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

Author

Listed:
  • Fossen, Frank M.

    (University of Nevada, Reno)

  • Sorgner, Alina

    (John Cabot University)

Abstract

We investigate heterogeneous effects of new digital technologies on the individual-level employment- and wage dynamics in the U.S. labor market in the period from 2011-2018. We employ three measures that reflect different aspects of impacts of new digital technologies on occupations. The first measure, as developed by Frey and Osborne (2017), assesses the computerization risk of occupations, the second measure, developed by Felten et al. (2018), provides an estimate of recent advances in artificial intelligence (AI), and the third measure assesses the suitability of occupations for machine learning (Brynjolfsson et al., 2018), which is a subfield of AI. Our empirical analysis is based on large representative panel data, the matched monthly Current Population Survey (CPS) and its Annual Social and Economic Supplement (ASEC). The results suggest that the effects of new digital technologies on employment stability and wage growth are already observable at the individual level. High computerization risk is associated with a high likelihood of switching one's occupation or becoming non-employed, as well as a decrease in wage growth. However, advances in AI are likely to improve an individual's job stability and wage growth. We further document that the effects are heterogeneous. In particular, individuals with high levels of formal education and older workers are most affected by new digital technologies.

Suggested Citation

  • Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp12242
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    Cited by:

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    2. Seamus McGuinness & Konstantinos Pouliakas & Paul Redmond, 2023. "Skills-displacing technological change and its impact on jobs: challenging technological alarmism?," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(3), pages 370-392, April.
    3. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the digital divide: Workers' exposure to digitalization and its consequences for individual employment," Discussion Papers 118, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Labour and Regional Economics.
    4. Fossen, Frank M. & Sorgner, Alina, 2021. "Digitalization of work and entry into entrepreneurship," Journal of Business Research, Elsevier, vol. 125(C), pages 548-563.
    5. Fossen, Frank M., 2019. "Entrepreneurship over the Business Cycle in the United States: A Decomposition," IZA Discussion Papers 12499, Institute of Labor Economics (IZA).
    6. Nazareno, Luísa & Schiff, Daniel S., 2021. "The impact of automation and artificial intelligence on worker well-being," Technology in Society, Elsevier, vol. 67(C).
    7. Duch-Brown, Néstor & Gomez-Herrera, Estrella & Mueller-Langer, Frank & Tolan, Songül, 2022. "Market power and artificial intelligence work on online labour markets," Research Policy, Elsevier, vol. 51(3).

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    More about this item

    Keywords

    digitalization; artificial intelligence; machine learning; employment stability; unemployment; wage dynamics;
    All these keywords.

    JEL classification:

    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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