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Sweeping It under the Rug: Household Chores and Misreporting of Child Labor

Author

Listed:
  • Eva Dziadula

    (University of Notre Dame)

  • Danice Guzmán

    (University of Notre Dame)

Abstract

We collect data on child labor in almost 3,000 Nepali households, and our analysis shows that estimates of child labor prevalence vary from 11.6% to 29% with the definition of child labor used. The variation comes from the number of hours worked and from which tasks are considered child labor. Furthermore, we use two different surveys during data collection. In the first, an adult (proxy) reports on the daily activities of each child in the household, and in the second, the children (direct) respond themselves. Proxy and direct responses are less likely to match when the definition includes time spent on household chores, which is typically underestimated for girls. We find that proxy reporting of whether the child worked in the past week is 5.5 percentage points lower than the direct reporting. Within households, misreporting is significantly more likely for girls than for boys. Across households, however, misreporting is associated with child's age, not gender. Furthermore, among girls misreporting is associated with the number of younger children at home. Our analysis helps explain why varying measures of child labor used in the literature yield different results.

Suggested Citation

  • Eva Dziadula & Danice Guzmán, 2020. "Sweeping It under the Rug: Household Chores and Misreporting of Child Labor," Economics Bulletin, AccessEcon, vol. 40(2), pages 901-905.
  • Handle: RePEc:ebl:ecbull:eb-20-00065
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    References listed on IDEAS

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    1. 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.
    2. Basu, Kaushik & Das, Sanghamitra & Dutta, Bhaskar, 2010. "Child labor and household wealth: Theory and empirical evidence of an inverted-U," Journal of Development Economics, Elsevier, vol. 91(1), pages 8-14, January.
    3. Levison, Deborah & Moe, Karine S. & Marie Knaul, Felicia, 2001. "Youth Education and Work in Mexico," World Development, Elsevier, vol. 29(1), pages 167-188, January.
    4. George Psacharopoulos, 1997. "Child labor versus educational attainment Some evidence from Latin America," Journal of Population Economics, Springer;European Society for Population Economics, vol. 10(4), pages 377-386.
    5. Ragui Assaad & Deborah Levison & Nadia Zibani, 2010. "The Effect of Domestic Work on Girls' Schooling: Evidence from Egypt," Feminist Economics, Taylor & Francis Journals, vol. 16(1), pages 79-128.
    6. Ranjan RAY & Geoffrey LANCASTER, 2005. "The impact of children's work on schooling: Multi-country evidence," International Labour Review, International Labour Organization, vol. 144(2), pages 189-210, June.
    7. Webbink, Ellen & Smits, Jeroen & de Jong, Eelke, 2012. "Hidden Child Labor: Determinants of Housework and Family Business Work of Children in 16 Developing Countries," World Development, Elsevier, vol. 40(3), pages 631-642.
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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. Lakdawala, Leah K. & Martínez Heredia, Diana & Vera-Cossio, Diego A., 2023. "The Impact of Expanding Worker Rights to Informal Workers Evidence from Child Labor Legislation," IDB Publications (Working Papers) 12705, Inter-American Development Bank.

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    More about this item

    Keywords

    child labor; survey methods; data collection;
    All these keywords.

    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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