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Measuring child labor: comparisons between hours data and subjective measures

In: Child Labor and the Transition between School and Work

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  • Andrew Dillon

Abstract

This chapter examines a subjective measure of child labor as an alternative to hours data for eliciting the distribution of children's time between work, school, and leisure. The subjective child labor questions that were developed have two primary advantages. First, the subjective measures avoid proxy respondent bias in child labor reports made by parents in a standard hours module. Second, the subjective child labor module scales responses to elicit the relative distribution of the shares of children's time without relying on hours data, which are prone to severe outlier problems. Adult, proxy respondents are found to produce uniformly lower reports of children's time allocated to work and school than the child's own subjective responses. Conditional labor supply functions are also estimated to examine differences in the marginal effects of child, parent, household, and school characteristics between the two types of data. The use of children's subjective responses increases the magnitude of the marginal effects for child's age, parental education, and school availability with limited differences between household composition and asset variables.

Suggested Citation

  • 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.
  • Handle: RePEc:eme:rleczz:s0147-9121(2010)0000031008
    DOI: 10.1108/S0147-9121(2010)0000031008
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    2. André, Pierre & Delesalle, Esther & Dumas, Christelle, 2021. "Returns to farm child labor in Tanzania," World Development, Elsevier, vol. 138(C).
    3. F. Blanco & C. A. Valdivia, 2006. "Child labour in Venezuela: children's vulnerability to macroeconomic shocks," UCW Working Paper 52, Understanding Children's Work (UCW Programme).
    4. 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.
    5. 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.
    6. 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).

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