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The O*NET content model: strengths and limitations
[Stärken und Grenzen des O*NET-Models]

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  • Michael J. Handel

    (Northeastern University)

Abstract

This paper describes the Occupational Information Network (O*NET), a relatively recent database containing measures of occupational characteristics produced by the United States Department of Labor as a replacement for the Dictionary of Occupational Titles. O*NET scores cover cognitive, interpersonal, and physical skill requirements, as well as working conditions, and are derived mostly from survey responses of large, representative samples of workers. O*NET’s substantive scope and sampling are impressive, but there are also significant gaps and duplication in content. Underlying constructs, item wording, and response options are often vague or overly complex. However, O*NET items have generally sensible correlations with wages, which, along with the richness of the database, ensure O*NET’s place among researchers interested in work and labour markets.

Suggested Citation

  • Michael J. Handel, 2016. "The O*NET content model: strengths and limitations [Stärken und Grenzen des O*NET-Models]," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 49(2), pages 157-176, October.
    • Handle: RePEc:spr:jlabrs:v:49:y:2016:i:2:d:10.1007_s12651-016-0199-8
    DOI: 10.1007/s12651-016-0199-8
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    6. Nikolova, Milena & Lepinteur, Anthony & Cnossen, Femke, 2023. "Just Another Cog in the Machine? A Worker-Level View of Robotization and Tasks," IZA Discussion Papers 16610, Institute of Labor Economics (IZA).
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    8. G. Jacob Blackwood & Cindy Cunningham & Matthew Dey & Lucia Foster & Cheryl Grim & John C. Haltiwanger & Rachel L. Nesbit & Sabrina Pabilonia & Jay Stewart & Cody Tuttle & Zoltan Wolf, 2023. "Opening the Black Box: Task and Skill Mix and Productivity Dispersion," NBER Chapters, in: Technology, Productivity, and Economic Growth, National Bureau of Economic Research, Inc.
    9. Chiarello, Filippo & Fantoni, Gualtiero & Hogarth, Terence & Giordano, Vito & Baltina, Liga & Spada, Irene, 2021. "Towards ESCO 4.0 – Is the European classification of skills in line with Industry 4.0? A text mining approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    10. Giuseppe De Arcangelis & Rama Dasi Mariani, 2019. "Multi-Country Tasks Measures: Beyond US-based Data and a Focus on Migration," Economics Bulletin, AccessEcon, vol. 39(3), pages 2155-2161.
    11. Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2021. "Labour-saving automation and occupational exposure: a text-similarity measure," DISCE - Quaderni del Dipartimento di Politica Economica dipe0021, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    12. Gottlieb, Charles & Grobovšek, Jan & Poschke, Markus & Saltiel, Fernando, 2021. "Working from home in developing countries," European Economic Review, Elsevier, vol. 133(C).
    13. Raimi, Daniel & Greenspon, Jacob, 2022. "Matching Geographies and Job Skills in the Energy Transition," RFF Working Paper Series 22-25, Resources for the Future.
    14. Parsons, Christopher & Reysenbach, Tyler & Wahba, Jackline, 2020. "Network Sorting and Labor Market Outcomes: Evidence from the Chaotic Dispersal of the Viet Kieu," IZA Discussion Papers 13952, Institute of Labor Economics (IZA).
    15. Fruehwirt, Wolfgang & Duckworth, Paul, 2021. "Towards better healthcare: What could and should be automated?," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    16. Christenko, Aleksandr, 2022. "Automation and occupational mobility: A task and knowledge-based approach," Technology in Society, Elsevier, vol. 70(C).
    17. Jacqueline Mosomi & Amy Thornton, 2022. "Physical proximity and occupational employment change by gender during the COVID-19 pandemic," WIDER Working Paper Series wp-2022-90, World Institute for Development Economic Research (UNU-WIDER).
    18. Eduard Storm, 2023. "On the measurement of tasks: does expert data get it right?," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-24, December.
    19. Chigusa Okamoto, 2019. "The effect of automation levels on US interstate migration," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 63(3), pages 519-539, December.

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