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Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
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Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
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Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China

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Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China
Journal Article

Classification of Rural Relative Poverty Groups and Measurement of the Influence of Land Elements: A Questionnaire-Based Analysis of 23 Poor Counties in China

2023
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Overview
In 2021, China achieved an all-round victory in the fight against poverty and completed the task of eliminating absolute poverty. However, relative poverty will still exist for a long time. According to the degree of relative poverty, this paper divided rural population into four groups, incapability group, vulnerable group, marginal group and non-relative poverty group, to further explore the differences in specific land elements requirements among different groups. Firstly, ten factors were selected as evaluation indexes, including per capita household income, education level, poverty registration situation, employment situation, critical disease situation, natural disaster frequency situation, etc. By extracting 100 relative poverty group evaluation units as samples, the authors established a decision tree for rural relative poverty group evaluation based on an improved ID3 algorithm. Secondly, we quantified the effect of different land elements. Considering the resource, asset and capital function of land, this paper constructed an ordered logistic model with four groups as classification variables. The result showed that: (1) a better condition of land resource endowment leads to a lower degree of rural relative poverty; however, over-reliance on land increases the risk of relative poverty; (2) except for cultivation income and land transfer income, asset value and capital value of rural land are not evident. Suggestions are put forward: use land elements to build a long-term mechanism for rural relative poverty alleviation; improve the quantity, quality and spatial endowment of rural land resources; optimize the rural land property rights and land acquisition system; realize the market-based mechanism for rural land transfer; and implement the policy of Increase and Decrease Connection of Urban and Rural Construction Land.