中国银发经济发展水平测度及时空分异研究

doi:10.12118/j.issn.1000-6060.2025.752

Abstract

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

LIU Shiqi, ZHANG Airu. Measurement and spatiotemporal differentiation of China’s silver economy development level[J].Arid Land Geography, 2026, 49(10): 2158-2170.

Figures/Tables 12

Tab. 1

Tab. 2

Measurement results of China’s silver economy development level"

地区	省（区、市）	2012年	2013年		2015年	2016年	2017年	2018年	2019年	2020年	2021年	2022年	2023年
华东	江苏	0.229	0.269	0.288	0.289	0.313	0.322	0.344	0.350	0.452	0.501	0.513	0.538
	浙江	0.210	0.321	0.355	0.242	0.245	0.299	0.305	0.301	0.338	0.419	0.432	0.448
	山东	0.184	0.219	0.210	0.214	0.237	0.233	0.225	0.233	0.286	0.300	0.331	0.401
	福建	0.144	0.152	0.152	0.194	0.173	0.170	0.219	0.224	0.256	0.277	0.282	0.298
	安徽	0.117	0.127	0.126	0.144	0.180	0.184	0.216	0.181	0.215	0.249	0.278	0.265
	上海	0.061	0.076	0.100	0.092	0.111	0.138	0.120	0.134	0.148	0.220	0.194	0.204
	江西	0.078	0.093	0.079	0.083	0.097	0.128	0.098	0.123	0.175	0.188	0.203	0.204
华中	湖南	0.115	0.121	0.139	0.133	0.112	0.160	0.177	0.219	0.280	0.304	0.342	0.367
	河南	0.118	0.133	0.128	0.163	0.157	0.211	0.172	0.184	0.229	0.258	0.288	0.335
	湖北	0.078	0.088	0.107	0.142	0.141	0.133	0.147	0.166	0.214	0.246	0.258	0.266
西南	四川	0.153	0.171	0.209	0.230	0.292	0.316	0.345	0.318	0.354	0.375	0.383	0.424
	云南	0.095	0.110	0.086	0.100	0.113	0.099	0.135	0.122	0.197	0.176	0.190	0.211
	重庆	0.079	0.079	0.093	0.091	0.100	0.117	0.129	0.111	0.140	0.156	0.154	0.155
	贵州	0.065	0.091	0.076	0.105	0.090	0.112	0.102	0.087	0.152	0.141	0.155	0.149
	西藏	0.007	0.036	0.008	0.029	0.015	0.010	0.012	0.046	0.015	0.033	0.032	0.040
华南	广东	0.142	0.148	0.158	0.167	0.177	0.202	0.237	0.247	0.288	0.321	0.340	0.392
	广西	0.075	0.064	0.074	0.068	0.076	0.123	0.095	0.085	0.140	0.152	0.156	0.174
	海南	0.036	0.022	0.013	0.026	0.025	0.019	0.021	0.040	0.071	0.031	0.040	0.050
华北	河北	0.067	0.085	0.084	0.109	0.148	0.116	0.155	0.144	0.246	0.300	0.277	0.273
	北京	0.112	0.112	0.103	0.124	0.115	0.121	0.108	0.138	0.172	0.206	0.201	0.203
	山西	0.084	0.083	0.099	0.073	0.071	0.079	0.112	0.106	0.112	0.164	0.149	0.159
	天津	0.048	0.043	0.048	0.040	0.069	0.067	0.073	0.109	0.091	0.083	0.108	0.103
	内蒙古	0.031	0.056	0.064	0.043	0.061	0.051	0.061	0.048	0.077	0.108	0.115	0.147
东北	辽宁	0.077	0.071	0.083	0.116	0.094	0.103	0.123	0.141	0.143	0.169	0.166	0.182
	黑龙江	0.051	0.051	0.062	0.065	0.075	0.113	0.101	0.102	0.105	0.117	0.115	0.118
	吉林	0.032	0.039	0.037	0.048	0.041	0.063	0.105	0.095	0.094	0.120	0.127	0.132
西北	陕西	0.090	0.076	0.095	0.094	0.099	0.101	0.093	0.119	0.131	0.154	0.156	0.174
	甘肃	0.035	0.038	0.041	0.049	0.047	0.055	0.068	0.085	0.095	0.107	0.102	0.117
	新疆	0.060	0.044	0.046	0.064	0.074	0.060	0.089	0.070	0.085	0.076	0.071	0.084
	宁夏	0.015	0.021	0.018	0.013	0.019	0.027	0.026	0.029	0.064	0.058	0.054	0.060
	青海	0.022	0.016	0.016	0.019	0.024	0.032	0.039	0.038	0.037	0.069	0.049	0.042

Tab. 2

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 3

Fig. 6

Fig. 7

Fig. 8

Fig. 9

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一级指标	二级指标	三级指标	指标权重	指标方向
银发主体	人口基础	65岁及以上人口数/人	0.021	+
	人口基础	老年人口抚养比/%	0.010	+
	老年福利	高龄补贴老年人数/人	0.039	+
		护理补贴老年人数/人	0.064	+
		养老服务补贴老年人数/人	0.088	+
银发市场	老年教育	老年学校个数/个	0.058	+
	老年教育	老年学校在校人数/人	0.048	+
	老年活动	老年活动站参与人数/人	0.044	+
		老年人协会个数/个	0.030	+
		老年基金会个数/个	0.123	+
		老年社团组织个数/个	0.056	+
	消费能力	老年人可支配收入总量/10⁴元	0.031	+
		老年人食品消费支出总量/10⁴元	0.029	+
		老年人生活服务消费支出总量/10⁴元	0.029	+
		老年人教育文娱消费支出总量/10⁴元	0.027	+
		老年人医疗保健消费支出总量/10⁴元	0.028	+
	基础设施	养老机构数/个	0.070	+
	基础设施	养老机构床位数/张	0.042	+
银发保障	养老保障	城镇职工基本养老保险参保人数/10⁴人	0.021	+
		城镇职工基本养老保险基金收入/10⁸元	0.022	+
		城乡居民基本养老保险参保人数/10⁴人	0.025	+
		城乡居民基本养老保险基金收入/10⁸元	0.028	+
	医疗保障	每千人执业医师数量/$\mathrm{人}\bullet ({10}^{3}{\mathrm{人})}^{-1}$	0.009	+
		城乡居民基本医疗保险参保人数/10⁴人	0.030	+
		每千人医疗卫生机构床位数/$\mathrm{张}\bullet ({10}^{3}{\mathrm{人})}^{-1}$	0.006	+
		医疗卫生机构数/个	0.024	+

年份	全局莫兰指数	P值	Z值
2012	0.286	0.001	2.985
2013	0.306	0.001	3.277
2014	0.244	0.003	2.700
2015	0.244	0.005	2.573
2016	0.219	0.009	2.360
2017	0.243	0.005	2.581
2018	0.149	0.044	1.701
2019	0.181	0.023	1.997
2020	0.223	0.008	2.390
2021	0.240	0.005	2.546
2022	0.271	0.002	2.820
2023	0.219	0.010	2.332

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

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