IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/74943.html
   My bibliography  Save this paper

Online Labour Index: Measuring the Online Gig Economy for Policy and Research

Author

Listed:
  • Kässi, Otto
  • Lehdonvirta, Vili

Abstract

Labour markets are thought to be in the midst of a dramatic transformation, where standard employment is increasingly supplemented or substituted by temporary gig work mediated by online platforms. Yet the scale and scope of these changes is hard to assess, because conventional labour market statistics and economic indicators are ill-suited to measuring online gig work. We present the Online Labour Index (OLI), a new economic indicator that provides the online gig economy equivalent of conventional labour market statistics. It measures the utilization of online labour across countries and occupations by tracking the number of projects and tasks posted on platforms in near-real time. We describe how the OLI is constructed and demonstrate how it can be used to address previously unanswered questions about the online gig economy; in particular, we show that the online gig economy grew at an annualized rate of 14 percent. To benefit policymakers, labour market researchers, and the general public, the index is available as an open data set and interactive online visualization, which are automatically updated daily

Suggested Citation

  • Kässi, Otto & Lehdonvirta, Vili, 2016. "Online Labour Index: Measuring the Online Gig Economy for Policy and Research," MPRA Paper 74943, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:74943
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/74943/1/MPRA_paper_74943.pdf
    File Function: original version
    Download Restriction: no
    File URL: https://mpra.ub.uni-muenchen.de/86627/8/MPRA_paper_86627.pdf
    File Function: revised version
    Download Restriction: no
    File URL: https://mpra.ub.uni-muenchen.de/88548/1/MPRA_paper_88548.pdf
    File Function: revised version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Ajay Agrawal & John Horton & Nicola Lacetera & Elizabeth Lyons, 2015. "Digitization and the Contract Labor Market: A Research Agenda," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 219-250, National Bureau of Economic Research, Inc.
    2. Diane Coyle, 2015. "Commentary: Modernising Economic Statistics: Why It Matters," National Institute Economic Review, National Institute of Economic and Social Research, vol. 234(1), pages 4-7, November.
    3. John Horton & William R. Kerr & Christopher Stanton, 2017. "Digital Labor Markets and Global Talent Flows," NBER Chapters, in: High-Skilled Migration to the United States and Its Economic Consequences, pages 71-108, National Bureau of Economic Research, Inc.
    4. David H. Autor & Michael J. Handel, 2013. "Putting Tasks to the Test: Human Capital, Job Tasks, and Wages," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 59-96.
    5. Aubert-Tarby, Clémence & Escobar, Octavio R. & Rayna, Thierry, 2018. "The impact of technological change on employment: The case of press digitisation," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 36-45.
    6. Lawrence F. Katz & Alan B. Krueger, 2016. "The Rise and Nature of Alternative Work Arrangements in the United States, 1995-2015," NBER Working Papers 22667, National Bureau of Economic Research, Inc.
    7. Siou Chew Kuek & Cecilia Paradi-Guilford & Toks Fayomi & Saori Imaizumi & Panos Ipeirotis & Patricia Pina & Manpreet Singh, 2015. "The Global Opportunity in Online Outsourcing," World Bank Publications - Reports 22284, The World Bank Group.
    8. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    9. Katharine G. Abraham & John C. Haltiwanger & Kristin Sandusky & James R. Spletzer, 2017. "Measuring the Gig Economy: Current Knowledge and Open Issues," NBER Chapters, in: Measuring and Accounting for Innovation in the Twenty-First Century, pages 257-298, National Bureau of Economic Research, Inc.
    10. Peter Elias, 1997. "Occupational Classification (ISCO-88): Concepts, Methods, Reliability, Validity and Cross-National Comparability," OECD Labour Market and Social Policy Occasional Papers 20, OECD Publishing.
    11. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    12. John J. Horton, 2017. "The Effects of Algorithmic Labor Market Recommendations: Evidence from a Field Experiment," Journal of Labor Economics, University of Chicago Press, vol. 35(2), pages 345-385.
    13. De Groen, Willem Pieter & Maselli, Ilaria, 2016. "The Impact of the Collaborative Economy on the Labour Market," CEPS Papers 11625, Centre for European Policy Studies.
    14. Alan S. Blinder & Alan B. Krueger, 2013. "Alternative Measures of Offshorability: A Survey Approach," Journal of Labor Economics, University of Chicago Press, vol. 31(S1), pages 97-128.
    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. Fabian Braesemann & Fabian Stephany & Ole Teutloff & Otto Kassi & Mark Graham & Vili Lehdonvirta, 2021. "The global polarisation of remote work," Papers 2108.13356, arXiv.org, revised Nov 2022.
    2. Braesemann, Fabian & Stephany, Fabian & Teutloff, Ole & Kässi, Otto & Graham, Mark & Lehdonvirta, Vili, 2021. "The polarisation of remote work," SocArXiv q8a96, Center for Open Science.
    3. Malo, Miguel & Cueto, Begoña, 2019. "Do old and new labour market risks overlap? Automation, offshorability, and non-standard employment," MPRA Paper 95058, University Library of Munich, Germany.
    4. Melia, Elvis, 2020. "African jobs in the digital era: Export options with a focus on online labour," IDOS Discussion Papers 3/2020, German Institute of Development and Sustainability (IDOS).
    5. Songul Tolan & Annarosa Pesole & Fernando Martinez-Plumed & Enrique Fernandez-Macias & José Hernandez-Orallo & Emilia Gomez, 2020. "Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks," JRC Working Papers on Labour, Education and Technology 2020-02, Joint Research Centre.
    6. Ljubica Nedelkoska & Frank Neffke, 2019. "Skill Mismatch and Skill Transferability: Review of Concepts and Measurements," Papers in Evolutionary Economic Geography (PEEG) 1921, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Jun 2019.
    7. repec:gdk:wpaper:66 is not listed on IDEAS
    8. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    9. Mourelatos, Evangelos, 2021. "Personality and Ethics on Online Labor Markets: How mood influences ethical perceptions," EconStor Preprints 244735, ZBW - Leibniz Information Centre for Economics.
    10. Evangelos Mourelatos & Manolis Tzagarakis, 2018. "An investigation of factors affecting the visits of online crowdsourcing and labor platforms," Netnomics, Springer, vol. 19(3), pages 95-130, December.
    11. Rani Uma & Furrer Marianne, 2019. "On-Demand Digital Economy: Can Experience Ensure Work and Income Security for Microtask Workers?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(3), pages 565-597, June.
    12. Otto Kassi & Vili Lehdonvirta & Fabian Stephany, 2021. "How Many Online Workers are there in the World? A Data-Driven Assessment," Papers 2103.12648, arXiv.org, revised Apr 2021.
    13. Maria Cesira Urzi Brancati & Annarosa Pesole & Enrique Fernandez Macias, 2019. "Digital Labour Platforms in Europe: Numbers, Profiles, and Employment Status of Platform Workers," JRC Research Reports JRC117330, Joint Research Centre.
    14. Azzellini, Dario & Greer, Ian & Umney, Charles, 2019. "Limits of the platform economy: Digitalization and marketization in live music," Working Paper Forschungsförderung 154, Hans-Böckler-Stiftung, Düsseldorf.
    15. André Cieplinski, 2017. "Employee Control, Work Content and Wages," Department of Economics University of Siena 775, Department of Economics, University of Siena.
    16. John Horton & William R. Kerr & Christopher Stanton, 2017. "Digital Labor Markets and Global Talent Flows," NBER Chapters, in: High-Skilled Migration to the United States and Its Economic Consequences, pages 71-108, National Bureau of Economic Research, Inc.
    17. Edouard Ribes, 2021. "Scoping the transformation of the professional services industry," Working Papers hal-01889350, HAL.
    18. Moshe A. Barach & Aseem Kaul & Ming D. Leung & Sibo Lu, 2019. "Strategic Redundancy in the Use of Big Data: Evidence from a Two-Sided Labor Market," Strategy Science, INFORMS, vol. 4(4), pages 298-322, December.
    19. Cristiano Codagnone & Fabienne Abadie & Federico Biagi, 2016. "The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation?," JRC Research Reports JRC101280, Joint Research Centre.
    20. repec:gdk:wpaper:51 is not listed on IDEAS
    21. Joshua Greenstein, 2020. "The Precariat Class Structure and Income Inequality among US Workers: 1980–2018," Review of Radical Political Economics, Union for Radical Political Economics, vol. 52(3), pages 447-469, September.
    22. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.

    More about this item

    Keywords

    online labour; online gig work; measurement of vacancies; web data collection; occupation prediction;
    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
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • J20 - Labor and Demographic Economics - - Demand and Supply of Labor - - - General
    • J40 - Labor and Demographic Economics - - Particular Labor Markets - - - General

    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:pra:mprapa:74943. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.