Journal Article

New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data

Authors

  • Frank M. Fossen
  • Alina Sorgner
Publication Date

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.

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Info

JEL Classification
J22, J23, O33
DOI
10.1016/j.techfore.2021.121381

Key Words

  • artificial intelligence
  • digitalization
  • employment stability
  • Machine Learning
  • unemployment
  • wage dynamics