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Online Labour Index 2020: New ways to measure the world's remote freelancing market

Author

Listed:
  • Fabian Stephany
  • Otto Kassi
  • Uma Rani
  • Vili Lehdonvirta

Abstract

The Online Labour Index (OLI) was launched in 2016 to measure the global utilisation of online freelance work at scale. Five years after its creation, the OLI has become a point of reference for scholars and policy experts investigating the online gig economy. As the market for online freelancing work matures, a high volume of data and new analytical tools allow us to revisit half a decade of online freelance monitoring and extend the index's scope to more dimensions of the global online freelancing market. In addition to measuring the utilisation of online labour across countries and occupations by tracking the number of projects and tasks posted on major English-language platforms, the new Online Labour Index 2020 (OLI 2020) also tracks Spanish- and Russian-language platforms, reveals changes over time in the geography of labour supply, and estimates female participation in the online gig economy. The rising popularity of software and tech work and the concentration of freelancers on the Indian subcontinent are examples of the insights that the OLI 2020 provides. The OLI 2020 delivers a more detailed picture of the world of online freelancing via an interactive online visualisation updated daily. It provides easy access to downloadable open data for policymakers, labour market researchers, and the general public (www.onlinelabourobservatory.org).

Suggested Citation

  • Fabian Stephany & Otto Kassi & Uma Rani & Vili Lehdonvirta, 2021. "Online Labour Index 2020: New ways to measure the world's remote freelancing market," Papers 2105.09148, arXiv.org, revised Jun 2021.
  • Handle: RePEc:arx:papers:2105.09148
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    References listed on IDEAS

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    8. Fabian Stephany & Michael Dunn & Steven Sawyer & Vili Lehdonvirta, 2020. "Distancing Bonus Or Downscaling Loss? The Changing Livelihood of Us Online Workers in Times of COVID‐19," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 111(3), pages 561-573, July.
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    Cited by:

    1. Fung, Esabella, 2023. "A machine learning approach for assessing labor supply to the online labor market," MPRA Paper 118844, University Library of Munich, Germany.
    2. Brooke, Sian & Rao, Aliya, 2024. "Designing for justice in freelancing: testing platform interventions to minimise discrimination in online labour markets," LSE Research Online Documents on Economics 122152, London School of Economics and Political Science, LSE Library.
    3. Stephany, Fabian & Teutloff, Ole, 2024. "What is the price of a skill? The value of complementarity," Research Policy, Elsevier, vol. 53(1).
    4. Nwaobi, Godwin, 2024. "Gig Sector in the African Economy: Frameworks, Challenges and Prospects," MPRA Paper 120532, University Library of Munich, Germany.
    5. Fietz, Katharina & Lay, Jann, 2023. "Digitalisation and labour markets in developing countries," GIGA Working Papers 335, GIGA German Institute of Global and Area Studies.
    6. Evan Hurwitz & George Cevora, 2021. "Forecasting performance of workforce reskilling programmes," Papers 2107.10001, arXiv.org.
    7. Stephany, Fabian & Teutloff, Ole & Lehdonvirta, Vili, 2022. "What is the price of a skill? Revealing the complementary value of skills," MPRA Paper 114874, University Library of Munich, Germany.
    8. Saara Hämäläinen & Vaiva Petrikaitė, 2024. "Prediction algorithms in matching platforms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 78(3), pages 979-1020, November.

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