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The Trade-Off Between Child Labor and Schooling: Influence of Social Labeling NGOs in Nepal

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  • Chakrabarty, Sayan
  • Grote, Ulrike
  • Lüchters, Guido

Abstract

Does the labeling of products which have been produced without any child laborers contribute to increased welfare of children? This paper presents some results of a survey in Nepal conducted to analyze which factors determine the probability of a child to work, and to examine the influence of non governmental organizations (NGOs) which are engaged in social labeling, on the incidence of child labor and child schooling. Data were obtained from interviews with 410 households of Kathmandu Valley in Nepal. The results of the econometric analysis show that the probability of child labor (i) decreases if the carpet industry has implemented a labeling program, (ii) decreases if the adult’s income increases (‘luxury axiom’), (iii) decreases if the head of the household is educated, (iv) increases with the age of the head of the household, and (v) is increased in the presence of more children (aged 5-14) in the household. It can also be shown that labeling NGOs have a significant positive influence on sending the ex-child laborers to school.

Suggested Citation

  • Chakrabarty, Sayan & Grote, Ulrike & Lüchters, Guido, 2006. "The Trade-Off Between Child Labor and Schooling: Influence of Social Labeling NGOs in Nepal," Discussion Papers 276266, University of Bonn, Center for Development Research (ZEF).
    • Handle: RePEc:ags:ubzefd:276266
    DOI: 10.22004/ag.econ.276266
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    References listed on IDEAS

    as
    1. Edmonds, Eric V. & Pavcnik, Nina, 2006. "International trade and child labor: Cross-country evidence," Journal of International Economics, Elsevier, vol. 68(1), pages 115-140, January.
    2. Drusilla K. Brown & Alan V. Deardorff & Robert M. Stern, 2009. "U.S. Trade and Other Policy Options and Programs to Deter Foreign Exploitation of Child Labor," World Scientific Book Chapters, in: Globalization And International Trade Policies, chapter 18, pages 689-743, World Scientific Publishing Co. Pte. Ltd..
    3. Jafarey, Saqib & Lahiri, Sajal, 2002. "Will trade sanctions reduce child labour?: The role of credit markets," Journal of Development Economics, Elsevier, vol. 68(1), pages 137-156, June.
    4. Ranjan, Priya, 1999. "An economic analysis of child labor," Economics Letters, Elsevier, vol. 64(1), pages 99-105, July.
    5. Mark R. Rosenzweig, 1982. "Educational Subsidy, Agricultural Development, and Fertility Change," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 97(1), pages 67-88.
    6. Ranjan Ray, 2000. "Analysis of child labour in Peru and Pakistan: A comparative study," Journal of Population Economics, Springer;European Society for Population Economics, vol. 13(1), pages 3-19.
    7. Ravallion, Martin & Wodon, Quentin, 2000. "Does Child Labour Displace Schooling? Evidence on Behavioural Responses to an Enrollment Subsidy," Economic Journal, Royal Economic Society, vol. 110(462), pages 158-175, March.
    8. repec:ucp:bknber:9780226740867 is not listed on IDEAS
    9. George Psacharopoulos & Harry Anthony Patrinos, 1997. "Family size, schooling and child labor in Peru - An empirical analysis," Journal of Population Economics, Springer;European Society for Population Economics, vol. 10(4), pages 387-405.
    10. Grote, Ulrike & Basu, Arnab K. & Weinhold, Diana, 1998. "Child Labor and the International Policy Debate - The Education/Child Labor Trade-Off and the Consequences of Trade Sanctions," Discussion Papers 279717, University of Bonn, Center for Development Research (ZEF).
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    Cited by:

    1. Doytch, Nadia & Thelen, Nina & Mendoza, Ronald U., 2014. "The impact of FDI on child labor: Insights from an empirical analysis of sectoral FDI data and case studies," Children and Youth Services Review, Elsevier, vol. 47(P2), pages 157-167.

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    More about this item

    Keywords

    Community/Rural/Urban Development; Consumer/Household Economics; Institutional and Behavioral Economics; Marketing;
    All these keywords.

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J81 - Labor and Demographic Economics - - Labor Standards - - - Working Conditions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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