Cui Jinghang, Zhou Rong, Crandall K Jason, Cui Mingxuan, Bai Ruirui, Jia Yi
School of Sport and Physical Education, North University of China, Taiyuan, China.
Center for Applied Science in Health and Aging, Western Kentucky University, Bowling Green, KY, United States.
Front Public Health. 2025 Jan 21;12:1520834. doi: 10.3389/fpubh.2024.1520834. eCollection 2024.
With population aging, this demographic dividend diminishes, which may have implications for innovation in a region. Understanding the relationship between population aging and innovation is crucial for addressing economic challenges associated with an aging population.
This study utilized panel data on population aging and innovation from 252 cities between 2005 and 2014. Various estimation methods, including the fixed effects model, the generalized method of moments (GMM), and the mediation model, were used to analyze the data. These methods allowed for a comprehensive examination of the impact of population aging on innovation and the role of human capital in mediating this relationship.
The findings of the study indicate that both the 60-year-old and 65-year-old population significantly hinder innovation. The GMM suggests that innovation is "path dependent," meaning that past levels of innovation do not alleviate the negative effects of population aging on future innovation. Additionally, the mediation model analysis demonstrates that human capital plays a crucial role in mediating the relationship between population aging and innovation, highlighting the importance of investing in human capital development.
The findings of this research highlight the obstacles that population aging presents to fostering innovation. Overcoming these obstacles necessitates strategic investments in human capital and policies that support innovation. It is imperative for policymakers to implement recommendations that address population aging and encourage innovation in order to navigate the challenges posed by an aging population and promote a vibrant and dynamic economy.
随着人口老龄化,这种人口红利逐渐减少,这可能会对一个地区的创新产生影响。了解人口老龄化与创新之间的关系对于应对与老龄化人口相关的经济挑战至关重要。
本研究利用了2005年至2014年期间252个城市的人口老龄化和创新的面板数据。采用了各种估计方法,包括固定效应模型、广义矩估计法(GMM)和中介模型来分析数据。这些方法能够全面考察人口老龄化对创新的影响以及人力资本在调节这种关系中的作用。
研究结果表明,60岁和65岁的人口都显著阻碍创新。GMM表明创新具有“路径依赖性”,即过去的创新水平并不能减轻人口老龄化对未来创新的负面影响。此外,中介模型分析表明,人力资本在调节人口老龄化与创新之间的关系中起着关键作用,凸显了投资于人力资本发展的重要性。
本研究结果突出了人口老龄化对促进创新所带来的障碍。克服这些障碍需要对人力资本进行战略投资以及制定支持创新的政策。政策制定者必须实施应对人口老龄化和鼓励创新的建议,以便应对老龄化人口带来的挑战并促进充满活力和动态的经济。