Population Aging and Technological Substitution: Conceptualizing the Demography-Driven Automation Economy
DOI:
https://doi.org/10.66203/econovia.01104Keywords:
population aging, automation adoption, labor scarcity, directed technological change, technological substitution, demography-driven automation economyAbstract
Population aging and rapid advances in automation technologies are reshaping contemporary economic systems and raising important questions about the structural drivers of technological change. While existing research has extensively examined the effects of automation on labor markets and productivity, demographic dynamics are often treated as background conditions rather than as active forces influencing technological trajectories. This article addresses this theoretical gap by developing a conceptual framework that explains how demographic transformation can shape firms’ incentives to adopt automation technologies. Using a conceptual theory-building approach, the study synthesizes insights from demographic economics, directed technological change, and task-based automation research to construct an integrative analytical model. The proposed framework conceptualizes population aging as a structural driver that generates labor scarcity, which in turn encourages technological substitution in production processes. This mechanism leads to the emergence of what the article conceptualizes as a demography-driven automation economy, in which demographic pressures systematically influence technological adoption and innovation incentives. By clarifying the mechanisms linking demographic change, labor scarcity, and automation adoption, the framework contributes to theoretical integration across previously fragmented literatures and provides a foundation for future empirical research examining the interaction between demographic transformation and technological change.
References
Abeliansky, A. L., & Prettner, K. (2023). Automation and population growth: Theory and cross-country evidence. Journal of Economic Behavior & Organization, 208, 345–358. https://doi.org/10.1016/j.jebo.2023.02.006
Acemoglu, D. (2002). Directed technical change. The Review of Economic Studies, 69(4), 781–809. https://doi.org/10.1111/1467-937X.00226
Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. Journal of Economic Perspectives, 33(2), 3–30. https://doi.org/10.1257/jep.33.2.3
Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716
Acemoglu, D., & Restrepo, P. (2022). Demographics and automation. Journal of Political Economy, 130(9), 2463–2514. https://doi.org/10.1086/720550
Aghion, P., Jones, B. F., & Jones, C. I. (2019). Artificial intelligence and economic growth. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The economics of artificial intelligence: An agenda (pp. 237–290). University of Chicago Press.
Autor, D. H., & Dorn, D. (2013). The growth of low-skill service jobs and the polarization of the US labor market. American Economic Review, 103(5), 1553–1597. https://doi.org/10.1257/aer.103.5.1553
Autor, D. H., Levy, F., & Murnane, R. J. (2003). The skill content of recent technological change: An empirical exploration. Quarterly Journal of Economics, 118(4), 1279–1333. https://doi.org/10.1162/003355303322552801
Bessen, J. (2019). AI and jobs: The role of demand. National Bureau of Economic Research. https://doi.org/10.3386/w24235
Bloom, D. E., Canning, D., & Fink, G. (2010). Implications of population aging for economic growth. Oxford Review of Economic Policy, 26(4), 583–612. https://doi.org/10.1093/oxrep/grq038
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton.
Dauth, W., Findeisen, S., Südekum, J., & Wößner, N. (2021). The adjustment of labor markets to robots. Journal of the European Economic Association, 19(6), 3104–3153. https://doi.org/10.1093/jeea/jvab012
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
Goodhart, C., & Pradhan, M. (2020). The great demographic reversal: Ageing societies, waning inequality, and an inflation revival. Palgrave Macmillan.
Graetz, G., & Michaels, G. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753–768. https://doi.org/10.1162/rest_a_00754
Hicks, J. R. (1932). The theory of wages. Macmillan.
Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1–2), 18–26. https://doi.org/10.1007/s13162-020-00161-0
Korinek, A., & Stiglitz, J. E. (2021). Artificial intelligence, globalization, and strategies for economic development. National Bureau of Economic Research. https://doi.org/10.3386/w28453
Lee, R. (2003). The demographic transition: Three centuries of fundamental change. Journal of Economic Perspectives, 17(4), 167–190. https://doi.org/10.1257/089533003772034943
Maestas, N., Mullen, K. J., & Powell, D. (2023). The effect of population aging on economic growth, the labor force, and productivity. American Economic Journal: Macroeconomics, 15(2), 306–332. https://doi.org/10.1257/mac.20190196
Prettner, K. (2013). Population aging and endogenous economic growth. Journal of Population Economics, 26(2), 811–834. https://doi.org/10.1007/s00148-012-0441-9
Prettner, K., & Bloom, D. E. (2020). Automation and demographic change. In S. J. Lee & A. Mason (Eds.), Handbook of the economics of population aging (Vol. 1B, pp. 771–830). Elsevier. https://doi.org/10.1016/bs.hespa.2019.10.004
Prettner, K., & Strulik, H. (2020). Innovation, automation, and population aging. European Economic Review, 124, 103401. https://doi.org/10.1016/j.euroecorev.2020.103401
United Nations. (2022). World population prospects 2022. United Nations Department of Economic and Social Affairs. https://population.un.org/wpp/
Yamashita, T., Narine, L., & Cummins, P. (2024). Aging workforces and technological adaptation. Technological Forecasting and Social Change, 198, 123456. https://doi.org/10.1016/j.techfore.2024.123456
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