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干旱区地理 ›› 2026, Vol. 49 ›› Issue (10): 2158-2170.doi: 10.12118/j.issn.1000-6060.2025.752 cstr: 32274.14.ALG2025752

• 区域发展 • 上一篇    下一篇

中国银发经济发展水平测度及时空分异研究

刘世琦(), 张爱儒()   

  1. 青海大学财经学院, 青海 西宁 810016
  • 收稿日期:2025-11-24 修回日期:2025-12-22 出版日期:2026-10-25 发布日期:2026-10-26
  • 通讯作者: 张爱儒(1969-),男,博士,二级教授,博士生导师,主要从事生态经济等方面的研究. E-mail: qhdxjjxzar@126.com
  • 作者简介:刘世琦(2003-),男,硕士研究生,主要从事区域经济发展等方面的研究. E-mail: ys240202021634@qhu.edu.cn
    作者贡献

    论文构思:刘世琦;数据管理:刘世琦;规范分析:张爱儒;获取资助:刘世琦、张爱儒;调查研究:刘世琦;方法设计:刘世琦;项目管理:刘世琦、张爱儒;提供资源:张爱儒;软件编程:刘世琦;监督指导:张爱儒;验证复核:张爱儒;可视化:刘世琦;初稿撰写:刘世琦;修订编辑:刘世琦、张爱儒。

  • 基金资助:
    青海大学2025年研究生科研和实践创新项目(2025-GMKY-31);青海省哲学社会科学重大“揭榜挂帅”规划项目(25JB002);青海省“昆仑英才·高端创新创业人才”培养杰出人才项目(k9924063)

Measurement and spatiotemporal differentiation of China’s silver economy development level

LIU Shiqi(), ZHANG Airu()   

  1. School of Finance and Economics, Qinghai University, Xining 810016, Qinghai, China
  • Received:2025-11-24 Revised:2025-12-22 Published:2026-10-25 Online:2026-10-26

摘要:

推动银发经济增长,是中国在人口新常态下,保障民生福祉、促进经济持续增长、高质量发展的必然选择。基于中国31个省(区、市)2012—2023年的面板数据,从银发主体、银发市场、银发保障3个维度出发搭建银发经济评价指标体系,采用熵值法测度银发经济发展水平,并采用核密度估计、空间相关性分析、Dagum基尼系数等方法探究其时空分异。结果表明:(1) 中国银发经济发展水平表现出明显的上升趋势,七大区域之间发展层次明显,华东、华中地区为第一梯队,华北、华南、西南、东北地区为第二梯队,西北地区为第三梯队。(2) 不同区域间存在显著的空间异质性,整体呈现出空间正相关性的特征,高水平地区主要集中在华东地区,较高水平地区主要分布于华中地区,较低水平地区主要分布于西北地区。(3) 银发经济发展水平差异最主要的体现是区域与区域之间的差距,总体差异中超过2/3来源于七大区域之间的发展不平衡,内部差异中华南、西南地区发展差异较大,其中尤以华南地区内部差异最大。研究结果为中国银发经济发展提供参考。

关键词: 银发经济, 时空分异, 空间相关性, Dagum基尼系数

Abstract:

Under China’s current demographic conditions, promoting the growth of the silver economy is necessary for the people’s well-being via sustained economic growth and high-quality development. Using panel data from 31 provinces (autonomous regions and municipalities directly under the central government) from 2012 to 2023, this study constructs an evaluation index for the silver economy across three dimensions (silver population, silver market, and silver security), measures development levels using the entropy method, and examines spatiotemporal variation through kernel density estimation, spatial correlation analysis, and the Dagum Gini coefficient. The results show that China’s silver economy exhibits a steady upward trend, with seven major regions forming distinct tiers (east China and central China in the first tier; north China, south China, southwest China, and northeast China in the second; and northwest China in the third). Significant spatial heterogeneity exists, with an overall positive spatial correlation (i.e., high-level areas cluster in east China, relatively high-level areas in central China, and low-level areas in northwest China). Interregional differences constitute more than two-thirds of overall variation, while intraregional disparities are pronounced in south China and southwest China, with south China showing the greatest internal divergence. These findings offer insights for developing China’s silver economy.

Key words: silver economy, spatiotemporal differentiation, spatial correlation, Dagum Gini coefficient