IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i11p5046-d1668751.html

How Population Aging Drives Labor Productivity: Evidence from China

Author

Listed:
  • Chen Wu

    (School of Business, Nanjing University, Nanjing 210093, China)

  • Yang Cao

    (School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China)

  • Hao Xu

    (School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China)

Abstract

Population aging is a critical demographic trend in China, creating both challenges and opportunities for sustainable development. As aging alters the structure of the workforce and capital demand, understanding its effect on productivity is essential to managing demographic transitions in China. This study investigates the causal impact of population aging on labor productivity, with a focus on the mediating role of the capital–labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018, this paper employs industry- and year-fixed effects regression models to control for unobservable heterogeneity and conducts a formal causal mediation analysis. The analysis reveals that population aging significantly enhances labor productivity. Specifically, a one-percentage-point increase in the old-age dependency ratio is associated with a 1.47% increase in firm-level labor productivity. The capital–labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. Approximately 72.4% of the total effect is mediated through changes in capital intensity. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared with their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include (1) expanding targeted fiscal support for capital investment and automation in aging-intensive industries; (2) promoting vocational training programs tailored to older workers and digital skills development; and (3) strengthening infrastructure and institutional capacity in third-tier cities to better absorb productivity spillovers from demographic adjustment. By addressing these demographic and productivity linkages, the study contributes to achieving Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 10 (Reduced Inequalities), by promoting inclusive productivity growth, enhancing industrial adaptation to demographic change, and reducing regional and skill-based disparities.These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies.

Suggested Citation

  • Chen Wu & Yang Cao & Hao Xu, 2025. "How Population Aging Drives Labor Productivity: Evidence from China," Sustainability, MDPI, vol. 17(11), pages 1-28, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:5046-:d:1668751
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/11/5046/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/11/5046/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mr. Anton Korinek & Mr. Martin Schindler & Joseph Stiglitz, 2021. "Technological Progress, Artificial Intelligence, and Inclusive Growth," IMF Working Papers 2021/166, International Monetary Fund.
    2. Tan, Youchao & Liu, Xiumei & Sun, Hanwen & Zeng, Cheng(Colin), 2022. "Population ageing, labour market rigidity and corporate innovation: Evidence from China," Research Policy, Elsevier, vol. 51(2).
    3. Chen Bai & Xiaoyan Lei, 2020. "New trends in population aging and challenges for China’s sustainable development," China Economic Journal, Taylor & Francis Journals, vol. 13(1), pages 3-23, January.
    4. Danhong Shen & Haimeng Liang & Wangfang Shi, 2023. "Rural Population Aging, Capital Deepening, and Agricultural Labor Productivity," Sustainability, MDPI, vol. 15(10), pages 1-12, May.
    5. Richard Blundell & Lorraine Dearden & Costas Meghir & Barbara Sianesi, 1999. "Human capital investment: the returns from education and training to the individual, the firm and the economy," Fiscal Studies, Institute for Fiscal Studies, vol. 20(1), pages 1-23, March.
    6. Robert J. Gordon, 2016. "Perspectives on The Rise and Fall of American Growth," American Economic Review, American Economic Association, vol. 106(5), pages 72-76, May.
    7. David E. Bloom & David Canning & Günther Fink, 2010. "Implications of population ageing for economic growth," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 26(4), pages 583-612, Winter.
    8. Walheer, Barnabé, 2021. "Labor productivity and technology heterogeneity," Journal of Macroeconomics, Elsevier, vol. 68(C).
    9. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    10. Guo, Lu & Xiao, Fang, 2024. "Digital economy, aging of the labor force, and employment transformation of migrant workers: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 84(C), pages 787-807.
    11. Bjuggren, Carl Magnus, 2018. "Employment protection and labor productivity," Journal of Public Economics, Elsevier, vol. 157(C), pages 138-157.
    12. Bound, John & Schoenbaum, Michael & Stinebrickner, Todd R. & Waidmann, Timothy, 1999. "The dynamic effects of health on the labor force transitions of older workers," Labour Economics, Elsevier, vol. 6(2), pages 179-202, June.
    13. Tamara Gajić & Larisa A. Minasyan & Marko D. Petrović & Victor A. Bakhtin & Anna V. Kaneeva & Narine L. Wiegel, 2023. "Travelers’ (in)Resilience to Environmental Risks Emphasized in the Media and Their Redirecting to Medical Destinations: Enhancing Sustainability," Sustainability, MDPI, vol. 15(21), pages 1-23, October.
    14. Giuseppe Carone, 2005. "Long-Term Labour Force Projections for the 25 EU Member States:A set of data for assessing the economic impact of ageing," Labor and Demography 0512006, University Library of Munich, Germany.
    15. Chang-Tai Hsieh & Peter J. Klenow, 2009. "Misallocation and Manufacturing TFP in China and India," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1403-1448.
    16. Lee, Jong-Wha & Song, Eunbi & Kwak, Do Won, 2020. "Aging labor, ICT capital, and productivity in Japan and Korea," Journal of the Japanese and International Economies, Elsevier, vol. 58(C).
    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. Yujia Tian & Fei Sha & Haohui Chi & Zheng Ji, 2025. "The Impact of Drug Price Reduction on Healthcare System Sustainability: A CGE Analysis of China’s Centralized Volume-Based Procurement Policy," Sustainability, MDPI, vol. 17(16), pages 1-17, August.

    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. Zhao, Xiang & Liu, Jiali, 2025. "The impact of digital infrastructure on labor productivity," Economic Analysis and Policy, Elsevier, vol. 86(C), pages 274-287.
    2. Zuo, Jingjing & Han, Lu & Wang, Wei, 2025. "Who is compressing the “dividends” of employees? Research on the impact of population aging on employee treatment," Emerging Markets Review, Elsevier, vol. 69(C).
    3. Alzate, David & Carranza, Eliana & Duran-Franch, Joana & Packard, Truman & Proffen, Celina, 2024. "How Regulations Impact the Labor Market: A Review of the Literatures on Product and Labor Market Regulations," IZA Discussion Papers 17536, IZA Network @ LISER.
    4. Mokyr, Joel, 2018. "The past and the future of innovation: Some lessons from economic history," Explorations in Economic History, Elsevier, vol. 69(C), pages 13-26.
    5. Sheng, Jichuan & Ding, Rui & Yang, Hongqiang, 2024. "Corporate green innovation in an aging population: Evidence from Chinese listed companies," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    6. Nicholas Crafts & Pieter Woltjer, 2021. "Growth Accounting In Economic History: Findings, Lessons And New Directions," Journal of Economic Surveys, Wiley Blackwell, vol. 35(3), pages 670-696, July.
    7. Li, Zeguang & Huang, Yuanbiao & Hou, Keqiang, 2024. "Impacts of population aging on bank loan portfolios: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 95(C).
    8. Fulvio Castellacci, 2023. "Innovation and social welfare: A new research agenda," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1156-1191, September.
    9. Qing Liu & Larry Qiu & Miaojie Yu, 2017. "Worker Training, Firm Productivity, and Trade Liberalization: Evidence from Chinese Firms," The Developing Economies, Institute of Developing Economies, vol. 55(3), pages 189-209, September.
    10. Emanuela Sirtori & Louis Colnot, 2020. "Assessing the impact of megatrends on regional industrial transformations," Working Papers 202001, CSIL Centre for Industrial Studies.
    11. Arthur JACOBS & Freddy HEYLEN, 2025. "Demographic change, secular stagnation, and inequality: automation as a blessing?," JODE - Journal of Demographic Economics, Cambridge University Press, vol. 91(4), pages 508-548, December.
    12. Daniel Gallardo‐Albarrán & Robert Inklaar, 2021. "The Role Of Capital And Productivity In Accounting For Income Differences Since 1913," Journal of Economic Surveys, Wiley Blackwell, vol. 35(3), pages 952-974, July.
    13. Xuan, Siyuan & Hu, Jun & Yin, Jinghua & Li, Yang & Peng, Jie, 2025. "The role of FinTech in shaping urban innovation: A study of financial markets from the perspective of the patent renewal model," Pacific-Basin Finance Journal, Elsevier, vol. 91(C).
    14. Zhongqi Deng & Yu Zhang & Ao Yu, 2020. "The New Economy in China: An Intercity Comparison," SAGE Open, , vol. 10(4), pages 21582440209, December.
    15. Chen, Shiyi & Li, Yunpeng & Sun, Qinzhu, 2025. "Population aging and innovation slowdown: Dual mechanisms of firm cost structure and consumption preference," Economic Modelling, Elsevier, vol. 150(C).
    16. Chaudhary,Sarur & Sharma,Siddharth, 2022. "The Impact of Lifting Firing Restrictions on Firms : Evidence from a State-Level Labor Law Amendment," Policy Research Working Paper Series 10039, The World Bank.
    17. Daniel Kahneman, 2018. "Comment on "Artificial Intelligence and Behavioral Economics"," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 608-610, National Bureau of Economic Research, Inc.
    18. Ayanda Hlatshwayo & Friedrich Kreuser & Carol Newman & John Rand, 2019. "Worker mobility and productivity spillovers: An emerging market perspective," WIDER Working Paper Series wp-2019-114, World Institute for Development Economic Research (UNU-WIDER).
    19. Alpysbayeva, Dinara & Vanormelingen, Stijn, 2022. "Labor market rigidities and misallocation: Evidence from a natural experiment," Labour Economics, Elsevier, vol. 78(C).
    20. Chen, Yaorui & Wang, Hua, 2025. "Firm perceptions of population aging and cross-regional investment decisions: Evidence from China," Finance Research Letters, Elsevier, vol. 85(PA).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:11:p:5046-:d:1668751. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.