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Child Labor Variation by Type of Respondent: Evidence from a Large-Scale Study

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  • Dammert, Ana C.
  • Galdo, Jose

Abstract

This study uses a nationally representative survey to analyze a key survey design decision in child labor measurement: self-reporting versus proxy interviewing. The child/proxy disagreement affects 20% of the sample, which translates into a 17.1 percentage point difference in the national rate of child labor. Marginal effects from standard child labor supply functions show child/proxy differences, particularly when the household experienced negative shocks. We find that attitudes and social perceptions toward child labor are not related to the likelihood of disagreement. A modified bivariate choice model reports statistically significant probabilities of misclassification that range between 9% and 30%.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:wdevel:v:51:y:2013:i:c:p:207-220
    DOI: 10.1016/j.worlddev.2013.06.002
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    Cited by:

    1. 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.
    2. Dammert, Ana C. & de Hoop, Jacobus & Mvukiyehe, Eric & Rosati, Furio C., 2018. "Effects of public policy on child labor: Current knowledge, gaps, and implications for program design," World Development, Elsevier, vol. 110(C), pages 104-123.
    3. Deborah Levison & Deborah S. DeGraff & Esther W. Dungumaro, 2018. "Implications of Environmental Chores for Schooling: Children’s Time Fetching Water and Firewood in Tanzania," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 30(2), pages 217-234, April.
    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. Menon, Nidhiya & Rodgers, Yana van der Meulen, 2018. "Child labor and the minimum wage: Evidence from India," Journal of Comparative Economics, Elsevier, vol. 46(2), pages 480-494.
    6. Galdo, Jose C. & Dammert, Ana C. & Abebaw, Degnet, 2020. "Gender Bias in Agricultural Child Labor: Evidence from Survey Design Experiments," IZA Discussion Papers 13826, Institute of Labor Economics (IZA).
    7. Virginie Comblon & Anne-Sophie Robilliard, 2015. "Are female employment statistics more sensitive than male ones to questionnaire design? Evidence from Cameroon, Mali and Senegal," Working Papers DT/2015/22, DIAL (Développement, Institutions et Mondialisation).

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    More about this item

    Keywords

    child labor; self/proxy designs; maximum likelihood; survey design; Peru;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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