Abstract

Poverty is a severe problem faced by all nations. Eradicating poverty tops first in the Sustainable Development Goals. The elimination of poverty requires an understanding of what are the key contributors to poverty reduction, which makes it crucial to track the progress of poverty elimination for effective policy intervention and adjustment. Nevertheless, most present studies are limited to poverty prediction at a certain point in time, with less research conducted to investigate the dynamic spatial determinants of poverty eradication. China successfully eliminated extreme poverty at the end of 2020, and thus is a good example to investigate what causes poverty and how it is eradicated. Concerning the poverty reduction in China from 2014 to 2020, we combine multi-source geospatial data and random forest to answer what spatial factors cause poverty and which ones contribute most to poverty eradication. Results indicate that urbanization level and commercial development are the top two contributors to poverty identification, and they inherently determine the occurrence of poverty. It is interesting to observe that the rapid change of socioeconomic features represented by the restaurants is the major determinant in the process of poverty elimination. We suppose the multiple poverty alleviation pathways have led to the development of the catering industry, which helps lift the counties out of poverty. Overall, all the Chinese counties are moving towards a more balanced development with decreasing differences between poverty-stricken and non-poverty counties plus a decreased Gini index from 2014 to 2020. This comprehensive analysis benefits us in the understanding of the spatial determinants of poverty identification and elimination in China, which provides a solid example of poverty reduction in other developing countries.

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