Journal of Geographical Sciences ›› 2018, Vol. 28 ›› Issue (10): 1444-1466.doi: 10.1007/s11442-018-1555-0

• Orginal Article • Previous Articles     Next Articles

Village-level multidimensional poverty measurement in China: Where and how

Yanhui WANG1,2,3(), Yefeng CHEN1,2,3, Yao CHI1,2,3, Wenji ZHAO1,2,3, Zhuowei HU1,2,3, Fuzhou DUAN1,2,3*()   

  1. 1. Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China
    2. Key Laboratory of 3-Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China
    3. State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China
  • Received:2017-10-20 Accepted:2017-12-10 Online:2018-10-25 Published:2018-10-25
  • About author:

    Author: Wang Yanhui (1977-), PhD and Professor, E-mail: huiwangyan@sohu.com

  • Supported by:
    National Natural Science Foundation of China, No.41771157;National Key Research and Development Program of China, No.2018YFB0505402;Scientific Research Project of Beijing Education Committee, No.KM201810028014;Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds, No.025185305000/192

Abstract:

Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error (LSE) model and spatial econometric analysis model to identify the villages’ poverty types and poverty difference. The case study shows that: (1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang. (2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions. (3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type. (4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of poverty alleviation at all levels to mobilize all kinds of anti-poverty resources.

Key words: poor village, multidimensional poverty measurement, poverty type, poverty factors, spatial econometric analysis