Spatial-temporal characteristics of the coupling coordination of social security and economic development in China during 2002-2018

doi:10.1016/j.regsus.2021.04.001

Abstract

Abstract:

Clarifying the relationship between social security and economic development is helpful to realize the sustainable social security system and the stable function of sustainable economic development. In this paper, the entropy method, coupling coordination degree, standard deviation ellipse model, and spatial autocorrelation were used to study the spatial-temporal characteristics of coupling coordination of social security and economic development in China from 2002 to 2018. The results indicate that the relationship between social security and economic development in China has been gradually strengthened in the process of mutual adaptation and common development. The benign interaction between the two was unstable, though the coupling coordination degree gradually transitioned to the primary coupling coordination type. Besides, from a spatial perspective, first, the coupling coordination degree of social security and economic development in China contracted in the east-west and north-south directions, and the coupling coordination clustered in the central region in this period; second, the coupling coordination degree generally presented a positive spatial autocorrelation, and regions with similar coupling coordination degrees were in a state of agglomeration; finally, the hot spots clumped together to form a continuous area in the eastern coastal area while the cold spots expanded toward the northwest and northeast. Furthermore, the random distribution areas exhibited a trend of contraction.

Key words: Social security, Economic development, Coupling coordination degree, Gravity center, Moran index

Qiong LI, Yang ZHAO, Songlin LI, Lanlan ZHANG. Spatial-temporal characteristics of the coupling coordination of social security and economic development in China during 2002-2018[J]. Regional Sustainability, 2021, 2(2): 116-129.

Figures/Tables 7

Table 1

Fig. 1.

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Table 2

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Target layer	System layer	Criteria layer	Index layer	Weight	Indicator direction
Coupling coordination of social security and economic development	Economic development level	Economic growth (0.173)	GDP growth rate (%)	0.068	+
			Local general revenue growth (%)	0.059	+
			Retail growth rate of social consumer goods (%)	0.046	+
		Industrial structure (0.161)	Ratio of secondary industry value to GDP (%)	0.036	+
		Industrial structure (0.161)	Ratio of tertiary industry value to GDP (%)	0.125	+
		Qualitative efficiency (0.206)	GDP per capita (CNY)	0.151	+
		Qualitative efficiency (0.206)	Ratio of urban per capita disposable income to rural per capita disposable income (%)	0.055	-
		Foreign trade (0.460)	Total import and export of goods (1.0×10⁸ USD)	0.460	+
	Social security level	Social security expenditure level (0.072)	Proportion of social security expenditure to GDP (%)	0.072	+
		Social security fund (0.523)	Accumulated balance of medical insurance fund (1.0×10⁸ CNY)	0.102	+
			Accumulated balance of endowment insurance fund (1.0×10⁸ CNY)	0.099	+
			Accumulated balance of unemployment insurance fund (1.0×10⁸ CNY)	0.073	+
			Accumulated balance of maternity insurance fund (1.0×10⁸ CNY)	0.116	+
			Accumulated balance of work injury insurance fund (1.0×10⁸ CNY)	0.133	+
		Social insurance coverage rate (0.150)	Coverage rate of medical insurance for urban employees (%)	0.031	+
			Coverage rate of endowment insurance for urban employees (%)	0.018	+
			Coverage rate of unemployment insurance (%)	0.022	+
			Coverage rate of maternity insurance (%)	0.044	+
			Coverage rate of work injury insurance (%)	0.035	+
		Social security treatment (0.255)	Per capita expenditure of basic pension for urban employees (CNY)	0.043	+
			Technical health personnel per 1000 population (person)	0.057	+
			Number of beds in medical institutions per 1000 population (bed)	0.058	+
			Per capita expenditure of rural minimum living security (CNY)	0.097	+

Year	Barycentric coordinate	Minor semi-axis length (km)	Major semi-axis length (km)	Measure of area (×10⁴ km²)	Rotation angle (°)	Offset distance (km)	Offset direction
2002	33.397°N, 112.309°E	1073.226	1184.667	399.069	77.99	-	-
2003	33.425°N, 112.449°E	1054.731	1170.223	387.738	77.58	15.863	Northeast
2004	33.550°N, 112.543°E	1058.877	1164.339	387.305	76.91	17.378	Northeast
2005	33.612°N, 112.536°E	1056.155	1155.215	383.282	76.68	6.933	Northwest
2006	33.594°N, 112.637°E	1047.846	1169.917	385.106	75.22	11.399	Southeast
2007	33.542°N, 112.688°E	1046.456	1166.862	383.591	74.67	8.093	Southeast
2008	33.645°N, 112.612°E	1051.084	1173.074	387.338	74.62	14.223	Northwest
2009	33.523°N, 112.540°E	1044.905	1177.807	386.615	73.82	15.740	Southwest
2010	33.494°N, 112.622°E	1039.929	1165.697	380.818	73.55	9.664	Southeast
2011	33.594°N, 112.309°E	1053.343	1181.947	391.107	76.00	36.509	Northwest
2012	33.551°N, 112.283°E	1054.604	1182.120	391.632	76.05	5.583	Southwest
2013	33.467°N, 112.163°E	1057.594	1172.526	389.555	77.03	16.275	Southwest
2014	33.484°N, 112.362°E	1054.949	1165.320	386.193	76.38	22.191	Northeast
2015	33.475°N, 112.381°E	1047.115	1167.852	384.158	75.83	2.336	Southeast
2016	33.291°N, 112.275°E	1045.570	1169.429	384.109	74.96	23.594	Southwest
2017	33.336°N, 112.333°E	1044.737	1166.020	382.684	75.69	8.157	Northeast
2018	33.383°N, 112.441°E	1039.648	1152.325	376.347	75.64	13.087	Northeast

Year	Moran’s I	P value	Year	Moran’s I	P value
2002	0.238	0.015	2011	0.228	0.023
2003	0.294	0.004	2012	0.262	0.010
2004	0.308	0.003	2013	0.237	0.019
2005	0.288	0.005	2014	0.280	0.006
2006	0.302	0.003	2015	0.304	0.003
2007	0.324	0.002	2016	0.087	0.273
2008	0.327	0.002	2017	0.296	0.004
2009	0.304	0.003	2018	0.295	0.004
2010	0.329	0.002