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Technology, Vintage-Specific Human Capital, and Labor Displacement: Evidence from Linking Patents with Occupations

Author

Listed:
  • Leonid Kogan
  • Dimitris Papanikolaou
  • Lawrence D. W. Schmidt
  • Bryan Seegmiller

Abstract

We develop a measure of workers’ technology exposure that relies only on textual descriptions of patent documents and the tasks performed by workers in an occupation. Our measure appears to identify a combination of labor-saving innovations but also technologies that may require skills that incumbent workers lack. Using a panel of administrative data, we examine how subsequent worker earnings relate to workers’ technology exposure. We find that workers at both the bottom but also the top of the earnings distribution are displaced. Our interpretation is that low-paid workers are displaced as their tasks are automated while the highest-paid workers face lower earnings growth as some of their skills become obsolete. Our calibrated model fits these facts and emphasizes the importance of movements in skill quantities, not just skill prices, for the link between technology and inequality.

Suggested Citation

  • Leonid Kogan & Dimitris Papanikolaou & Lawrence D. W. Schmidt & Bryan Seegmiller, 2021. "Technology, Vintage-Specific Human Capital, and Labor Displacement: Evidence from Linking Patents with Occupations," NBER Working Papers 29552, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29552
    Note: CF EFG LS PR
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    Citations

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    Cited by:

    1. John Carter Braxton & Kyle F. Herkenhoff & Jonathan Rothbaum & Lawrence Schmidt, 2021. "Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter," Opportunity and Inclusive Growth Institute Working Papers 55, Federal Reserve Bank of Minneapolis.
    2. Tyna Eloundou & Sam Manning & Pamela Mishkin & Daniel Rock, 2023. "GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models," Papers 2303.10130, arXiv.org, revised Aug 2023.
    3. Benjamin Schneider & Hillary Vipond, 2023. "The Past and Future of Work: How History Can Inform the Age of Automation," CESifo Working Paper Series 10766, CESifo.
    4. Schneider, Benjamin & Vipond, Hillary, 2023. "The past and future of work: how history can inform the age of automation," Economic History Working Papers 119282, London School of Economics and Political Science, Department of Economic History.
    5. Fabio Montobbio & Jacopo Staccioli & Maria Enrica Virgillito & Marco Vivarelli, 2021. "Labour-saving automation and occupational exposure: a text-similarity measure," DISCE - Quaderni del Dipartimento di Politica Economica dipe0021, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    6. Barry, John W. & Campello, Murillo & Graham, John R. & Ma, Yueran, 2022. "Corporate flexibility in a time of crisis," Journal of Financial Economics, Elsevier, vol. 144(3), pages 780-806.
    7. Seegmiller, Bryan & Papanikolaou, Dimitris & Schmidt, Lawrence D.W., 2023. "Measuring document similarity with weighted averages of word embeddings," Explorations in Economic History, Elsevier, vol. 87(C).

    More about this item

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • N3 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy
    • N6 - Economic History - - Manufacturing and Construction
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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