PROGRESS IN GEOGRAPHY ›› 2020, Vol. 39 ›› Issue (6): 1013-1023.doi: 10.18306/dlkxjz.2020.06.011

• Special Issue | Multidimensional Poverty and Livelihood Sustainability • Previous Articles     Next Articles

Spatial difference of multidimensional poverty and its influencing factors in the rural areas of Hainan Province

ZHANG Jinping, LIN Dan, ZHOU Xiangli, YU Zhenxin, SONG Wei, CHENG Yeqing*()   

  1. College of Geography and Environmental Sciences, Hainan Normal University, Haikou 571158, China
  • Received:2020-01-08 Revised:2020-05-09 Online:2020-06-28 Published:2020-08-28
  • Contact: CHENG Yeqing E-mail:34794249@qq.com
  • Supported by:
    National Natural Science Foundation of China(41661028);National Natural Science Foundation of China(41761118);Natural Science Foundation of Hainan Province(417099);Natural Science Foundation of Hainan Province(418MS052);High-level Talent Project of Natural Science Foundation of Hainan Province(2019RC178);Innovative Research Project for Postgraduates of Hainan Province in 2019(Hys2019-240)

Abstract:

Poverty has multidimensional attributes, and it has become a consensus to study poverty from a multidimensional perspective according to different social groups and backgrounds. In order to measure the multidimensional poverty situation in the rural areas where the poor population is concentrated in Hainan Province, we expanded the index system based on the exit criteria for targeted poverty alleviation fulfilling the basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, and established a multidimensional poverty assessment conceptual model for rural households in Hainan Province that covers education, health, housing, livelihood, and income indicators. Then, based on household survey data from 3924 households in 70 towns and 134 poor villages of Hainan Province in 2018, we used the double threshold Alkire-Foster (A-F) method to evaluate the multidimensional poverty status of rural households and villages, and then used the geographically weighted regression (GWR) model to analyze the spatial heterogeneity of the influencing factors of multidimensional poverty in villages. The study results show that: 1) The incidence of multidimensional poverty of the surveyed households was 18.22%. But the incidence of multidimensional poverty in villages with severe multidimensional poverty is not necessarily high. 2) The four indicators of farming households' asset status, cooking fuels, family members' diseases, and family members’ highest academic qualifications contribute the most to multidimensional poverty, while the contribution ratio of indicators belonging to the standard of fulfilling basic needs of food and clothing and guaranteeing compulsory education, basic medical care, and housing, as well as income are generally not high. The multidimensional poverty in the contiguous poverty areas in the central and western regions of the province is mainly manifested by poor asset conditions, unclean cooking fuels, high prevalence of disease of family members, and lower education levels. 3) The GWR model analysis showed that as the most important influencing factors of multidimensional poverty, spatial heterogeneity of the estimated coefficients of the four variables, gender of the household head, education level of the household head, ratio of female labor force, and dependency ratio, have very obvious impacts. In general, areas with more female-headed and low-education attainment individual headed households tend to be more prone to multidimensional poverty, and their impacts increased from east to west and from north to south, separately. With an increasing trend from north to south, the effect of the proportion of female labor force is negative and that of the dependency ratio is positive, which reflects the typical regional characteristics of weak labor force and relatively more industrious women in Hainan poverty-stricken areas.

Key words: multidimensional poverty, Alkire-Foster (A-F) method, geographically weighted regression (GWR), spatial heterogeneity, Hainan Province