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Data and Code for “Within Occupation Changes Dominate Changes in What Workers Do: A Shift-Share Decomposition, 2005-2015”

Version
V0
Resource Type
Dataset
Creator
  • Freeman, Richard (Harvard University. Department of Economics)
  • Ganguli, Ina (University of Massachusetts-Amherst)
  • Handel, Michael (Northeastern University)
Publication Date
2020-09-15
Funding Reference
  • Alfred P. Sloan Foundation
    • Award Number: B-2017-9943-OWRR
  • IBM
    • Award Number: 7643026-01-1-1
Free Keywords
occupations; technological change; tasks; shift-share decomposition
Description
  • Abstract

    This paper measures aggregate changes in job characteristics in the U.S. 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.
Availability
Download
This study is freely available to the general public via web download.
Relations
  • Has version
    DOI: 10.3886/E120830V1
Publications
  • Freeman, Richard B., Ina Ganguli, and Michael J. Handel. “Within-Occupation Changes Dominate Changes in What Workers Do: A Shift-Share Decomposition, 2005–2015.” AEA Papers and Proceedings 110 (May 2020): 394–99. https://doi.org/10.1257/pandp.20201005.
    • ID: 10.1257/pandp.20201005 (DOI)

Update Metadata: 2020-09-15 | Issue Number: 1 | Registration Date: 2020-09-15

Freeman, Richard; Ganguli, Ina; Handel, Michael (2020): Data and Code for “Within Occupation Changes Dominate Changes in What Workers Do: A Shift-Share Decomposition, 2005-2015”. Version: V0. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E120830