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Demographics and Automation

Author

Listed:
  • Daron Acemoglu

    (MIT and CIFAR)

  • Pascual Restrepo

    () (Boston University)

Abstract

We argue theoretically and document empirically that aging leads to greater (industrial) automation, and in particular, to more intensive use and development of robots. Using US data, we document that robots substitute for middle-aged workers (those between the ages of 36 and 55). We then show that demographic change—corresponding to an increasing ratio of older to middle-aged workers—is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across US commuting zones. We also provide evidence of more rapid development of automation technologies in coun- tries undergoing greater demographic change. Our directed technological change model further predicts that the induced adoption of automation technology should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation. Both of these predictions receive support from country-industry variation in the adoption of robots. Our model also implies that the productivity implications of aging are ambiguous when technology responds to demographic change, but we should expect produc- tivity to increase and labor share to decline relatively in industries that are most amenable to automation, and this is indeed the pattern we find in the data.

Suggested Citation

  • Daron Acemoglu & Pascual Restrepo, 2018. "Demographics and Automation," Boston University - Department of Economics - The Institute for Economic Development Working Papers Series dp-299, Boston University - Department of Economics.
    • Handle: RePEc:bos:iedwpr:dp-299
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    File URL: http://www.bu.edu/econ/files/2012/11/Demograhics-and-Automation.pdf
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    Cited by:

    1. Pietro Checcucci, 2019. "The Silver Innovation. Older workers characteristics and digitalisation of the economy," Working Papers 0040, ASTRIL - Associazione Studi e Ricerche Interdisciplinari sul Lavoro.
    2. Francisco Perez-Arce & Maria J. Prados & Tarra Kohli, 2018. "The Decline in the U.S. Labor Force Participation Rate," Working Papers wp385, University of Michigan, Michigan Retirement Research Center.
    3. Krenz, Astrid & Prettner, Klaus & Strulik, Holger, 2018. "Robots, reshoring, and the lot of low-skilled workers," Center for European, Governance and Economic Development Research Discussion Papers 351, University of Goettingen, Department of Economics.
    4. Gunes Arkadas Asik & Mohamed Ali Marouani & Michelle Marshalian & Ulas Karakoc, 2018. "Productivity, Structural Change and Skills Dynamics in Tunisia and Turkey," Working Papers 1269, Economic Research Forum, revised 10 Dec 2018.

    More about this item

    Keywords

    aging; automation; demographic change; economic growth; directed technological change; productivity; robots; tasks; technology;

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • 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
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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