IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i10p4318-d1652631.html
   My bibliography  Save this article

Economic Structural Adjustment Promoting Sustainable Growth in Shanghai: A Two-Decade Study (2004–2023)

Author

Listed:
  • Danjun Wang

    (School of Finance, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Yunqi Zhou

    (School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK)

  • Fengwei Wang

    (College of Surveying and Geo-Informatics, Tongji University, Shanghai 200092, China)

Abstract

This study investigates the structural transformation of Shanghai’s economy (2004–2023), analyzing the interplay between industrial shifts and sustainable growth. While prior work has focused on short-term trends or isolated sectors, we provide the first comprehensive analysis of Shanghai’s two-decade transition from manufacturing to services, leveraging annual nominal GDP data and three forecasting models (Autoregressive Integrated Moving Average model ARIMA, Support Vector Machine SVM, and Grey Model GM). Our findings reveal that the tertiary sector’s contribution surged from 50.8% to 75.2% of GDP, driven by finance, technology, and real estate, while the secondary sector declined to 24.6%. The autoregressive integrated moving average ARIMA(1,1) model outperformed alternatives (mean absolute percentage error 2.97%), projecting GDP growth to CNY 60,321.54 trillion by 2026. Crucially, we demonstrate that Shanghai’s structural evolution aligns with advanced urban economies (e.g., New York, Tokyo), yet retains distinct industrial resilience due to China’s dual-circulation policy. These results challenge assumptions about manufacturing decline, instead highlighting a rebalancing toward high-value-added sectors. The study contributes (1) a validated framework for forecasting urban GDP in policy-stabilized economies and (2) empirical evidence for prioritizing tertiary innovation in sustainable development strategies. Policymakers and researchers can leverage these insights to navigate trade-offs between growth, equity, and environmental goals in rapidly urbanizing regions.

Suggested Citation

  • Danjun Wang & Yunqi Zhou & Fengwei Wang, 2025. "Economic Structural Adjustment Promoting Sustainable Growth in Shanghai: A Two-Decade Study (2004–2023)," Sustainability, MDPI, vol. 17(10), pages 1-17, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4318-:d:1652631
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/10/4318/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/10/4318/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Holz, Carsten A., 2008. "China's Economic Growth 1978-2025: What We Know Today About China's Economic Growth Tomorrow," World Development, Elsevier, vol. 36(10), pages 1665-1691, October.
    2. Weicheng Xu & Meng Wang, 2024. "How Do Financial Development and Industrial Structure Affect Green Total Factor Energy Efficiency: Evidence from China," Energies, MDPI, vol. 17(2), pages 1-26, January.
    3. World Bank, 2021. "The Changing Wealth of Nations 2021," World Bank Publications - Books, The World Bank Group, number 36400, April.
    4. Zhiwei Liu & Yonglei Fang & Lei Ma, 2022. "A Study on the Impact of Population Age Structure Change on Economic Growth in China," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    5. Jena, Pradyot Ranjan & Majhi, Ritanjali & Kalli, Rajesh & Managi, Shunsuke & Majhi, Babita, 2021. "Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 324-339.
    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. Danjun Wang & Zhanyang Zhang & Fengwei Wang & Xiaomeng Qiu, 2024. "Quantification of the short-term impact of economic shock events on the gross domestic product of 31 provinces in China from 2005 to 2022," SN Business & Economics, Springer, vol. 4(8), pages 1-22, August.
    2. Orietta Nicolis & Jean Paul Maidana & Fabian Contreras & Danilo Leal, 2024. "Analyzing the Impact of COVID-19 on Economic Sustainability: A Clustering Approach," Sustainability, MDPI, vol. 16(4), pages 1-30, February.
    3. Kaivo-oja, J. & Luukkanen, J. & Panula-Ontto, J. & Vehmas, J. & Chen, Y. & Mikkonen, S. & Auffermann, B., 2014. "Are structural change and modernisation leading to convergence in the CO2 economy? Decomposition analysis of China, EU and USA," Energy, Elsevier, vol. 72(C), pages 115-125.
    4. Zarnigor Dzhuraeva & James Okrah & Gulbahor N. Naziri, 2023. "The effect of COVID-19 restrictions (lockdown) on GDP growth in CIS countries," R-Economy, Ural Federal University, Graduate School of Economics and Management, vol. 9(4), pages 422-436.
    5. Lu, Ran & Xu, Wen & Zeng, Hongjun & Zhou, Xiangjing, 2023. "Volatility connectedness among the Indian equity and major commodity markets under the COVID-19 scenario," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1465-1481.
    6. Yothin Jinjarak & Ilan Noy & Quy Ta, 2022. "Pandemics and Economic Growth: Evidence from the 1968 H3N2 Influenza," Economics of Disasters and Climate Change, Springer, vol. 6(1), pages 73-93, March.
    7. Marina Yu. Malkina, 2021. "How the 2020 pandemic affected tax revenues in Russian regions?," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(2), pages 239-260, June.
    8. Tafreschi, Darjusch, 2015. "The income body weight gradients in the developing economy of China," Economics & Human Biology, Elsevier, vol. 16(C), pages 115-134.
    9. Michael Murach & Helmut Wagner, 2017. "How severe will the growth slowdown in China caused by the structural change be? An evaluation based on experiences from Japan and South Korea," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 15(3), pages 269-287, July.
    10. Segarra-Blasco, Agustí & Teruel, Mercedes & Cattaruzzo, Sebastiano, 2021. "The economic reaction to non-pharmaceutical interventions during Covid-19," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 592-608.
    11. Andrea Fracasso, 2015. "Economic Rebalancing and Growth: the Japanese experience and China’s prospects," DEM Discussion Papers 2015/07, Department of Economics and Management.
    12. Ling Tang & Qin Bao & ZhongXiang Zhang & Shouyang Wang, 2015. "Carbon-based border tax adjustments and China’s international trade: analysis based on a dynamic computable general equilibrium model," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(2), pages 329-360, April.
    13. Bonatti, Luigi & Fracasso, Andrea, 2013. "Regime switches in the Sino-American co-dependency: Growth and structural change in China," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 1-32.
    14. Christian Dreger & Daniel Gros, 2021. "Lockdowns and the US Unemployment Crisis," Economics of Disasters and Climate Change, Springer, vol. 5(3), pages 449-463, October.
    15. Bonatti, Luigi & Fracasso, Andrea, 2013. "Hoarding of international reserves in China: Mercantilism, domestic consumption and US monetary policy," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1044-1078.
    16. Murach, Michael & Wagner, Helmut, 2017. "How severe will the growth slowdown in China caused by the structural change be? – An evaluation based on experiences from Japan and South Korea," CEAMeS Discussion Paper Series 8/2017, University of Hagen, Center for East Asia Macro-economic Studies (CEAMeS).
    17. World Bank, 2024. "The Changing Wealth of Nations: Adding Water to the Changing Wealth of Nations," World Bank Publications - Reports 42356, The World Bank Group.
    18. Chandan Sharma & Ritesh Kumar Mishra, 2023. "The great lockdown, uncertainty and trade: asymmetric impact on imports," Empirical Economics, Springer, vol. 65(6), pages 2805-2836, December.
    19. Wang, Lili & Szirmai, Adam, 2008. "Regional Capital Inputs in Chinese Industry and Manufacturing, 1978-2003," MERIT Working Papers 2008-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    20. Bao, Qin & Tang, Ling & Zhang, ZhongXiang & Wang, Shouyang, 2013. "Impacts of border carbon adjustments on China's sectoral emissions: Simulations with a dynamic computable general equilibrium model," China Economic Review, Elsevier, vol. 24(C), pages 77-94.

    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:10:p:4318-:d:1652631. 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.