importance of an accurate measurement. The author analyses whether the type of respondent plays an important role in explaining variations in child labour statistics. Using data from two sites in Tanzania, the analysis shows that “whom we ask” matters considerably when estimating the prevalence of child labour. The results suggest that prevalence increases by approximately 35 to 65 per cent when using child self‐reports rather than proxy reports. This bias affects 14 to 31 per cent of the sample, depending on the indicator. Discrepancies decrease as the child ages and increase if proxy attitudes demonstrate opposition to child labour.

Suggested Citation

  • Sarah A. JANZEN, 2018. "Child labour measurement: Whom should we ask?," International Labour Review, International Labour Organization, vol. 157(2), pages 169-191, June.
    • Handle: RePEc:bla:intlab:v:157:y:2018:i:2:p:169-191
    DOI: 10.1111/ilr.12041
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    References listed on IDEAS

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    1. Basu, Kaushik & Van, Pham Hoang, 1998. "The Economics of Child Labor," American Economic Review, American Economic Association, vol. 88(3), pages 412-427, June.
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    3. Dillon, Andrew & Bardasi, Elena & Beegle, Kathleen & Serneels, Pieter, 2012. "Explaining variation in child labor statistics," Journal of Development Economics, Elsevier, vol. 98(1), pages 136-147.
    4. Dammert, Ana C. & Galdo, Jose, 2013. "Child Labor Variation by Type of Respondent: Evidence from a Large-Scale Study," World Development, Elsevier, vol. 51(C), pages 207-220.
    5. L. Guarcello & I. Kovrova & S. Lyon & M. Manacorda & F. C. Rosati, 2010. "Towards consistency in child labour measurement: Assessing the comparability of estimates generated by different survey instruments," UCW Working Paper 54, Understanding Children's Work (UCW Programme).
    6. Duryea, Suzanne & Lam, David & Levison, Deborah, 2007. "Effects of economic shocks on children's employment and schooling in Brazil," Journal of Development Economics, Elsevier, vol. 84(1), pages 188-214, September.
    7. Jean-Marie Baland & James A. Robinson, 2000. "Is Child Labor Inefficient?," Journal of Political Economy, University of Chicago Press, vol. 108(4), pages 663-679, August.
    8. Beegle, Kathleen & Dehejia, Rajeev H. & Gatti, Roberta, 2006. "Child labor and agricultural shocks," Journal of Development Economics, Elsevier, vol. 81(1), pages 80-96, October.
    9. Richard ANKER, 2000. "The economics of child labour: A framework for measurement," International Labour Review, International Labour Organization, vol. 139(3), pages 257-280, September.
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    Cited by:

    1. Nicola S. Pocock & Clara W. Chan & Cathy Zimmerman, 2021. "Suitability of Measurement Tools for Assessing the Prevalence of Child Domestic Work: A Rapid Systematic Review," IJERPH, MDPI, vol. 18(5), pages 1-20, February.
    2. André, Pierre & Delesalle, Esther & Dumas, Christelle, 2021. "Returns to farm child labor in Tanzania," World Development, Elsevier, vol. 138(C).
    3. Marine JOUVIN, 2021. "Addressing social desirability bias in child labor measurement : an application to cocoa farms in Côte d’Ivoire," Bordeaux Economics Working Papers 2021-08, Bordeaux School of Economics (BSE).
    4. Sophie Hedges & David W. Lawson & Jim Todd & Mark Urassa & Rebecca Sear, 2019. "Sharing the Load: How Do Coresident Children Influence the Allocation of Work and Schooling in Northwestern Tanzania?," Demography, Springer;Population Association of America (PAA), vol. 56(5), pages 1931-1956, October.
    5. Jose Galdo & Ana C Dammert & Degnet Abebaw, 2021. "Gender Bias in Agricultural Child Labor: Evidence from Survey Design Experiments," The World Bank Economic Review, World Bank, vol. 35(4), pages 872-891.
    6. Andika Wahab & Ramli Dollah, 2023. "Measuring Child Labor in Oil Palm Production in Sabah, Malaysia," SAGE Open, , vol. 13(4), pages 21582440231, October.

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