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Are female employment statistics more sensitive than male ones to questionnaire design? Evidence from Cameroon, Mali and Senegal

Author

Listed:
  • Virginie Comblon

    () (Universite Paris-Dauphine, PSL Research University, IRD, LEDa, DIAL, 75016 PARIS, FRANCE)

  • Anne-Sophie Robilliard

    () (IRD, LEDa, DIAL UMR 225, 75010 Paris, France)

Abstract

This paper investigates the effect of several survey questionnaire characteristics on employment statistics. It also assess the differences in sensitivity to survey design across gender and living area. Indeed, as suggested in the literature, women, especially those living in rural areas, are expected to be more sensitive than men to survey design, due to both the nature of the work (seasonal, occasional, temporary, informal, unpaid family work) and social norms. In many African countries, labor force surveys are not available on a regular basis and the way existing household surveys and census measure employment differs greatly, both over time and between countries. This makes it difficult to properly study labor market dynamics and to draw meaningful policy recommendations. Using about fifty surveys and censuses collected in Cameroon, Mali and Senegal between 1976 and 2012, we first review the diversity of survey instruments used and highlight the key questionnaire characteristics that are likely to affect employment statistics. Exploiting within-survey variations of the wording of questions, the detail of the labor module and the length of the reference period, we then assess the effect of these features on labor statistics. Empirical results shows significant effects of each questionnaire feature and suggest that women are not systematically more sensitive than men to survey design, nor is it the case for rural individuals compared to urban ones.

Suggested Citation

  • 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).
  • Handle: RePEc:dia:wpaper:dt201522
    as

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    File URL: http://www.dial.ird.fr/media/ird-sites-d-unites-de-recherche/dial/documents/publications/doc_travail/2015/2015-22
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    References listed on IDEAS

    as
    1. 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.
    2. repec:ilo:ilowps:343981 is not listed on IDEAS
    3. 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.
    4. Ray Langsten & Rania Salen, 2008. "Two Approaches to Measuring Women's Work in Developing Countries: A Comparison of Survey Data from Egypt," Population and Development Review, The Population Council, Inc., vol. 34(2), pages 283-305, June.
    5. 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.
    6. repec:dau:papers:123456789/10921 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Calvo, Thomas & Razafindrakoto, Mireille & Roubaud, François, 2019. "Fear of the state in governance surveys? Empirical evidence from African countries," World Development, Elsevier, vol. 123(C), pages 1-1.
    2. Kilic,Talip & Van den Broeck,Goedele & Koolwal,Gayatri B. & Moylan,Heather G., 2020. "Are You Being Asked ? Impacts of Respondent Selection on Measuring Employment," Policy Research Working Paper Series 9152, The World Bank.

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    More about this item

    Keywords

    Employment statistics; Survey design; Gender; Data comparability; Sub-Saharan Africa;
    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
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
    • O55 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Africa

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