IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp5156.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp5156.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Eric V. Edmonds, 2005. "Does Child Labor Decline with Improving Economic Status?," Journal of Human Resources, University of Wisconsin Press, vol. 40(1).
    5. Margaret Grosh & Paul Glewwe, 2000. "Designing Household Survey Questionnaires for Developing Countries," World Bank Publications - Books, The World Bank Group, number 25338, December.
    6. Basu, Kaushik & Van, Pham Hoang, 1998. "The Economics of Child Labor," American Economic Review, American Economic Association, vol. 88(3), pages 412-427, June.
    7. 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).
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. André, Pierre & Delesalle, Esther & Dumas, Christelle, 2021. "Returns to farm child labor in Tanzania," World Development, Elsevier, vol. 138(C).
    6. Yonatan Dinku & David Fielding & Murat Genç, 2018. "Health shocks and child time allocation decisions by households: evidence from Ethiopia," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 7(1), pages 1-23, December.
    7. Del Carpio, Ximena V. & Loayza, Norman V. & Wada, Tomoko, 2016. "The Impact of Conditional Cash Transfers on the Amount and Type of Child Labor," World Development, Elsevier, vol. 80(C), pages 33-47.
    8. 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.
    9. Thakurata, Indrajit & D'Souza, Errol, 2018. "Child labour and human capital in developing countries - A multi-period stochastic model," Economic Modelling, Elsevier, vol. 69(C), pages 67-81.
    10. Vimefall, Elin, 2015. "Income diversification and working children," Working Papers 2015:8, Örebro University, School of Business.
    11. Oded STARK & Wiktor BUDZINSKI, 2023. "The demand for gratitude as a restraint on the use of child labor: A hypothesis," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 89(1), pages 137-147, March.
    12. Mauricio Moura & Rodrigo Bueno, 2014. "The Effect of Land Title on Child Labor Supply: Empirical Evidence from Brazil," Research in Labor Economics, in: Factors Affecting Worker Well-being: The Impact of Change in the Labor Market, volume 40, pages 195-222, Emerald Group Publishing Limited.
    13. Oryoie, Ali Reza & Alwang, Jeffrey & Tideman, Nicolaus, 2017. "Child Labor and Household Land Holding: Theory and Empirical Evidence from Zimbabwe," World Development, Elsevier, vol. 100(C), pages 45-58.
    14. Awaworyi Churchill, Sefa & Iqbal, Nasir & Nawaz, Saima & Yew, Siew Ling, 2021. "Unconditional cash transfers, child labour and education: theory and evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 437-457.
    15. Federico Tagliati, 2019. "Child labor under cash and in-kind transfers: evidence from rural Mexico," Working Papers 1935, Banco de España.
    16. 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.
    17. Vimefall, Elin, 2011. "What determines which children work? Empirical evidence from Kenya," Working Papers 2011:3, Örebro University, School of Business.
    18. Jorge Valero‐Gil & Magali Valero, 2022. "Why has there been a fall in child labour and an increase in school attendance in Mexico?," Development Policy Review, Overseas Development Institute, vol. 40(6), November.
    19. Harounan Kazianga & Francis Makamu, 2017. "Crop Choice, School Participation, and Child Labor in Developing Countries: Cotton Expansion in Burkina Faso," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(1), pages 34-54.
    20. Edmonds, Eric & Theoharides, Caroline, 2020. "The short term impact of a productive asset transfer in families with child labor: Experimental evidence from the Philippines," Journal of Development Economics, Elsevier, vol. 146(C).

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp5156. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.