IDEAS home Printed from https://ideas.repec.org/p/wbk/wbrwps/5192.html

Do labor statistics depend on how and to whom the questions are asked ? results from a survey experiment in Tanzania

Author

Listed:
  • Bardasi, Elena
  • Beegle, Kathleen
  • Dillon, Andrew
  • Serneels, Pieter

Abstract

Labor market statistics are critical for assessing and understanding economic development. In practice, widespread variation exists in how labor statistics are measured in household surveys in low-income countries. Little is known whether these differences have an effect on the labor statistics they produce. This paper analyzes these effects by implementing a survey experiment in Tanzania that varied two key dimensions: the level of detail of the questions and the type of respondent. Significant differences are observed across survey designs with respect to different labor statistics. Labor force participation rates, for example, vary by as much as 10 percentage points across the four survey assignments. Using a short labor module without screening questions on employment generates lower female labor force participation and lower rates of wage employment for both men and women. Response by proxy rather than self-report yields lower male labor force participation, lower female working hours, and lower employment in agriculture for men. The differences between proxy and self reporting seem to come from information imperfections within the household, especially with the distance in age between respondent and subject playing an important role, while gender and educational differences seem less important.

Suggested Citation

  • 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.
  • Handle: RePEc:wbk:wbrwps:5192
    as

    Download full text from publisher

    File URL: http://www-wds.worldbank.org/external/default/WDSContentServer/WDSP/IB/2010/01/27/000158349_20100127140449/Rendered/PDF/WPS5192.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olivia Bertelli, 2020. "Investing in Agriculture when it is worth it. Empirical evidence from rural Uganda," Working Papers hal-02446820, HAL.
    2. Oya, Carlos., 2010. "Rural inequality, wage employment and labour market formation in Africa : historical and micro-level evidence," ILO Working Papers 994582213402676, International Labour Organization.
    3. Ugo Pica-Ciamarra & Derek Baker & Nancy Morgan & Alberto Zezza & Carlo Azzarri & Cheikh Ly & Longin Nsiima & Simplice Nouala & Patrick Okello & Joseph Sserugga, 2014. "Investing in the Livestock Sector : Why Good Numbers Matter, A Sourcebook for Decision Makers on How to Improve Livestock Data," World Bank Publications - Reports 17830, The World Bank Group.
    4. Olivia Bertelli, 2019. "Investing in agriculture when it is worth it. Evidence from rural Uganda," Working Papers DT/2019/05, DIAL (Développement, Institutions et Mondialisation).
    5. 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.
    6. Cheryl Doss, 2015. "Women and Agricultural Productivity: What Does the Evidence Tell Us?," Working Papers 1051, Economic Growth Center, Yale University.
    7. Alwang, Jeffrey & Larochelle, Catherine & Barrera, Victor, 2017. "Farm Decision Making and Gender: Results from a Randomized Experiment in Ecuador," World Development, Elsevier, vol. 92(C), pages 117-129.
    8. Vandercasteelen, Joachim & Dereje, Mekdim & Minten, Bart & Taffesse, Alemayehu Seyoum, 2016. "Row planting teff in Ethiopia: Impact on farm-level profitability and labor allocation," ESSP working papers 92, International Food Policy Research Institute (IFPRI).
    9. Burrone, Sara & Giannelli, Gianna Claudia, 2019. "Does Child Labor Lead to Vulnerable Employment in Adulthood? Evidence for Tanzania," IZA Discussion Papers 12162, Institute of Labor Economics (IZA).
    10. Duncan Chaplin & Arif Mamun & Thomas Fraker & Kathy Buek & Minki Chatterji & Denzel Hankinson, 2011. "Evaluation of Tanzania Energy Sector Project: Updated Design Report," Mathematica Policy Research Reports d946b658c7774742aeeec5d65, Mathematica Policy Research.
    11. Fox, Louise & Pimhidzai, Obert, 2013. "Different dreams, same bed : collecting, using, and interpreting employment statistics in Sub-Saharan Africa -- the case of Uganda," Policy Research Working Paper Series 6436, The World Bank.
    12. Palacios-Lopez, Amparo & Christiaensen, Luc & Kilic, Talip, 2017. "How much of the labor in African agriculture is provided by women?," Food Policy, Elsevier, vol. 67(C), pages 52-63.
    13. World Bank, 2012. "Uganda - Promoting Inclusive Growth : Transforming Farms, Human Capital, and Economic Geography, Synthesis Report," World Bank Publications - Reports 12655, The World Bank Group.
    14. Beegle, Kathleen & De Weerdt, Joachim & Friedman, Jed & Gibson, John, 2012. "Methods of household consumption measurement through surveys: Experimental results from Tanzania," Journal of Development Economics, Elsevier, vol. 98(1), pages 3-18.
    15. Bryceson, Deborah Fahy, 2019. "Gender and generational patterns of African deagrarianization: Evolving labour and land allocation in smallholder peasant household farming, 1980–2015," World Development, Elsevier, vol. 113(C), pages 60-72.
    16. Arthi, Vellore & Beegle, Kathleen & De Weerdt, Joachim & Palacios-López, Amparo, 2018. "Not your average job: Measuring farm labor in Tanzania," Journal of Development Economics, Elsevier, vol. 130(C), pages 160-172.
    17. Matteo Rizzo & Blandina Kilama & Marc Wuyts, 2015. "The Invisibility of Wage Employment in Statistics on the Informal Economy in Africa: Causes and Consequences," Journal of Development Studies, Taylor & Francis Journals, vol. 51(2), pages 149-161, February.
    18. Dervisevic, Ervin & Goldstein, Markus, 2021. "He Said, She Said: The Impact of Gender and Marriage Perceptions on Self and Proxy Reporting of Labor," 2021 Conference, August 17-31, 2021, Virtual 315396, International Association of Agricultural Economists.
    19. repec:ilo:ilowps:458221 is not listed on IDEAS
    20. Joachim Vandercasteelen & Mekdim Dereje & Bart Minten & Alemayehu Seyoum Taffesse, 2018. "Labour, profitability and gender impacts of adopting row planting in Ethiopia," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 45(4), pages 471-503.
    21. 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).
    22. repec:mpr:mprres:7138 is not listed on IDEAS
    23. Joachim Frick & Kristina Krell, 2011. "Einkommensmessungen in Haushaltspanelstudien für Deutschland: Ein Vergleich von EU-SILC und SOEP," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 5(3), pages 221-248, December.
    24. 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.
    25. repec:qeh:ophiwp:ophiwp072 is not listed on IDEAS

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • 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:wbk:wbrwps:5192. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Roula I. Yazigi (email available below). General contact details of provider: https://edirc.repec.org/data/dvewbus.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.