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    Human capital, non-agricultural employment and poverty reduction in rural families:An empirical analysis based on Wenquan County, Xinjiang
    WANG Huan-huan, WANG Hua-li
    HUBEI AGRICULTURAL SCIENCES    2022, 61 (17): 121-126.   DOI: 10.14088/j.cnki.issn0439-8114.2022.17.018
    Abstract360)      PDF (1419KB)(253)       Save
    In order to win the battle of poverty alleviation and consolidate the achievements of poverty alleviation, it is necessary to establish a long-term mechanism to solve relative poverty by stimulating internal forces, and human capital is an important factor to stimulate internal forces to alleviate relative poverty. Based on the perspective of human capital, this paper analyzed the impact of human capital on poverty reduction of rural families in Wenquan County of Xinjiang Uygur Autonomous Region by using the binary Logistic model, and discussed the mediating effect of non-agricultural employment level in the process of human capital acting on poverty. The results showed that the levels of education, health, skills training and migration of poor rural households are lower than those of non-poor rural households under relative poverty standards; education, health, skills training and migration of human capital have a significant indigenous impact on poverty reduction in rural households, and the role in alleviating relative poverty is health > skills training > migration > education; human capital will play a role in poverty reduction of rural families through the level of non-agricultural employment. Countermeasures to increase human capital accumulation and suggestions to promote non-agricultural employment are given.
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    Study on multidimensional relative poverty identification and its governance in deep poverty areas: Take Hotian County of Xinjiang as an example
    BUALI·Bakri, HALQAM·Siyiti
    HUBEI AGRICULTURAL SCIENCES    2022, 61 (17): 127-132.   DOI: 10.14088/j.cnki.issn0439-8114.2022.17.019
    Abstract378)      PDF (1412KB)(137)       Save
    Based on A-F multidimensional poverty measurement method, a multidimensional relative poverty identification index system is constructed to identify the multidimensional relative poverty in Hotian County, a deep poverty-stricken area in southern Xinjiang. It is found that about 52.127% of farmers have multidimensional poverty when κ=3 is taken as the poverty threshold. When decomposing the contribution rate of each dimension to multidimensional relative poverty, it is found that employment status and income level contribute the most to the multidimensional relative poverty of farmers. At κ=3, the multidimensional relative poverty level of women in the study area is significantly higher than that of men. The incidence of relative poverty among the elderly in the study area is relatively common; according to the type of farmers ' poverty, it is found that the poverty level of low-income cardholders is the deepest, and the relative poverty level increases with the increase of dimension. The countermeasures to solve the problem of multidimensional relative poverty are put forward.
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