区域多维贫困测量的理论与方法

doi:10.11821/dlxb202004007

摘要/Abstract

摘要：

贫困包括区域贫困和个体贫困,两者均具有多维属性。区域多维贫困是贫困地理学研究的重要内容,深度贫困地区是区域多维贫困的集中表现,是当前和未来脱贫攻坚的贫中之贫、困中之困、坚中之坚。本文以空间贫困理论为基础,界定了贫困地域系统和区域多维贫困的概念,并探究了区域多维贫困测度指标体系与评估方法。据此,以中国334个深度贫困县为研究对象,运用BP神经网络模型和ESDA技术刻画了中国深度贫困地区的多维贫困空间格局。结果表明：① 区域多维贫困是贫困地域系统发展演化过程中“人”“地”“业”三个核心要素耦合失调的一种外在表现形式,是特定地域在生态环境劣势、经济劣势、社会福利劣势上的综合表现,包括生态贫困、经济贫困和福利贫困3个维度。② 深度贫困地区最“深”的地方在青藏高原,最“深”的短板在公共服务和基础设施。从单一维度的贫困指数来看,深度贫困地区的福利贫困指数（WPI）>经济贫困指数（EPI）>生态贫困指数（NPI）,三者平均值分别为2.77、2.66、1.89,贫困人口社会福利供给不足和公共服务短缺是深度贫困地区最突出的问题;从多维贫困指数来看,青藏高原是区域多维贫困指数（RMP）的高集聚区或热点区,生态贫困、经济贫困和福利贫困程度均显著高于其他地区。③ 区域多维贫困指数能较好地揭示特定区域的贫困状况。在地理位置偏远、生态环境极其脆弱、区域劣势突出的地区,区域贫困和个体贫困在空间上高度重叠。

关键词: 区域多维贫困, 贫困地理学, 贫困地域系统, 深度贫困地区, 区域可持续发展

Abstract:

Poverty includes regional poverty and individual poverty, both of which are featured by multidimensional concept. Regional multidimensional poverty (RMP) is a major theme and content in poverty geography. Because of harsh natural environment, vulnerable economy and inadequate public services, severely impoverished areas (SIAs) are typical and highlighted areas of RMP, which have been the biggest obstacle to poverty alleviation in China. Based on the theory of spatial poverty, this paper defines the notion of impoverished areal system (IAS) and regional multidimensional poverty (RMP), explores their internal connections and proposes the evaluation indictors and measurement method for RMP. Taking 334 severely impoverished counties as research samples, we analyze the multidimensional poverty patterns of SIAs in 2016 by BP neural network model and exploratory spatial data analysis (ESDA). Results show that: (1) RMP is an external manifestation of the coupling imbalance of "human", "environment" and "industry" in the evolution of IAS. It reveals regional disadvantages in natural environment, economic development and social welfare, corresponding to natural poverty, economic poverty and welfare poverty, respectively. (2) The most severely impoverished county, with the poorest services and infrastructure, is found in the Qinghai-Tibet Plateau. From a single dimension of regional poverty, the Welfare Poverty Index (WPI) > Economic Poverty Index (EPI) > Natural Poverty Index (NPI) in the SIAs, whose average is 2.77, 2.66 and 1.89, respectively, indicating that the lack of social welfare and public services for the poor has become the prominent problem in the SIAs. From the perspective of multidimensional poverty, the Qinghai-Tibet Plateau is a high agglomeration region or "hot spot" of RMP, which is significantly higher than other areas in terms of natural poverty, economic poverty and welfare poverty. (3) Both RMP and individual multidimensional poverty are effective measures of poverty targeting. Their matching coefficient (M) can help us to judge the poverty status of some specific areas, e.g., RMP is superior to individual multidimensional poverty in the remote areas, extremely fragile ecological environment and obvious regional disadvantage, where the matching coefficient (M) is higher. RMP can more objectively reflect the true level of geographical capitals, effectively target poor areas and identify determinant impoverishing factors.

Key words: regional multidimensional poverty, poverty geography, impoverished areal system, severely impoverished areas, regional sustainable development

李寻欢, 周扬, 陈玉福. 区域多维贫困测量的理论与方法[J]. 地理学报, 2020, 75(4): 753-768.

LI Xunhuan, ZHOU Yang, CHEN Yufu. Theory and measurement of regional multidimensional poverty[J]. Acta Geographica Sinica, 2020, 75(4): 753-768.

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参考文献 44

[1]	Liu Yansui, Zhou Yang, Liu Jilai . Regional differentiation characteristics of rural poverty and targeted poverty alleviation strategy in China. Bulletin of Chinese Academy of Sciences, 2016,31(3):269-278.
	[ 刘彦随, 周扬, 刘继来 . 中国农村贫困化地域分异特征及其精准扶贫策略. 中国科学院院刊, 2016,31(3):269-278.]
[2]	Zhou Y, Liu Y S . The geography of poverty: Review and research prospects. Journal of Rural Studies, 201. https://doi.org/10.1016/j.jrurstud.2019.01.008
[3]	World Bank . Poverty and Shared Prosperity 2018: Piecing Together the Poverty Puzzle. Washington DC: World Bank, 2018.
[4]	United Nations . Transforming Our World: The 2030 Agenda for Sustainable Development. New York: United Nations, 2015.
[5]	Rowntree B S . Poverty: A Study of Town Life. London: Macmillan, 1901.
[6]	Wang Xiaolin. The Measurement of Poverty: Theories and Methods. 2nd ed. Beijing: Social Sciences Academic Press, 2017.
	[ 王小林 . 贫困测量: 理论与方法. 2版. 北京: 社会科学文献出版社, 2017.]
[7]	Sen A . Commodities and Capabilities. The Canadian Journal of Economics, 1987,20(1):198-201. doi: 10.2307/135247
[8]	Zhou Jinyan . Why have almost all efforts to reduce poverty in sub-Saharan Africa failed? Chinese Science Bulletin, 2018,63(7):606-610.
	[ 周瑾艳 . 为什么改变撒哈拉以南非洲贫困状态的努力几乎全部失败? 科学通报, 2018,63(7):606-610.]
[9]	Wang Xiaolin, Alkire Sabina . Measurement of multidimensional poverty in China: Evaluation and policy implication. Chinese Rural Economy, 2009(12):4-10.
	[ 王小林 , Alkire Sabina. 中国多维贫困测量: 估计和政策含义. 中国农村经济, 2009(12):4-10.]
[10]	Tandia D, Havard M . The evolution of thinking about poverty: Exploring the interactions. General Information, 1999,55(6):957-963.
[11]	UNDP. Human Development Report 1990: Concept and Measurement of Human Development. New York and Oxford: Oxford University Press, 1990.
[12]	He Renwei, Li Guangqin, Liu Yunwei , et al. Theoretical analysis and case study on targeted poverty alleviation based on sustainable livelihoods framework: A case study of Liangshan Yi Autonomous Prefecture, Sichuan Province. Progress in Geography, 2017,36(2):182-192. doi: 10.18306/dlkxjz.2017.02.005
	[ 何仁伟, 李光勤, 刘运伟 , 等. 基于可持续生计的精准扶贫分析方法及应用研究: 以四川凉山彝族自治州为例. 地理科学进展, 2017,36(2):182-192.] doi: 10.18306/dlkxjz.2017.02.005
[13]	Alkire S, Foster J . Counting and multidimensional poverty measurement. Journal of Public Economics, 2011,95(7-8):476-487. doi: 10.1016/j.jpubeco.2010.11.006
[14]	Alkire S, Foster J . Understandings and misunderstandings of multidimensional poverty measurement. Journal of Economic Inequality, 2011,9(2):289-314. doi: 10.1007/s10888-011-9181-4
[15]	Fu Bojie . Geography: From knowledge, science to decision making support. Acta Geographica Sinica, 2017,72(11):1923-1932. doi: 10.11821/dlxb201711001
	[ 傅伯杰 . 地理学: 从知识、科学到决策. 地理学报, 2017,72(11):1923-1932.] doi: 10.11821/dlxb201711001
[16]	Ding Jianjun, Leng Zhiming . Regional poverty analysis in a view of geography science. Acta Geographica Sinica, 2018,73(2):232-247. doi: 10.11821/dlxb201802003
	[ 丁建军, 冷志明 . 区域贫困的地理学分析. 地理学报, 2018,73(2):232-247.] doi: 10.11821/dlxb201802003
[17]	Jiang Dehua, Zhang Yaoguang, Yang Liu , et al. Research on the Classfication and Development of Poor Area in China. Geographical Research, 1988,7(3):1-16.
	[ 姜德华, 张耀光, 杨柳 , 等. 中国贫困地区类型划分及开发研究提要报告. 地理研究, 1988,7(3):1-16.]
[18]	Zhou Y, Li Y R, Liu Y S . The nexus between regional eco-environmental degradation and rural impoverishment in China. Habitat International, 2020,96:102086. doi: 10.1016/j.habitatint.2019.102086
[19]	Wang Yanhui, Qian Leyi, Duan Fuzhou . Multidimensional poverty measurement and spatial distribution pattern at the county scale: A case study on key county from national contiguous special poverty-stricken areas. Scientia Geographica Sinica, 2013,33(12):1489-1497.
	[ 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. 地理科学, 2013,33(12):1489-1497.]
[20]	Liu Y S, Liu J L, Zhou Y . Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies. Journal of Rural Studies, 2017,52:66-75. doi: 10.1016/j.jrurstud.2017.04.002
[21]	Chen Yefeng, Wang Yanhui, Zhao Wenji , et al. Contributing factors and classification of poor villages in China. Acta Geographica Sinica, 2017,72(10):1827-1844. doi: 10.11821/dlxb201710008
	[ 陈烨烽, 王艳慧, 赵文吉 , 等. 中国贫困村致贫因素分析及贫困类型划分. 地理学报, 2017,72(10):1827-1844.] doi: 10.11821/dlxb201710008
[22]	Liu Yanhua, Xu Yong . Geographical identification and classification of multi-dimensional poverty in rural China. Acta Geographica Sinica, 2015,70(6):993-1007. doi: 10.11821/dlxb201506012
	[ 刘艳华, 徐勇 . 中国农村多维贫困地理识别及类型划分. 地理学报, 2015,70(6):993-1007.] doi: 10.11821/dlxb201506012
[23]	Zhou Yang, Guo Yuanzhi, Liu Yansui . Comprehensive measurement of county poverty and anti-poverty targeting after 2020 in China. Acta Geographica Sinica, 2018,73(8):1478-1493. doi: 10.11821/dlxb201808007
	[ 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. 地理学报, 2018,73(8):1478-1493.] doi: 10.11821/dlxb201808007
[24]	Chen Yefeng, Wang Yanhui, Wang Xiaolin . Measurement and spatial analysis of poverty-stricken villages in China. Geographical Research, 2016,35(12):2298-2308.
	[ 陈烨烽, 王艳慧, 王小林 . 中国贫困村测度与空间分布特征分析. 地理研究, 2016,35(12):2298-2308.]
[25]	Yuan Yuan, Wang Yanglin, Ma Jing , et al. Multidimensional evaluation of county poverty degree in Hebei Province. Progress in Geography, 2014,33(1):124-133. doi: 10.11820/dlkxjz.2014.01.014
	[ 袁媛, 王仰麟, 马晶 , 等. 河北省县域贫困度多维评估. 地理科学进展, 2014,33(1):124-133.] doi: 10.11820/dlkxjz.2014.01.014
[26]	Wen Qi, Shi Linna, Ma Caihong , et al. Spatial heterogeneity of multidimensional poverty at the village level: Loess Plateau. Acta Geographica Sinica, 2018,73(10):1850-1864. doi: 10.11821/dlxb201810003
	[ 文琦, 施琳娜, 马彩虹 , 等. 黄土高原村域多维贫困空间异质性研究: 以宁夏彭阳县为例. 地理学报, 2018,73(10):1850-1864.] doi: 10.11821/dlxb201810003
[27]	Zhou Y, Guo L Y, Liu Y S . Land consolidation boosting poverty alleviation in China: Theory and practice. Land Use Policy, 2019,82:339-348. doi: 10.1016/j.landusepol.2018.12.024
[28]	Liu Y S, Guo Y Z, Zhou Y . Poverty alleviation in rural China: Policy changes, future challenges and policy implications. China Agricultural Economic Review, 2018,10(2):241-259. doi: 10.1108/CAER-10-2017-0192
[29]	Liu Xiaopeng, Li Yonghong, Wang Yajuan , et al. Geographical identification of spatial poverty at county scale. Acta Geographica Sinica, 2017,72(3):545-557. doi: 10.11821/dlxb201703014
	[ 刘小鹏, 李永红, 王亚娟 , 等. 县域空间贫困的地理识别研究: 以宁夏泾源县为例. 地理学报, 2017,72(3):545-557.] doi: 10.11821/dlxb201703014
[30]	Liu Xiaopeng, Su Xiaofang, Wang Yajuan , et al. Review on spatial poverty and deprivation and its enlightenments to poverty geography studies in China. Arid Land Geography, 2014,37(1):144-152.
	[ 刘小鹏, 苏晓芳, 王亚娟 , 等. 空间贫困研究及其对我国贫困地理研究的启示. 干旱区地理, 2014,37(1):144-152.]
[31]	Chen Quangong, Chen Xi . Spatial poverty and its policy implications. Guizhou Social Sciences, 2010(8):87-92.
	[ 陈全功, 程蹊 . 空间贫困及其政策含义. 贵州社会科学, 2010(8):87-92.]
[32]	Jalan J, Ravallion M . Geographic poverty traps? A micro model of consumption growth in rural China. Journal of Applied Econometrics, 2002,17(4):329-346. doi: 10.1002/(ISSN)1099-1255
[33]	Jalan J, Ravallion M . Spatial poverty traps? World Bank Policy Research Working Paper No. 1862, 1997.
[34]	Daimon T . The spatial dimension of welfare and poverty: Lessons from a regional targeting programme in Indonesia. Asian Economic Journal, 2001,15(4):345-367. doi: 10.1111/asej.2001.15.issue-4
[35]	Bird K, Shepherd A . Livelihoods and chronic poverty in Semiarid Zimbabwe. World Development, 2003,31(3):591-610. doi: 10.1016/S0305-750X(02)00220-6
[36]	Chronic Poverty Research Centre . Chronic poverty report 2004-05. Manchester: CPRC, University of Manchester, 2004.
[37]	Zhou Y, Guo Y Z, Liu Y S , et al. Targeted poverty alleviation and land policy innovation: Some practice and policy implications from China. Land Use Policy, 2018,74:53-65. doi: 10.1016/j.landusepol.2017.04.037
[38]	Alkire S . Dimensions of human development. World Development, 2002,30(2):181-205. doi: 10.1016/S0305-750X(01)00109-7
[39]	Li Shuangcheng, Xu Yueqing, Fu Xiaofeng . Spatial simulation using GIS and ANN for regional pauperization in China. Resources Science, 2005,27(4):76-81.
	[ 李双成, 许月卿, 傅小锋 . 基于GIS和ANN的中国区域贫困化空间模拟分析. 资源科学, 2005,27(4):76-81.]
[40]	Xu Jianhua. Mathematical Method in Contemporary Geography. 3rd ed. Beijing: Higher Education Press, 2018.
	[ 徐建华 . 现代地理学中的数学方法. 3版. 北京: 高等教育出版社, 2018.]
[41]	Xu Yueqing, Li Shuangcheng, Cai Yunlong . Spatial simulation using GIS and artificial neural network for regional poverty: A case study of Maotiaohe Watershed, Guizhou Province. Progress in Geography, 2006,25(3):79-85. doi: 10.11820/dlkxjz.2006.03.010
	[ 许月卿, 李双成, 蔡运龙 . 基于GIS和人工神经网络的区域贫困化空间模拟分析: 以贵州省猫跳河流域为例. 地理科学进展, 2006,25(3):79-85.] doi: 10.11820/dlkxjz.2006.03.010
[42]	Chen Yanguang. Geographical Data Analysis with Matlab. Beijing: Higher Education Press, 2012.
	[ 陈彦光 . 基于Matlab的地理数据分析. 北京: 高等教育出版社, 2012.]
[43]	Robert H N . Theory of the backpropagation neural network. International 1989 Joint Conference on Neural Networks, 1989(1):593-605.
[44]	Zhou Yang, Li Xunhuan . Geographical pattern and mechanism of poverty differentiation in plain areas: A case study of Lixin County, Anhui Province. Scientia Geographica Sinica, 2019,39(10):1592-1601.
	[ 周扬, 李寻欢 . 平原农区贫困地理格局及其分异机制: 以安徽省利辛县为例. 地理科学, 2019,39(10):1592-1601.]

维度	编码	指标	指标释义
生态贫困	X₁	平均海拔(m)	县域平均DEM高程
	X₂	地表起伏度(m)	县域栅格单元的高程范围
	X₃	坡度大于25°土地面积占比(%)	地表坡度大于25°的土地面积占比
	X₄	生态脆弱区面积占比(%)	土地沙化区和土壤强度侵蚀区的面积占比
	X₅	人均耕地面积(m²/人)	水田、旱地的总面积除以户籍人口
经济贫困	X₆	人均GDP(元)	地区生产总值/常住人口
	X₇	人均财政收入(元)	公共财政预算收入/户籍人口
	X₈	固定资产投资(万元)	社会固定资产投资总额
	X₉	路网密度(km/km²)	县域交通道路里程/总面积
	X₁₀	到铁路干线的最短距离(km)	县域几何中心到铁路干线的最短距离
福利贫困	X₁₁	在校学生数(人)	普通中学、中职、小学在校学生总数
	X₁₂	平均受教育年限(年)	居民受教育的平均年限长度
	X₁₃	医疗卫生机构床位数(床/千人)	医疗卫生机构床位数/常住人口
	X₁₄	社会福利性单位床位数(床/千人)	社会福利性单位床位数/常住人口

NPI	X₁	X₂		X₃		X₄		X₅	等级
	1	1		1		1		1	5(高)
	0.8001	0.5126		0.6636		0.6218		0.9946	4(较高)
	0.5605	0.3317		0.3932		0.3468		0.9767	3(中)
	0.3331	0.2176		0.2336		0.1735		0.9260	2(较低)
	0.1533	0.1151		0.0896		0.0614		0.0000	1(低)
EPI	X₆	X₇		X₈		X₉		X₁₀	等级
	1	1		1		1		1	5(高)
	0.8504	0.9760		0.9159		0.4288		0.9318	4(较高)
	0.7531	0.9493		0.8129		0.2366		0.8694	3(中)
	0.6383	0.8901		0.6665		0.1153		0.7630	2(较低)
	0.4488	0.4202		0.3832		0.0425		0.4770	1(低)
WPI	X₁₁		X₁₂		X₁₃		X₁₄		等级
	1		1		1		1		5(高)
	0.9250		0.7248		0.9245		0.9609		4(较高)
	0.8312		0.5046		0.8763		0.9181		3(中)
	0.6857		0.3224		0.7686		0.8423		2(较低)
	0.3970		0.1992		0.0000		0.0000		1(低)