Occupational change : automation and reskilling risks

Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, May, 2020

Bibliographic Details
Main Author: Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology.
Other Authors: Erik Brynjolfsson.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2020
Subjects:
Online Access:https://hdl.handle.net/1721.1/128103
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author Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology.
author2 Erik Brynjolfsson.
author_facet Erik Brynjolfsson.
Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology.
author_sort Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology.
collection MIT
description Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, May, 2020
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spelling mit-1721.1/1281032023-01-16T15:09:33Z Occupational change : automation and reskilling risks Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology. Erik Brynjolfsson. Sloan School of Management. Sloan School of Management Sloan School of Management. Thesis: S.M. in Management Research, Massachusetts Institute of Technology, Sloan School of Management, May, 2020 Cataloged from the official PDF of thesis. Includes bibliographical references (pages 45-47). We derive a novel occupation-industry level panel of skill demands from the near-universe of tagged online job postings in the US for the last decade (2010-2018). We use this data to study how the skill demands of occupations have changed and how these changes affect the returns to skills. Low- and medium-wage occupations' skill demands changed more than those of high-wage ones. Thus, lower-wage workers face not only higher risks of technological displacement but also increased risks of reskilling in order to stay productive. We show that routine-biased technological change (RBTC) due to automation technologies such as ML can best explain these results, while skill-biased and (endogenously) directed technological change cannot. Technical skills, such as ML, Business, Software, and Data Skills have particularly high implied market values, as do Social Skills and Creativity. These therefore represent lucrative (re-)skill investment opportunities for workers, unlike writing and non-cognitive skills. Finally, there is significant heterogeneity in industry fixed effects with the Utilities, Mining, Management and IT Industries offering much higher returns than the Food and Retail industries, even after controlling for skills. by Sebastian Steffen. S.M. in Management Research S.M.inManagementResearch Massachusetts Institute of Technology, Sloan School of Management 2020-10-19T00:43:17Z 2020-10-19T00:43:17Z 2020 2020 Thesis https://hdl.handle.net/1721.1/128103 1200238355 eng MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided. http://dspace.mit.edu/handle/1721.1/7582 47 pages application/pdf Massachusetts Institute of Technology
spellingShingle Sloan School of Management.
Steffen, Sebastian(Scientist in business management)Massachusetts Institute of Technology.
Occupational change : automation and reskilling risks
title Occupational change : automation and reskilling risks
title_full Occupational change : automation and reskilling risks
title_fullStr Occupational change : automation and reskilling risks
title_full_unstemmed Occupational change : automation and reskilling risks
title_short Occupational change : automation and reskilling risks
title_sort occupational change automation and reskilling risks
topic Sloan School of Management.
url https://hdl.handle.net/1721.1/128103
work_keys_str_mv AT steffensebastianscientistinbusinessmanagementmassachusettsinstituteoftechnology occupationalchangeautomationandreskillingrisks