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Explaining Variation in Child Labor Statistics

Author

Listed:
  • Dillon, Andrew

    (Michigan State University)

  • Bardasi, Elena

    (World Bank)

  • Beegle, Kathleen

    (World Bank)

  • Serneels, Pieter

    (University of East Anglia)

Abstract

Child labor statistics are critical for assessing the extent and nature of child labor activities in developing countries. In practice, widespread variation exists in how child labor is measured. Questionnaire modules vary across countries and within countries over time along several dimensions, including respondent type and the structure of the questionnaire. Little is known about the effect of these differences on child labor statistics. This paper presents the results from a randomized survey experiment in Tanzania focusing on two survey aspects: different questionnaire design to classify children work and proxy response versus self-reporting. Use of a short module compared with a more detailed questionnaire has a statistically significant effect, especially on child labor force participation rates, and, to a lesser extent, on working hours. Proxy reports do not differ significantly from a child’s self-report. Further analysis demonstrates that survey design choices affect the coefficient estimates of some determinants of child labor in a child labor supply equation. The results suggest that low-cost changes to questionnaire design to clarify the concept of work for respondents can improve the data collected.

Suggested Citation

  • Dillon, Andrew & Bardasi, Elena & Beegle, Kathleen & Serneels, Pieter, 2010. "Explaining Variation in Child Labor Statistics," IZA Discussion Papers 5156, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp5156
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    References listed on IDEAS

    as
    1. Sonia Bhalotra & Christopher Heady, 2003. "Child Farm Labor: The Wealth Paradox," The World Bank Economic Review, World Bank, vol. 17(2), pages 197-227, December.
    2. Eric V. Edmonds, 2005. "Does Child Labor Decline with Improving Economic Status?," Journal of Human Resources, University of Wisconsin Press, vol. 40(1).
    3. Basu, Kaushik & Van, Pham Hoang, 1998. "The Economics of Child Labor," American Economic Review, American Economic Association, vol. 88(3), pages 412-427, June.
    4. 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).
    5. Bardasi, Elena & Beegle, Kathleen & Dillon, Andrew & Serneels, Pieter, 2010. "Do labor statistics depend on how and to whom the questions are asked ? results from a survey experiment in Tanzania," Policy Research Working Paper Series 5192, The World Bank.
    6. Andrew Dillon, 2010. "Measuring child labor: comparisons between hours data and subjective measures," Research in Labor Economics, in: Child Labor and the Transition between School and Work, pages 135-159, Emerald Group Publishing Limited.
    7. Eric V. Edmonds & Norbert Schady, 2012. "Poverty Alleviation and Child Labor," American Economic Journal: Economic Policy, American Economic Association, vol. 4(4), pages 100-124, November.
    8. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries," World Bank Publications - Books, The World Bank Group, number 25338.
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    More about this item

    Keywords

    child labor; survey design; Tanzania;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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