• ISSN: 2301-3567 (Print), 2972-3981 (Online)
    • Abbreviated Title: J. Econ. Bus. Manag.
    • Frequency: Quarterly
    • DOI: 10.18178/JOEBM
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HOME > Archive > 2025 > Volume 13 Number 1 (2025) >
JOEBM 2025 Vol.13(1): 1-7
DOI: 10.18178/joebm.2025.13.1.839

Economic Implications of Aging Populations: A Multiple Regression Analysis of GDP in Shanghai and Beijing with Policy Recommendations

Jiaxu Dai
Malvern College Qingdao, Qingdao, Shandong, China
Email: 13863920385@163.com (J.X.D.)

Manuscript received November 5, 2024; revised December 14, 2024; accepted January 2, 2025; published January 20, 2025.

Abstract—An increasing body of research has begun to focus on the potential impact of an aging population on economic development, particularly in China. This country has experienced rapid economic growth due to its demographic dividend. Given this context, studying aging demographics in China has acquired a sense of urgency. This paper examines the implications of an aging population on China’s economy by analyzing data from 2011 to 2021 concerning GDP, aging population, public budgets, and large enterprise expenditures in Shanghai and Beijing. Utilizing multiple regression analysis, we find that in these two economically vibrant cities, an increase in the elderly population has a positive impact on GDP. We offer plausible explanations for this phenomenon and propose several practical solutions to address China’s aging population challenges. These findings not only provide valuable guidance for policymakers but also offer a new perspective on understanding the complex interplay between aging demographics and economic development.

Keywords—aging population, economic development, multiple regression analysis, policy recommendations

Cite: Jiaxu Dai, "Economic Implications of Aging Populations: A Multiple Regression Analysis of GDP in Shanghai and Beijing with Policy Recommendations," Journal of Economics, Business and Management, vol. 13, no. 1, pp. 1-7, 2025.

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

 

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