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Within-Occupation Changes Dominate Changes in What Workers Do: A Shift-Share Decomposition, 2005–2015

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  • Richard B. Freeman
  • Ina Ganguli
  • Michael J. Handel

Abstract

This paper measures aggregate changes in job characteristics in the United States from 2005 to 2015 and decomposes those changes into components representing shifts within occupations and changes in occupational employment shares. Per our title, within-occupation changes dominate, raising doubts about the ability of projections based on expected changes in the occupational composition of employment to capture the likely future of work. Indeed, our data show only weak relationships between automatability, repetitiveness, and other job attributes and changes in occupational employment. The results suggest that analysts give greater attention to within-occupation impacts of technology in assessing the future of work.

Suggested Citation

  • Richard B. Freeman & Ina Ganguli & Michael J. Handel, 2020. "Within-Occupation Changes Dominate Changes in What Workers Do: A Shift-Share Decomposition, 2005–2015," AEA Papers and Proceedings, American Economic Association, vol. 110, pages 394-399, May.
    • Handle: RePEc:aea:apandp:v:110:y:2020:p:394-99
    DOI: 10.1257/pandp.20201005
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    Citations

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    Cited by:

    1. van der Velde, Lucas, 2022. "Phasing out: Routine tasks and retirement," Journal of Comparative Economics, Elsevier, vol. 50(3), pages 784-803.
    2. Belloni, Michele & Carrino, Ludovico & Meschi, Elena, 2022. "The impact of working conditions on mental health: Novel evidence from the UK," Labour Economics, Elsevier, vol. 76(C).
    3. Jeff Borland & Michael Coelli, 2023. "The Australian labour market and IT-enabled technological change," Melbourne Institute Working Paper Series wp2023n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    4. A. Cetrulo & D. Guarascio & M. E. Virgillito, 2022. "Working from home and the explosion of enduring divides: income, employment and safety risks," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 39(2), pages 345-402, July.
    5. Aksoy, Cevat Giray & Özcan, Berkay & Philipp, Julia, 2021. "Robots and the gender pay gap in Europe," European Economic Review, Elsevier, vol. 134(C).
    6. Christenko, Aleksandr, 2022. "Automation and occupational mobility: A task and knowledge-based approach," Technology in Society, Elsevier, vol. 70(C).
    7. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2022. "For whom the bell tolls: The firm-level effects of automation on wage and gender inequality," Research Policy, Elsevier, vol. 51(7).
    8. F Baum, Christopher & Lööf, Hans & Stephan, Andreas & F. Zimmermann, Klaus, 2020. "Productivity of refugee workers and implications for innovation and growth," Working Paper Series in Economics and Institutions of Innovation 485, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies, revised 24 Mar 2022.
    9. Alena Pauliková & Zdenka Gyurák Babeľová & Monika Ubárová, 2021. "Analysis of the Impact of Human–Cobot Collaborative Manufacturing Implementation on the Occupational Health and Safety and the Quality Requirements," IJERPH, MDPI, vol. 18(4), pages 1-15, February.
    10. Arntz, Melanie & Genz, Sabrina & Gregory, Terry & Lehmer, Florian & Zierahn-Weilage, Ulrich, 2024. "De-routinization in the fourth industrial revolution: Firm-level evidence," ZEW Discussion Papers 24-005, ZEW - Leibniz Centre for European Economic Research.
    11. Enrique Fernandez-Macias & Martina Bisello, 2020. "A Taxonomy of Tasks for Assessing the Impact of New Technologies on Work," JRC Working Papers on Labour, Education and Technology 2020-04, Joint Research Centre.
    12. Martina Bisello & Marta Fana & Enrique Fernández-Macías & Sergio Torrejón Pérez, 2021. "A comprehensive European database of tasks indices for socio-economic research," JRC Working Papers on Labour, Education and Technology 2021-04, Joint Research Centre.
    13. Fana Marta & Giangregorio Luca, 2021. "Routine-biased technical change can fail: Evidence from France," JRC Working Papers on Labour, Education and Technology 2021-14, Joint Research Centre.

    More about this item

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

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