中国低保人口分布特征及影响因素研究
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摘要
文章基于中国县级低保数据,采用空间统计分析方法,对低保人口分布特征及其影响因素进行了分析。研究发现:(1)低保人口规模在"胡焕庸线"两侧呈"西少东多"态势,83.5%的低保人口分布于东南半壁,低保率则呈"西高东低"态势,西北半壁的低保率达10.9%,东南半壁仅为3.9%。(2)全国低保人口规模和低保率总体呈下降趋势。低保人口总量由西向东递减,西部地区的低保人口总量占全国低保人口总数的比重呈上升态势,使低保人口的重心向西北方向移动。(3)低保率存在较强的空间正相关关系,且其空间集聚趋势在弱化,低保率的热点区与中国集中连片特困地区高度重合,且大部分位于"胡焕庸线"的西北半壁,冷点区域则集中分布在经济社会较为发达的渤海湾北岸的唐山到雷州半岛的东部沿海地区。(4)从影响因素来看,海拔对低保率有显著的正向影响,人均GDP和人均受教育程度对低保率有显著的负向影响。
Based on data of the people living on minimum subsistence allowance, the paper analyses the spatial distribution and its determinants using spatial statistical analysis method. The study finds that:(1) the people living on minimum subsistence allowance are distributed more in the eastern regions than in the western regions. Those in southeast regions account for 83.5% in total. Yet, the proportion of population receiving the allowance is higher in the western regions and lower in the eastern regions. The proportion is 10.9% in the northwest of"Hu Line"and 3.9% in the southeast.(2) The size and relative share of the allowance receivers decrease in general, and its total decreases from west to east. The proportion in the western regions tends to increase, which makes the center of gravity of the subsistence allowance move to the northwest.(3) There is a strong positive spatial correlation in the relative share of allowance receivers and the trend of spatial agglomeration is weakening. The hot-spot areas of the rate coincide highly with concentrated contiguous areas and most of them are located in the northwest of the "Hu Line". The cold spots areas are concentrated in the eastern coastal areas of Tangshan to Leizhou Peninsula on the north bank of the Bohai Bay, where local economies are more developed.(4) The rate of allowance receivers is higher in areas with higher altitude, and GDP per capita and education per capita have a significant negative impact on the allowance rate.
Based on data of the people living on minimum subsistence allowance, the paper analyses the spatial distribution and its determinants using spatial statistical analysis method. The study finds that:(1) the people living on minimum subsistence allowance are distributed more in the eastern regions than in the western regions. Those in southeast regions account for 83.5% in total. Yet, the proportion of population receiving the allowance is higher in the western regions and lower in the eastern regions. The proportion is 10.9% in the northwest of"Hu Line"and 3.9% in the southeast.(2) The size and relative share of the allowance receivers decrease in general, and its total decreases from west to east. The proportion in the western regions tends to increase, which makes the center of gravity of the subsistence allowance move to the northwest.(3) There is a strong positive spatial correlation in the relative share of allowance receivers and the trend of spatial agglomeration is weakening. The hot-spot areas of the rate coincide highly with concentrated contiguous areas and most of them are located in the northwest of the "Hu Line". The cold spots areas are concentrated in the eastern coastal areas of Tangshan to Leizhou Peninsula on the north bank of the Bohai Bay, where local economies are more developed.(4) The rate of allowance receivers is higher in areas with higher altitude, and GDP per capita and education per capita have a significant negative impact on the allowance rate.
引文
1.高向东(2003):《大城市人口分布变动与郊区化研究---以上海为例》,复旦大学出版社。
2.谷缙等(2018):《城乡贫困人口时空格局演变及影响因素---以济南市为例》,《湖南师范大学自然科学学报》,第2期。
3.梁汉媚、方创琳(2011):《中国城市贫困人口动态变化与空间分异特征探讨》,《经济地理》,第10期。
4.孟斌等(2005):《基于空间分析方法的中国区域经济差异研究》,《地理科学》,第4期。
5.孙守纪、齐传钧(2010):《美国补充收入保障计划及其启示》,《美国研究》,第4期。
6.袁媛等(2016):《中国城市贫困的空间差异特征》,《地理科学进展》,第2期。
7.张凌华、王卓(2017):《中国族际居住隔离空间特征及影响因素---基于2000和2010年人口普查数据的分析》,《中国人口科学》,第6期。
8.Bramley G.,Lancaster S.,Gordon G.(2000),Benefit Take-up and the Geography of Poverty in Scotland.Regional Studies.34(6):507-519.
9.Debarsy N.,Ertur C.(2010),Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model.Regional Science and Urban Economics.40(6):453-470.
10.Gatrell A.C.(1979),Autocorrelation in Spaces.Environment and Planning A:Economy and Space.11(5):507-516.
11.Liu Y.,Wu F.(2006),Urban Poverty Neighbourhoods:Typology and Spatial Concentration under China’s Market Transition,A Case Study of Nanjing.Geoforum.37(4):610-626.
12.Neumark D.,Powers E.T.(2006),Supplemental Security Income,Labor Supply,and Migration.Journal of Population Economics.19(3):447-479.
13.Vega S.H.,Elhorst J.P.(2015),The Slx Model.Journal of Regional Science.55(3):339-363.
14.Wong S.(2016),Geographies of Medicalized Welfare:Spatial Analysis of Supplemental Security Income in the U.S.,2000-2010.Social Science&Medicine.160:9-19.
(1)国务院扶贫开发办在《中国农村扶贫开发纲要(2011~2020年)》中公布的集中连片特困地区共包括14个片区,由于西藏、新疆南疆三地州部分地区的县级数据缺失,本研究仅统计除了这两个区外的其他12个片区。
2.谷缙等(2018):《城乡贫困人口时空格局演变及影响因素---以济南市为例》,《湖南师范大学自然科学学报》,第2期。
3.梁汉媚、方创琳(2011):《中国城市贫困人口动态变化与空间分异特征探讨》,《经济地理》,第10期。
4.孟斌等(2005):《基于空间分析方法的中国区域经济差异研究》,《地理科学》,第4期。
5.孙守纪、齐传钧(2010):《美国补充收入保障计划及其启示》,《美国研究》,第4期。
6.袁媛等(2016):《中国城市贫困的空间差异特征》,《地理科学进展》,第2期。
7.张凌华、王卓(2017):《中国族际居住隔离空间特征及影响因素---基于2000和2010年人口普查数据的分析》,《中国人口科学》,第6期。
8.Bramley G.,Lancaster S.,Gordon G.(2000),Benefit Take-up and the Geography of Poverty in Scotland.Regional Studies.34(6):507-519.
9.Debarsy N.,Ertur C.(2010),Testing for Spatial Autocorrelation in a Fixed Effects Panel Data Model.Regional Science and Urban Economics.40(6):453-470.
10.Gatrell A.C.(1979),Autocorrelation in Spaces.Environment and Planning A:Economy and Space.11(5):507-516.
11.Liu Y.,Wu F.(2006),Urban Poverty Neighbourhoods:Typology and Spatial Concentration under China’s Market Transition,A Case Study of Nanjing.Geoforum.37(4):610-626.
12.Neumark D.,Powers E.T.(2006),Supplemental Security Income,Labor Supply,and Migration.Journal of Population Economics.19(3):447-479.
13.Vega S.H.,Elhorst J.P.(2015),The Slx Model.Journal of Regional Science.55(3):339-363.
14.Wong S.(2016),Geographies of Medicalized Welfare:Spatial Analysis of Supplemental Security Income in the U.S.,2000-2010.Social Science&Medicine.160:9-19.
(1)国务院扶贫开发办在《中国农村扶贫开发纲要(2011~2020年)》中公布的集中连片特困地区共包括14个片区,由于西藏、新疆南疆三地州部分地区的县级数据缺失,本研究仅统计除了这两个区外的其他12个片区。
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