IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_10685.html
   My bibliography  Save this paper

Artificial Intelligence and Jobs: Evidence from US Commuting Zones

Author

Listed:
  • Alessandra Bonfiglioli
  • Rosario Crinò
  • Gino Gancia
  • Ioannis Papadakis

Abstract

We study the effect of Artificial Intelligence (AI) on employment across US commuting zones over the period 2000-2020. A simple model shows that AI can automate jobs or complement workers, and illustrates how to estimate its effect by exploiting variation in a novel measure of local exposure to AI: job growth in AI-related professions built from detailed occupational data. Using a shift-share instrument that combines industry-level AI adoption with local industry employment, we estimate robust negative effects of AI exposure on employment across commuting zones and time. We find that AI’s impact is different from other capital and technologies, and that it works through services more than manufacturing. Moreover, the employment effect is especially negative for low-skill and production workers, while it turns positive for workers at the top of the wage distribution. These results are consistent with the view that AI has contributed to the automation of jobs and to widen inequality.

Suggested Citation

  • Alessandra Bonfiglioli & Rosario Crinò & Gino Gancia & Ioannis Papadakis, 2023. "Artificial Intelligence and Jobs: Evidence from US Commuting Zones," CESifo Working Paper Series 10685, CESifo.
    • Handle: RePEc:ces:ceswps:_10685
    as

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10685.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2022. "Quasi-Experimental Shift-Share Research Designs," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 89(1), pages 181-213.
    2. Sotiris Blanas & Gino Gancia & Sang Yoon (Tim) Lee, 2019. "Who is afraid of machines?," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, vol. 34(100), pages 627-690.
    3. Rodrigo Ad~ao & Michal Koles'ar & Eduardo Morales, 2018. "Shift-Share Designs: Theory and Inference," Papers 1806.07928, arXiv.org, revised Aug 2019.
    4. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    5. Rodrigo Adão & Michal Kolesár & Eduardo Morales, 2019. "Shift-Share Designs: Theory and Inference," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 1949-2010.
    6. Gordon H. Hanson, 2021. "Immigration and Regional Specialization in AI," NBER Working Papers 28671, National Bureau of Economic Research, Inc.
    7. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    8. Jillian Grennan & Roni Michaely, 2020. "Artificial Intelligence and High-Skilled Work: Evidence from Analysts," Swiss Finance Institute Research Paper Series 20-84, Swiss Finance Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christina Gathmann & Felix Grimm & Erwin Winkler, 2024. "AI, Task Changes in Jobs, and Worker Reallocation," CESifo Working Paper Series 11585, CESifo.
    2. Albanesi, Stefania & Da Silva, António Dias & Jimeno, Juan F. & Lamo, Ana & Wabitsch, Alena, 2023. "New technologies and jobs in Europe," Working Paper Series 2831, European Central Bank.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mann, Katja & Pozzoli, Dario, 2024. "Robots and immigration," Journal of Economic Behavior & Organization, Elsevier, vol. 227(C).
    2. Hémous, David & Dechezleprêtre, Antoine & Olsen, Morten & Zanella, carlo, 2019. "Automating Labor: Evidence from Firm-level Patent Data," CEPR Discussion Papers 14249, C.E.P.R. Discussion Papers.
    3. Hyejin Kim, 2024. "The impact of robots on labor demand: evidence from job vacancy data in South Korea," Empirical Economics, Springer, vol. 67(3), pages 1185-1209, September.
    4. Brey, Björn, 2024. "The effect of recent technological change on US immigration policy," Journal of Economic Behavior & Organization, Elsevier, vol. 227(C).
    5. Stemmler, Henry, 2023. "Automated Deindustrialization: How Global Robotization Affects Emerging Economies—Evidence from Brazil," World Development, Elsevier, vol. 171(C).
    6. Zhu, Ruini & Yuan, Ye & Wang, Yaojing, 2024. "Love, health, and robots: Automation, migration, and family responses in rural China," China Economic Review, Elsevier, vol. 85(C).
    7. Chuan, A. & Zhang, W., 2021. "Non-College Occupations, Workplace Routinization, and the Gender Gap in College Enrollment," Cambridge Working Papers in Economics 2177, Faculty of Economics, University of Cambridge.
    8. Mattia Filomena & Matteo Picchio & Alessia Lo Turco, 2024. "Trade exposure, immigrants and workplace injuries," Working Papers 488, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Galle, Simon & Lorentzen, Linnea, 2024. "The unequal effects of trade and automation across local labor markets," Journal of International Economics, Elsevier, vol. 150(C).
    10. Faber, Marius, 2020. "Robots and reshoring: Evidence from Mexican labor markets," Journal of International Economics, Elsevier, vol. 127(C).
    11. Kirill Borusyak & Peter Hull & Xavier Jaravel, 2023. "Design-Based Identification with Formula Instruments: A Review," NBER Working Papers 31393, National Bureau of Economic Research, Inc.
    12. Liu, Chen & Ma, Xiao, 2018. "China's Export Surge and the New Margins of Trade," MPRA Paper 103970, University Library of Munich, Germany, revised Oct 2020.
    13. Biavaschi, Costanza & Facchini, Giovanni, 2020. "Immigrant Franchise and Immigration Policy: Evidence from the Progressive Era," IZA Discussion Papers 13195, Institute of Labor Economics (IZA).
    14. Matthieu Crozet & Laura Hering & Sandra Poncet, 2024. "Is There a Bright Side to the China Syndrome? Rising Export Opportunities and Life Satisfaction in China," The World Bank Economic Review, World Bank, vol. 38(4), pages 708-740.
    15. Singer, Gregor, 2024. "Complementary inputs and industrial development: can lower electricity prices improve energy efficiency?," LSE Research Online Documents on Economics 122365, London School of Economics and Political Science, LSE Library.
    16. Mertens, Matthias & Müller, Steffen & Neuschäffer, Georg, 2022. "Identifying rent-sharing using firms' energy input mix," IWH Discussion Papers 19/2022, Halle Institute for Economic Research (IWH).
    17. McNeil, Andrew & Luca, Davide & Lee, Neil, 2023. "The long shadow of local decline: Birthplace economic adversity and long-term individual outcomes in the UK," Journal of Urban Economics, Elsevier, vol. 136(C).
    18. Blanas, Sotiris & Oikonomou, Rigas, 2023. "COVID-induced economic uncertainty, tasks and occupational demand," Labour Economics, Elsevier, vol. 81(C).
    19. Cali,Massimiliano & Presidente,Giorgio, 2021. "Automation and Manufacturing Performance in a Developing Country," Policy Research Working Paper Series 9653, The World Bank.
    20. Kilian, Lutz & Zhou, Xiaoqing, 2024. "Heterogeneity in the pass-through from oil to gasoline prices: A new instrument for estimating the price elasticity of gasoline demand," Journal of Public Economics, Elsevier, vol. 232(C).

    More about this item

    Keywords

    artificial intelligence; automation; displacement; labor;
    All these keywords.

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_10685. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.