In mountainous areas, the regional difference of poverty is significant due to the interweaving of natural conditions and cultural factors. The determination of the poverty-affluence degree and the reasons can help to improve decision support for mountainous areas to get rid of poverty and become rich. This paper takes mountain counties in Hebei province as the basic unit. 33 indicators are selected from five dimensions. The natural environment (A), the land resources (B), the county economy (C), the people's quality of life (D) and the livelihood ability (E) to construct a index system. And multidimensional povertyaffluence status is obtained in research area. The poverty location entropy is introduced to analyze the influence of each dimension on the occurrence of poverty. In order to discover the spatial consistency and differences between poverty-affluence distribution and dominant dimension, the two results are compared in space. And sustainable livelihood strategies are discussed with the dominant factors of each dimension. The results are as follows. the incidence of multidimensional poverty is 89.52% and above moderate poverty is 62.50%. The poverty level is deep in research area. In spatial distribution, moderate and low poverty degrees were frequent, while severe, rich or relatively rich areas are scattered. In poverty driver, the incidence of poverty dominated by A and C dimensions is higher than that of other dimensions. Severe poverty is highly coupled with A dimension, and moderate poverty is consistent with A and C dimensions. Basing on the results, the livelihoods strategies are put forward, such as the ecological relocation, an increase of the profit of the natural resources and getting rid of poverty through land and agricultural industry.
LIU Xin
,
QIN Yanjie
,
FENG Xiaomiao
,
ZHU Sujia
. Determination of poverty-affluence degree and sustainable livelihood strategies in mountainous counties of Hebei Province[J]. Science & Technology Review, 2020
, 38(13)
: 73
-82
.
DOI: 10.3981/j.issn.1000-7857.2020.13.009
[1] 西奥多·W·舒尔茨. 人力资本理论[M]. 北京:北京经济学院出版社, 1991.
[2] 阿瑟·刘易斯. 二元经济论[M]. 北京:北京经济学院出版社, 1989.
[3] 拉格纳·纳克斯. 不发达国家资本的形成问题[M]. 北京:商务印书馆, 1966.
[4] 刘豪兴. 农村社会学[M]. 北京:中国人民大学出版社, 2004.
[5] 冈纳·缪尔达尔. 亚洲的戏剧:对一些国家贫困问题的研究[M]. 北京:北京经济学院出版社, 1992.
[6] 刘成果. 世纪扶贫文稿[M]. 北京:中国农业出版社, 2003.
[7] 周彬彬. 向贫困挑战[M]. 北京:人民出版社, 1991.
[8] 康晓光.中国贫困与反贫困理论[M]. 桂林:广西人民出版社, 1995.
[9] 樊宏, 刘妙娟. 可持续发展是贫困山区的根本出路[J]. 科技导报, 2003(5):57-59.
[10] 李瑞华, 汤晓月, 李永杰. 贫困县退出的识别方法与运行机制研究[J]. 农业现代化研究, 2017, 38(6):1016-1025.
[11] 程晓宇, 陈志钢, 张莉. 农村持久多维贫困测量与分析[J]. 中国人口·资源与环境, 2019, 29(7):140-148.
[12] 余文波, 蔡海生, 张莹, 等. 农村土地精准扶贫/脱贫研究综述及展望[J]. 江西农业学报, 2017, 29(4):117-122.
[13] 国家统计局住户调查办公室. 2017中国农村贫困监测报告[M]. 北京:中国统计出版社, 2017.
[14] 陈国阶. 2003中国山区发展报告[M]. 北京:商务印书馆, 2004.
[15] 王小林. 贫困标准及全球贫困状况[J]. 经济研究参考, 2012(55):41-50.
[16] 李昌勇. 基于CHNS的中国家庭多维贫困研究[D]. 安徽:安徽财经大学, 2014.
[17] 王金营, 李竞博. 连片贫困地区农村家庭贫困测度及其致贫原因分析[J]. 中国人口科学, 2013(4):2-12.
[18] 周扬, 郭远智, 刘彦随. 中国县域贫困综合测度及2020年后减贫瞄准[J]. 地理学报, 2018, 73(8):1481.
[19] 曾永明, 张果. 基于GIS和BP神经网络的区域农村贫困空间模拟分析——一种区域贫困程度测度新方法[J]. 地理与地理信息科学, 2011, 27(2):70-75.
[20] 王艳慧, 钱乐毅, 段福洲. 县级多维贫困度量及其空间分布格局研究——以连片特困区扶贫重点县为例[J]. 地理科学, 2013, 33(12):1489-1497.
[21] 周常春, 翟羽佳, 车震宇. 连片特困区农户多维贫困测度及能力建设研究[J]. 中国人口·资源与环境, 2017, 27(11):95-103.
[22] Ian S. Livelihoods perspectives and rural development[J]. The Journal of Peasant Studies, 2009, 36(1):171-196.
[23] DFID. Sustainable livelihoods guidance sheets[R]. London, UK:Department for International Development, 2000:68-125.
[24] Vista B M, Nel E, Binns T. Land, landlords and sustainable livelihoods:The impact of agrarian reform on a coconut hacienda in the Philippines[J]. Land Use Policy, 2012, 29(1):154-164.
[25] 赵雪雁. 地理学视角的可持续生计研究:现状、问题与领域[J]. 地理研究, 2017, 36(10):1859-1872.
[26] 汤青, 李扬, 陈明星, 等. 半城镇化农民可持续生计与农村可持续发展[J]. 地理科学进展, 2018, 37(8):1023.
[27] 刘欣, 赵艳霞, 葛京凤, 等. 河北省太行山区土地资源生态安全预警与调控研究[J]. 生态与农村环境学报, 2010, 26(6):534-538.
[28] 陈莲芳, 严良. 基于复合区位熵的中国油气资源产业集群识别[J]. 中国人口·资源与环境, 2012, 22(2):152-158.
[29] 范郢, 古恒宇, 孟鑫, 等. 中国东北地区产业集群的空间格局分析[J]. 地域研究与开发, 2019, 38(3):18-22.