IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i23p16093-d990683.html
   My bibliography  Save this article

How Population Aging Affects Industrial Structure Upgrading: Evidence from China

Author

Listed:
  • Xiao Shen

    (School of Business, Xinyang Normal University, Xinyang 464000, China)

  • Jingbo Liang

    (School of Business, Xinyang Normal University, Xinyang 464000, China)

  • Jiangning Cao

    (School of Business Administration, Zhongnan Uninersity of Economics and Law, Wuhan 430073, China)

  • Zhengwen Wang

    (School of Economics and Management, Wuhan University, Wuhan 430072, China
    National Institute of Insurance Development, Wuhan University, Ningbo 315100, China)

Abstract

The question of how to proactively respond to population aging has become a major global issue. As a country with the largest elderly population in the world, China suffers a stronger shock from population aging, which makes it more urgent to transform its industrial and economic development model. Concretely, in the context of the new macroeconomic environment that has undergone profound changes, the shock of population aging makes the traditional industrial structure upgrading model (driven by large-scale factor inputs, imitation innovation and low-cost technological progress, and strong external demand) more unsustainable, and China has an urgent need to transform it to a more sustainable one. Only with an in-depth analysis of the influence mechanism of population aging on the upgrading of industrial structure can we better promote industrial structure upgrading under the impact of population aging. Therefore, six MSVAR models were constructed from each environmental perspective based on data from 1987 to 2021. The probabilities of regime transition figures show that the influencing mechanisms have a clear two-regime feature from any view; specifically, the omnidirectional environmental transition occurs in 2019. A further impulse–response analysis shows that, comparatively speaking, under the new environment regime the acceleration of population aging (1) aggravates the labor shortage, thus narrowing the industrial structure upgrading ranges; (2) has a negative, rather than positive, impact on the capital stock, but leads to a cumulative increase in industrial structure upgrading; (3) forces weaker technological progress, but further leads to a stronger impact on the industrial structure upgrading; (4) forces greater consumption upgrading, which further weakens industrial structure upgrading; (5) narrows rather than expands the upgrading of investment and industrial structures; and (6) narrows the upgrading of export and industrial structures. Therefore, we should collaboratively promote industrial structure upgrading from the supply side relying heavily on independent innovation and talent, and the demand side relying heavily on the upgrading of domestic consumption and exports.

Suggested Citation

  • Xiao Shen & Jingbo Liang & Jiangning Cao & Zhengwen Wang, 2022. "How Population Aging Affects Industrial Structure Upgrading: Evidence from China," IJERPH, MDPI, vol. 19(23), pages 1-23, December.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:16093-:d:990683
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/23/16093/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/23/16093/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fang Cai, 2020. "The Second Demographic Dividend as a Driver of China's Growth," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(5), pages 26-44, September.
    2. Fei Fan & Shangze Dai & Keke Zhang & Haiqian Ke, 2021. "Innovation agglomeration and urban hierarchy: evidence from Chinese cities," Applied Economics, Taylor & Francis Journals, vol. 53(54), pages 6300-6318, November.
    3. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    4. Lingchen Liu & Fan Wu & Huiying Tong & Cuihong Hao & Tingting Xie, 2021. "The Digital Divide and Active Aging in China," IJERPH, MDPI, vol. 18(23), pages 1-14, December.
    5. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2021. "The Adjustment of Labor Markets to Robots [“Skills, Tasks and Technologies: Implications for Employment and Earnings]," Journal of the European Economic Association, European Economic Association, vol. 19(6), pages 3104-3153.
    6. 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.
    7. Cai, Jie & Stoyanov, Andrey, 2016. "Population aging and comparative advantage," Journal of International Economics, Elsevier, vol. 102(C), pages 1-21.
    8. Peter Harasztosi & Attila Lindner, 2019. "Who Pays for the Minimum Wage?," American Economic Review, American Economic Association, vol. 109(8), pages 2693-2727, August.
    9. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    10. Wu, Feifei & Yang, Hongna & Gao, Bo & Gu, Yan, 2021. "Old, not yet rich? The impact of population aging on export upgrading in developing countries," China Economic Review, Elsevier, vol. 70(C).
    11. Francis Lwesya, 2022. "Integration into regional or global value chains and economic upgrading prospects: an analysis of the East African Community (EAC) bloc," Future Business Journal, Springer, vol. 8(1), pages 1-14, December.
    12. Kitao, Sagiri & Mikoshiba, Minamo, 2020. "Females, the elderly, and also males: Demographic aging and macroeconomy in Japan," Journal of the Japanese and International Economies, Elsevier, vol. 56(C).
    13. Goh, Soo Khoon & McNown, Robert & Wong, Koi Nyen, 2020. "Macroeconomic implications of population aging: Evidence from Japan," Journal of Asian Economics, Elsevier, vol. 68(C).
    14. Yingzhu Yang & Rong Zheng & Lexiang Zhao, 2021. "Population Aging, Health Investment and Economic Growth: Based on a Cross-Country Panel Data Analysis," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    15. Matteo Cervellati & Uwe Sunde, 2005. "Human Capital Formation, Life Expectancy, and the Process of Development," American Economic Review, American Economic Association, vol. 95(5), pages 1653-1672, December.
    16. Ronald Lee & A. Mason & E. Amporfu & C.-B. An & L. R. Bixby & J. Bravo & M. Bucheli & Q. Chen & P. Comelatto & D. Coy & Hippolyte d'Albis & G. Donehower & L. Dramani & A. Furnkranz-Prskawetz & R. I. G, 2014. "Is low fertility really a problem? Population aging, dependency, and consumption," PSE-Ecole d'économie de Paris (Postprint) hal-01075298, HAL.
    17. Daron Acemoglu, 2007. "Equilibrium Bias of Technology," Econometrica, Econometric Society, vol. 75(5), pages 1371-1409, September.
    18. John Humphrey & Hubert Schmitz, 2002. "How does insertion in global value chains affect upgrading in industrial clusters?," Regional Studies, Taylor & Francis Journals, vol. 36(9), pages 1017-1027.
    19. Huimin Li & Jianyuan Huang & Jiayun Liu, 2022. "External Support for Elderly Care Social Enterprises in China: A Government-Society-Family Framework of Analysis," IJERPH, MDPI, vol. 19(14), pages 1-22, July.
    20. Wang, Xueli & Wang, Lei & Zhang, Xuerong & Fan, Fei, 2022. "The spatiotemporal evolution of COVID-19 in China and its impact on urban economic resilience," China Economic Review, Elsevier, vol. 74(C).
    21. Grigoli, Francesco & Koczan, Zsoka & Topalova, Petia, 2020. "Automation and labor force participation in advanced economies: Macro and micro evidence," European Economic Review, Elsevier, vol. 126(C).
    22. Meng Li & Kunrong Shen, 2013. "Population Aging and Housing Consumption: A Nonlinear Relationship in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 21(5), pages 60-77, September.
    23. Zhengwen Wang & Yunxiao Zong & Yuwan Dan & Shi-Jie Jiang, 2021. "Country risk and international trade: evidence from the China-B&R countries," Applied Economics Letters, Taylor & Francis Journals, vol. 28(20), pages 1784-1788, November.
    Full references (including those not matched with items on IDEAS)

    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. Wang, Linhui & Cao, Zhanglu & Dong, Zhiqing, 2023. "Are artificial intelligence dividends evenly distributed between profits and wages? Evidence from the private enterprise survey data in China," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 342-356.
    2. Bürgisser, Reto, 2023. "Policy Responses to Technological Change in the Workplace," SocArXiv kwxn2, Center for Open Science.
    3. Dennis C. Hutschenreiter & Tommaso Santini & Eugenia Vella, 2022. "Automation and sectoral reallocation," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 335-362, May.
    4. Genz, Sabrina & Schnabel, Claus, 2023. "Digitalization is not gender-neutral," Economics Letters, Elsevier, vol. 230(C).
    5. 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.
    6. Matthias Doepke & Anne Hannusch & Fabian Kindermann & Michèle Tertilt, 2022. "The Economics of Fertility: A New Era," NBER Working Papers 29948, National Bureau of Economic Research, Inc.
    7. Heyman, Fredrik & Olsson, Martin, 2022. "Long-Run Effects of Technological Change: The Impact of Automation and Robots on Intergenerational Mobility," Working Paper Series 1451, Research Institute of Industrial Economics, revised 29 Jun 2023.
    8. Andreas Baur & Lisandra Flach & Isabella Gourevich & Florian Unger, 2023. "North-South Trade: The Impact of Robotization," CESifo Working Paper Series 10865, CESifo.
    9. Casper Worm Hansen & Holger Strulik, 2017. "Life expectancy and education: evidence from the cardiovascular revolution," Journal of Economic Growth, Springer, vol. 22(4), pages 421-450, December.
    10. Davide Antonioli & Alberto Marzucchi & Francesco Rentocchini & Simone Vannuccini, 2022. "Robot Adoption and Innovation Activities (last revised: December 2023)," Munich Papers in Political Economy 21, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    11. Xu Dong & Yang Chen & Qinqin Zhuang & Yali Yang & Xiaomeng Zhao, 2022. "Agglomeration of Productive Services, Industrial Structure Upgrading and Green Total Factor Productivity: An Empirical Analysis Based on 68 Prefectural-Level-and-Above Cities in the Yellow River Basin," IJERPH, MDPI, vol. 19(18), pages 1-19, September.
    12. Kopecky, Joseph, 2023. "Population age structure and secular stagnation: Evidence from long run data," The Journal of the Economics of Ageing, Elsevier, vol. 24(C).
    13. Lili Yang & Ning Ma, 2022. "Empirical Study on the Influence of Urban Environmental Industrial Structure Optimization on Ecological Landscape Greening Construction," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    14. Belloc, Filippo & Burdin, Gabriel & Cattani, Luca & Ellis, William & Landini, Fabio, 2022. "Coevolution of job automation risk and workplace governance," Research Policy, Elsevier, vol. 51(3).
    15. Philipp Lergetporer & Katharina Wedel & Katharina Werner, 2023. "Automatability of occupations, workers’ labor-market expectations, and willingness to train," Munich Papers in Political Economy 32, Munich School of Politics and Public Policy and the School of Management at the Technical University of Munich.
    16. Kexu Wu & Zhiwei Tang & Longpeng Zhang, 2022. "Population Aging, Industrial Intelligence and Export Technology Complexity," Sustainability, MDPI, vol. 14(20), pages 1-24, October.
    17. David Autor & Caroline Chin & Anna M. Salomons & Bryan Seegmiller, 2022. "New Frontiers: The Origins and Content of New Work, 1940–2018," NBER Working Papers 30389, National Bureau of Economic Research, Inc.
    18. Henri Haapanala & Ive Marx & Zachary Parolin, 2023. "Robots and unions: The moderating effect of organized labour on technological unemployment," Economic and Industrial Democracy, Department of Economic History, Uppsala University, Sweden, vol. 44(3), pages 827-852, August.
    19. Dami'an Vergara, 2022. "Minimum Wages and Optimal Redistribution," Papers 2202.00839, arXiv.org, revised Dec 2022.
    20. Simone d’alessandro & Tiziano Distefano & Guilherme Spinato Morlin & Davide Villani, 2023. "Policy Responses to Labour-Saving Technologies: Basic Income, Job Guarantee, and Working Time Reduction," JRC Working Papers on Social Classes in the Digital Age 2023-09, Joint Research Centre.

    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:jijerp:v:19:y:2022:i:23:p:16093-:d:990683. 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.