Acta Geographica Sinica ›› 2018, Vol. 73 ›› Issue (10): 1850-1864.doi: 10.11821/dlxb201810003

• Land Consolidation and Rural Vitalization • Previous Articles     Next Articles

Spatial heterogeneity of multidimensional poverty at the village level: Loess Plateau

WEN Qi1,2(),SHI Linna1,2,MA Caihong1,2(),WANG Yongsheng3   

  1. 1. School of Resources and Environment, Ningxia University, Yinchuan 750021, China
    2. Key Laboratory (China-Arab) of Resource Evaluation and Environmental Regulation of Arid Region in Ningxia, Yinchuan 750021, China
    3. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2017-10-09 Online:2018-10-25 Published:2018-10-25
  • Supported by:
    National Natural Science Foundation of China, No.41661042, No.41761034;The Key R&D Program of Soft Science Project Foundation of Ningxia Hui Autonomous Region, No.NZY201604


Targeted poverty alleviation is a pillar of China's new and innovative anti-poverty and development strategy. China is an agricultural country with a large but poor rural population. At the village level, poverty alleviation has the potential to affect millions of citizens. The Loess Plateau is a composite of fragile ecological environment and rural poverty communities. As a backward economy often twins with fragile ecology, studying poverty from a multidimensional perspective in tandem with spatial heterogeneity and its influencing factors can provide an effective analysis of poverty in regions with characteristics similar to those of the Loess Plateau. This study features Pengyang, which is a poverty-stricken county located on the Loess Plateau, and relies on the approach by Alkire and Foster to measure multidimensional poverty, using spatial autocorrelation, Geodetector, OLSR and quantile regression (QR) analysis. Results from our investigation show that the study area has a deep level of multidimensional poverty, with a Multidimensional Poverty Index (MPI) score of 0.045. The rates of health, housing, and education dimensions were 0.263, 0.245, and 0.227, respectively. Moran's I of MPI was 0.2, which indicates that multidimensional poverty was positively correlated with a spatial pattern of "north, south, middle; high, high, low". Using Geodetector, the mean distance between villages and the center of town, as well as the mean elevation of the villages and mean distance to a river, were found to be the main factors of spatial heterogeneity within the MPI. The q-values of them were 0.552, 0.396, and 0.326, respectively, and the result of regression analysis conforms to the Geodetector. The interaction of the above factors enabled the creation of a multidimensional poverty spatial heterogeneity mechanism at village level for the Loess Plateau, revealing a lack in welfare of farmers, the poor of infrastructure, the congenital deficiency and stalled development of industry, and weak government functioning at the township level. Our results suggest that new strategies regarding urbanization should be investigated in order to improve and ensure the quality of public services in areas with similar characteristic as the Loess Plateau. These new strategies could enable the resolution of problems from the root, such as designing public goods and services that fill gaps in current health care and housing options, as well as the operation of transport facilities at the village level. This could help to mitigate welfare loss of farmers as well as reduce the negative impact of health, housing, education, and other dimensions of poverty.

Key words: multidimensional poverty, spatial heterogeneity, Geodetector, quantile regression, Loess Plateau