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How Does Population Aging Affect New Quality Productivity in Economic Sustainability? An Empirical Study Based on Mediating Mechanisms and Moderating Effects

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Listed:
  • Xiaowen Sha

    (Department of Global Business, Yeungnam University, Gyeongsan-si 38541, Gyeongsangbuk-do, Republic of Korea)

  • Boyang Li

    (Graduate School of Technology Management, Kyung Hee University, Yongin-si 17104, Gyeonggi-do, Republic of Korea)

  • Ziyu Zhao

    (Department of Mathematics, The University of Manchester, Manchester M13 9PL, UK)

  • Xiaosong Yin

    (Applied Physics & Applied Mathematics Department, Columbia University, New York, NY 10027, USA)

  • Jinyao Dong

    (School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore)

  • Yuhang Yang

    (Department of Computer Science, Faculty of Engineering, The University of Hong Kong, Hong Kong 999077, China)

  • Zhihao Xu

    (College of Computer Science and Technology, Qingdao University, Qingdao 266071, China)

Abstract

Population aging is increasingly recognized as a challenge to sustainable economic development, raising concerns about its impact on innovation and productivity. This study examines how population aging affects “new quality productivity” in China, using a balanced panel dataset of 30 provinces from 2011 to 2022. The analysis employs panel regression models with fixed effects and incorporates mediation and moderation approaches to explore underlying pathways. Land productivity is identified as a significant channel through which aging influences productivity, while the level of urbanization is examined as a moderating factor in this relationship. The results indicate that population aging significantly inhibits new quality productivity. Specifically, an aging population leads to lower land productivity, which hinders the growth of new quality productivity. However, higher urbanization is found to mitigate the adverse effect of aging on productivity. These findings are robust under various model specifications and statistical checks. In conclusion, the study underscores the necessity for proactive measures to mitigate the adverse effects of demographic aging. The findings provide policy insights, suggesting that boosting technological innovation, improving agricultural efficiency, and leveraging urbanization can help sustain high-quality development in the face of an aging population.

Suggested Citation

  • Xiaowen Sha & Boyang Li & Ziyu Zhao & Xiaosong Yin & Jinyao Dong & Yuhang Yang & Zhihao Xu, 2025. "How Does Population Aging Affect New Quality Productivity in Economic Sustainability? An Empirical Study Based on Mediating Mechanisms and Moderating Effects," Sustainability, MDPI, vol. 17(18), pages 1-23, September.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8249-:d:1749065
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    as
    1. James Gross & Yu Ouyang, 2021. "Types of urbanization and economic growth," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 25(1), pages 71-85, January.
    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. Edward L. Glaeser & Wentao Xiong, 2017. "Urban Productivity in the Developing World," NBER Working Papers 23279, National Bureau of Economic Research, Inc.
    4. 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.
    5. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    6. Cao, Jing & Ho, Mun S. & Hu, Wenhao & Jorgenson, Dale, 2020. "Effective labor supply and growth outlook in China," China Economic Review, Elsevier, vol. 61(C).
    7. Daron Acemoglu & Pascual Restrepo, 2017. "Secular Stagnation? The Effect of Aging on Economic Growth in the Age of Automation," American Economic Review, American Economic Association, vol. 107(5), pages 174-179, May.
    8. Costantini, Valeria & Mazzanti, Massimiliano, 2012. "On the green and innovative side of trade competitiveness? The impact of environmental policies and innovation on EU exports," Research Policy, Elsevier, vol. 41(1), pages 132-153.
    9. Dani Rodrik, 2016. "Premature deindustrialization," Journal of Economic Growth, Springer, vol. 21(1), pages 1-33, March.
    10. Beine, Michel & Docquier, Frederic & Rapoport, Hillel, 2001. "Brain drain and economic growth: theory and evidence," Journal of Development Economics, Elsevier, vol. 64(1), pages 275-289, February.
    11. Daniele Angelini, 2023. "Aging Population and Technology Adoption," Working Paper Series of the Department of Economics, University of Konstanz 2023-01, Department of Economics, University of Konstanz.
    12. Lyu, Yanwei & Xiao, Xuan & Zhang, Jinning, 2024. "Does the digital economy enhance green total factor productivity in China? The evidence from a national big data comprehensive pilot zone," Structural Change and Economic Dynamics, Elsevier, vol. 69(C), pages 183-196.
    13. Bruno Lanz & Simon Dietz & Tim Swanson, 2018. "Global Economic Growth and Agricultural Land Conversion under Uncertain Productivity Improvements in Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(2), pages 545-569.
    14. Lee, Chien-Chiang & He, Zhi-Wen & Yuan, Zihao, 2023. "A pathway to sustainable development: Digitization and green productivity," Energy Economics, Elsevier, vol. 124(C).
    15. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
    16. Guanchun Liu & Yuanyuan Liu & Chengsi Zhang, 2018. "Factor allocation, economic growth and unbalanced regional development in China," The World Economy, Wiley Blackwell, vol. 41(9), pages 2439-2463, September.
    17. Leora Friedberg, 2003. "The Impact of Technological Change on Older Workers: Evidence from Data on Computer Use," ILR Review, Cornell University, ILR School, vol. 56(3), pages 511-529, April.
    18. Jinlin Li & Litai Chen & Ying Chen & Jiawen He, 2022. "Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 616-629, April.
    19. Jules N. Pretty, 1997. "The sustainable intensification of agriculture," Natural Resources Forum, Blackwell Publishing, vol. 21(4), pages 247-256, November.
    20. Fusheng Xie & Nan Jiang & Xiaolu Kuang, 2025. "Towards an accurate understanding of ‘new quality productive forces’," Economic and Political Studies, Taylor & Francis Journals, vol. 13(1), pages 1-15, January.
    21. Edward L. Glaeser & Wentao Xiong, 2017. "Urban productivity in the developing world," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(3), pages 373-404.
    22. Ronald Lee & Andrew Mason, 2010. "Fertility, Human Capital, and Economic Growth over the Demographic Transition [Fécondité, capital humain et croissance économique au cours de la transition démographique]," European Journal of Population, Springer;European Association for Population Studies, vol. 26(2), pages 159-182, May.
    23. Lei Ding & Kingsley Haynes & Yanchun Liu, 2008. "Telecommunications infrastructure and regional income convergence in China: panel data approaches," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 42(4), pages 843-861, December.
    24. Ferguson, Ross & Wilkinson, William & Hill, Robert, 2000. "Electricity use and economic development," Energy Policy, Elsevier, vol. 28(13), pages 923-934, November.
    25. Luigi Guiso & Paola Sapienza & Luigi Zingales, 2008. "Trusting the Stock Market," Journal of Finance, American Finance Association, vol. 63(6), pages 2557-2600, December.
    26. Wolfgang Lutz & Warren Sanderson & Sergei Scherbov, 2008. "The coming acceleration of global population ageing," Nature, Nature, vol. 451(7179), pages 716-719, February.
    27. Chaozhu Li & Xiaoliang Li & Jiaxu Wang & Tianchu Feng, 2023. "Impacts of Aging Agricultural Labor Force on Land Transfer: An Empirical Analysis Based on the China Family Panel Studies," Land, MDPI, vol. 12(2), pages 1-15, January.
    28. Dan Ma & Kai Zhou & Jingwen Xu & Yihan Qian, 2023. "Industrial structure upgrading, population aging and migration: An empirical study based on Chinese provincial panel data," PLOS ONE, Public Library of Science, vol. 18(10), pages 1-17, October.
    29. Feder, Gershon, 1985. "The relation between farm size and farm productivity : The role of family labor, supervision and credit constraints," Journal of Development Economics, Elsevier, vol. 18(2-3), pages 297-313, August.
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