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Improving the Estimate of Trafficking in Human Beings and Modern Slavery by Integrating Data From ILO/Walk Free/IOM and UNODC

Author

Listed:
  • Sylvia Walby

    (University of London)

  • Brian Francis

    (Lancaster University)

Abstract

An improved global estimate of the amount of trafficking in human beings/modern slavery is produced. The paper develops the methodology for data to populate Indicator 16.2.2 in the UN SDGs, ‘the estimated number of victims of human trafficking per 100,000 population, by sex, age, and form of exploitation’. The improved estimate is constructed by integrating data from the International Labour Organization/Walk Free/International Organization for Migration (ILO/Walk Free/IOM) with administrative data from United Nations Organization on Drugs and Crime (UNODC) rather than from the Counter Trafficking Global Data Collaborative (CTDC). The data from the UNODC is more comprehensive and less volatile than that from the CTDC on registered victims of trafficking. The new estimate is more than 30% larger, increases the proportion of trafficking for purposes of sexual exploitation from 27 to 56%, and increases the proportion of victims of trafficking who are female from 54 to 64%. This has implications for the priorities for social and public policy for prevention and for the provision of services to mitigate harms.

Suggested Citation

  • Sylvia Walby & Brian Francis, 2025. "Improving the Estimate of Trafficking in Human Beings and Modern Slavery by Integrating Data From ILO/Walk Free/IOM and UNODC," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 176(2), pages 669-693, January.
    • Handle: RePEc:spr:soinre:v:176:y:2025:i:2:d:10.1007_s11205-024-03474-w
    DOI: 10.1007/s11205-024-03474-w
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    References listed on IDEAS

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    1. José-Miguel Bello y Villarino, 2021. "Measuring Corruption: A Critical Analysis of the Existing Datasets and Their Suitability for Diachronic Transnational Research," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 157(2), pages 709-747, September.
    2. Lax Chan & Bernard W. Silverman & Kyle Vincent, 2021. "Multiple Systems Estimation for Sparse Capture Data: Inferential Challenges When There Are Nonoverlapping Lists," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(535), pages 1297-1306, July.
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