地理学报 ›› 2018, Vol. 73 ›› Issue (8): 1478-1493.doi: 10.11821/dlxb201808007

• 城市与区域发展 • 上一篇    下一篇

中国县域贫困综合测度及2020年后减贫瞄准

周扬1,2(),郭远智1,2,3(),刘彦随1,2,3()   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101
    2. 中国科学院精准扶贫评估研究中心,北京 100101
    3. 中国科学院大学,北京 100049
  • 收稿日期:2017-10-31 出版日期:2018-08-15 发布日期:2018-07-31
  • 基金资助:
    国家社会科学基金重大项目(15ZDA021);国家自然科学基金项目(41601172, 41471143, 41371186);中国博士后科学基金项目(2016M591105)

Comprehensive measurement of county poverty and anti-poverty targeting after 2020 in China

ZHOU Yang1,2(),GUO Yuanzhi1,2,3,LIU Yansui1,2,3   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Center for Assessment and Research on Targeted Poverty Alleviation, CAS, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2017-10-31 Online:2018-08-15 Published:2018-07-31
  • Supported by:
    National Social Science Foundation of China, No.15ZDA 021;National Natural Science Foundation of China, No.41601172, No.41471143, No.41371186;China Postdoctoral Science Foundation, No.2016M591105

摘要:

贫困问题长期以来受到世界各国的重点关注。科学揭示农村贫困发生机制、贫困化格局和探究2020年后减贫瞄准策略,成为新时代中国农村贫困问题研究的重要议题。本文基于人地关系地域系统理论,多维度剖析了中国农村贫困的发生机理,构建了表征县域贫困压力的指标体系,运用BP神经网络模型对县域多维贫困压力指数进行了综合测度,识别出2020年后国家政策仍需重点倾斜的帮扶县,并划分出帮扶县的4种类型。结果表明:① 人类发展能力、自然资源禀赋、社会经济发展及由这三个维度构成的县域综合发展能力呈现出自东南沿海向西北内陆递减的规律,并与地势的三级阶梯呈现出一致性;② 2020年后仍需要国家政策倾斜的帮扶县有716个,主要分布在青藏高原高寒区、三级阶梯的过渡地带、西南喀斯特地区等生态脆弱区和少数民族集聚区;③ 识别的帮扶县可以划分为综合制约型一类重点帮扶县、人类发展能力制约型二类一般帮扶县、自然资源禀赋和社会经济水平制约型三类一般帮扶县,以及人类发展能力和社会经济水平制约型四类一般帮扶县,重点帮扶县主要集中在深度贫困地区。新时期中国贫困格局、贫困化机制、减贫路径及问题和模式,亟需深化创新精准扶贫的体制机制,这为重视和加强贫困地理学的研究提出了新机遇和新挑战。

关键词: 贫困, 人地关系地域系统, 多维贫困, 地理格局, 减贫瞄准, 贫困地理学, 中国

Abstract:

Poverty has long been the focus of all countries in the world. To achieve the goal of building a moderately prosperous society in all aspects, Chinese government clearly points out that all rural residents living below the current poverty line should be lifted out of poverty, and poverty should be eliminated in all poverty-stricken counties and regions by 2020. But due to the limitation of development capacity, the improvement of the new poverty standard and living standard, there will still be quite a large number of people in poverty in future and it will exist for a long time. Thus, it is of great significance to study the pattern of rural poverty and the poverty stress at county level in China and investigate anti-poverty targeting after 2020. To this end, we first analyze the mechanism of rural poverty from the perspective of man-land areal system and construct an indicator system of county development index (CDI) to characterize county poverty stress. Then the BP neural network model is applied to measure the poverty stress and identify the county that still need policy-support (CNPS) after 2020 when the goal of eliminating poverty is achieved. Results show that poverty is a manifestation of the imbalance between human system and land system, which can be measured by three aspects, i.e., human development capability, natural resource endowment and socio-economic development. The deficiency of natural resource endowments is one of the main causes of poverty, while socio-economic development and improvement of agricultural production conditions make contribution to poverty alleviation in rural areas. Human development capability, socio-economic level, natural resource endowment and comprehensive development at county level in China show a gradient decrement from the southeast coast to the northwest inland, which can be divided into three agglomerated areas by the three ladders of the terrain. More concretely, high-cold regions of Tibetan Plateau and its periphery, as well as arid areas in the west of South Xinjiang are the low-value areas of CDI. The eastern coastal areas, Sichuan Basin and the middle and lower reaches of the Yangtze River, where the natural condition is good and the level of economic development is high, are the middle-high-/high-value areas of CDI. At last, the standard deviation of CDI is applied to measure poverty stress at county level. Results show that 716 counties need to be further focused by national anti-poverty policies after 2020, most of which are distributed in the high-cold region of Tibetan Plateau, the transition zone of the three ladders and the Karst region in Southwest China. These counties can be roughly divided into four types, i.e., key aiding counties restricted by multidimensional factors (Type Ⅰ), general aiding counties restricted by human development capability (Type Ⅱ), general aiding counties restricted by both natural resource endowment and socio-economic development (Type Ⅲ), and tgeneral aiding counties restricted by both human development capability and socio-economic development (Type Ⅳ). Understanding poverty patterns and its dynamic mechanisms as well as the ways to poverty reduction in the new period can enrich the study of poverty geography.

Key words: poverty, man-land areal system, multidimensional poverty, geographical pattern, poverty alleviation targeting, poverty geography, China