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Regional Equity and Influencing Factor of Social Assistance in China
Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 201...
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Published in: | Chinese geographical science 2021-08, Vol.31 (4), p.611-628 |
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description | Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression (GWR) model. The results suggest that the level of per capita social assistance expenditure (PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality. This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue, urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. The remaining three factors have a positive effect on PSAE, but the effect intensity is not high. |
doi_str_mv | 10.1007/s11769-021-1195-7 |
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Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression (GWR) model. The results suggest that the level of per capita social assistance expenditure (PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality. This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue, urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. 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Sci</addtitle><description>Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression (GWR) model. The results suggest that the level of per capita social assistance expenditure (PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality. This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue, urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. 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Ye, Shilin ; Qi, Xinhua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c391t-d2c7882275a86f13c89902ce0c5f0f32fb8d8efb8eb0201483eec00e383c0d783</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Earth and Environmental Science</topic><topic>Geography</topic><topic>Heterogeneity</topic><topic>Inequality</topic><topic>Natural disasters</topic><topic>Per capita</topic><topic>Poverty</topic><topic>Urbanization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Jiawei</creatorcontrib><creatorcontrib>Ye, Shilin</creatorcontrib><creatorcontrib>Qi, Xinhua</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Science Journals</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest Central (New)</collection><collection>ProQuest One Academic (New)</collection><collection>ProQuest One Academic Middle East (New)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Chinese geographical science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Jiawei</au><au>Ye, Shilin</au><au>Qi, Xinhua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regional Equity and Influencing Factor of Social Assistance in China</atitle><jtitle>Chinese geographical science</jtitle><stitle>Chin. Geogr. Sci</stitle><date>2021-08-01</date><risdate>2021</risdate><volume>31</volume><issue>4</issue><spage>611</spage><epage>628</epage><pages>611-628</pages><issn>1002-0063</issn><eissn>1993-064X</eissn><abstract>Social assistance is the last safety net in the social security system and plays a vital role in poverty alleviation in countries around the world. Promoting the equal financial assistance is meaningful to achieve equalization of social assistance. Based on the provincial panel data from 2002 to 2017, this paper analyzes the dynamic characteristics and main influencing factors of the equity of social assistance in China, using the Theil index and geographically weighted regression (GWR) model. The results suggest that the level of per capita social assistance expenditure (PSAE) in China keeps increasing year by year, but the changes in different regions and provinces are quite different. These changes not only significantly changed the spatial pattern of PSAE in China, but also greatly improved its spatial coupling with the deeply impoverished areas. Further analysis shows that the regional inequality of PSAE between provinces is obvious during the study period, and the inter-regional inequality is significantly higher than the intra-regional inequality. This makes inter-regional inequality become the main source of the regional inequality of PSAE in China for a long time. According to GWR results, there is obvious spatiotemporal heterogeneity in the influence intensity and direction of the per capita financial revenue, urbanization rate, urban unemployment rate, natural disaster-affected area, and transfer payment intensity on the PSAE. The urbanization rate and per capita financial revenue are the main driving factors of PSAE, and the impact intensity of per capita financial revenue tends to strengthen. 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subjects | Earth and Environmental Science Geography Heterogeneity Inequality Natural disasters Per capita Poverty Urbanization |
title | Regional Equity and Influencing Factor of Social Assistance in China |
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