Full Citation

Title: New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data

Citation Type: Journal Article

Publication Year: 2022

ISBN:

ISSN: 0040-1625

DOI: 10.1016/J.TECHFORE.2021.121381

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PMID:

Abstract: We analyze heterogeneous effects of new digital technologies on individual-level wage and employment dynamics in the United States from 2011-2018. To this end, we employ four digital technology measures from recent literature: computerization probabilities of occupations, occupational impacts of artificial intelligence, and the suitability of tasks for machine learning and their within-occupation variance. Based on CPS and ASEC panel data, the results indicate that labor-displacing digital technologies are associated with slower wage growth and higher probabilities of switching one's occupation and becoming non-employed. In contrast, labor-reinstating digital technologies improve individual labor market outcomes. Workers with high levels of formal education are most affected by the new generation of digital technologies.

Url: https://scholar.google.com/scholar_url?url=https://www.sciencedirect.com/science/article/pii/S004016252100812X&hl=en&sa=X&d=7637080071576451861&ei=FQKxYemkI4GUy9YP3dGDuAQ&scisig=AAGBfm1r6-l34nFMJ2JAatToElrdE6Yzag&oi=scholaralrt&hist=SD6T3SsAAAAJ:537693993

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Authors: Fossen, Frank M.; Sorgner, Alina

Periodical (Full): Technological Forecasting and Social Change

Issue:

Volume: 175

Pages: 1-17

Data Collections: IPUMS CPS

Topics: Education, Labor Force and Occupational Structure, Poverty and Welfare

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