Vol17 No.7: 1749-1762
【Title】Mapping determinants of rural poverty in Guangxi – a less developed region of China
【Author】ZHAO Yin-jun1,2; LU Yuan1,2*
【Addresses】1 Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning 530001, China; 2 School of Geography and Planning, Nanning Normal University, Nanning 530001, China
【Corresponding author】LU Yuan
【Citation】Zhao YJ, Lu Y (2020) Mapping determinants of rural poverty in Guangxi – a less developed region of China. Journal of Mountain Science 17(7). https://doi.org/10.1007/s11629-019-5760-9
【Abstract】Rapid urbanization in China has led to an increasing imbalance in regional development. The Guangxi Zhuang Autonomous Region, a less developed border province with unique cultural diversity, has a relatively large population (4.52million people in 2015) under the poverty line, according to the national standard of poverty. China has launched a national campaign to reduce poverty using a wide range of new development policies and large-scale investment. However, there have been few studies on the determinants of poverty at the county level across a province. This paper aims to explore the spatial and social differences related to poverty among 109 counties by considering the spatial heterogeneity of poverty determinants. Spatial statistical models revealed that slope (Slp), GDP per capita (GDPP), the ethnic minority population ratio (EMPR), medical and technical personnel of healthcare institutions (MTP) and illiteracy rate (IR) significantly affect the patterns of the poverty rate, with a high adjusted R2 (0.67), while the poverty rate affects GDPP, IR, MTP and EMPR; i.e., the effects are interactional. Furthermore, the IR is significantly affected by the provision of schools and transportation conditions. Among these determinants, social factors may be key. The spatial patterns of these relationships demonstrate remarkable variation across the province and between minor and major groups. This quantitative evidence is enhanced by in-depth interviews with selected groups. These results are expected to be useful for the anti-poverty project in Guangxi.
【Keywords】Determinants; Ordinary least squaresregression; Geographically weighted regression; Poverty; Spatial distribution; Guangxi