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Spatial distribution pattern and influencing factors of relative poverty in rural China

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  • Tang, Kai
  • Li, Zhenshan
  • He, Chun

Abstract

Exploring the spatial distribution pattern of rural relative poverty and its influencing factors is of great significance for solving the problem of poverty. This research calculates the relative poverty level of rural areas in China by using POVCAL software of the World Bank according to income grouping data and analyzes the spatial and temporal pattern characteristics. After establishing a spatial Durbin model to explore the influencing factors of rural relative poverty in China, the results are as follows. The level of relative poverty in rural China is on the rise as a whole, and there is a certain spatial dependence characteristic. Education differentiation and income gap between urban and rural areas have an aggravating effect on rural relative poverty, while rural medical level, rural social security level, and urban-rural segmentation can alleviate rural relative poverty.

Suggested Citation

  • Tang, Kai & Li, Zhenshan & He, Chun, 2023. "Spatial distribution pattern and influencing factors of relative poverty in rural China," Innovation and Green Development, Elsevier, vol. 2(1).
    • Handle: RePEc:eee:ingrde:v:2:y:2023:i:1:s2949753122000303
    DOI: 10.1016/j.igd.2022.100030
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    1. Han, Jixuan & Li, Tianshu & Philbin, Simon P., 2023. "Does low-carbon pilot policy in China improve corporate profitability? The role of innovation and subsidy," Innovation and Green Development, Elsevier, vol. 2(2).
    2. Li, Shuangyan & Chang, Ge & Zunong, Reyihanguli, 2023. "Does regional digital economy development influence green investment?," Innovation and Green Development, Elsevier, vol. 2(3).

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