Has significant improvement achieved related to the livelihood capital of rural households after the effort of reducing poverty at large scale? New evidence from a survey of the severe poverty areas in China
被引:5
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Mai, Qiangsheng
[1
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Luo, Mingcan
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机构:
Southwest Forestry Univ, Sch Econ & Management, Kunming, Yunnan, Peoples R ChinaSouthwest Forestry Univ, Sch Accounting, Kunming 650224, Yunnan, Peoples R China
Luo, Mingcan
[2
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Chen, Jiancheng
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Beijing Forestry Univ, Sch Econ & Management, Beijing, Peoples R ChinaSouthwest Forestry Univ, Sch Accounting, Kunming 650224, Yunnan, Peoples R China
Chen, Jiancheng
[3
]
机构:
[1] Southwest Forestry Univ, Sch Accounting, Kunming 650224, Yunnan, Peoples R China
[2] Southwest Forestry Univ, Sch Econ & Management, Kunming, Yunnan, Peoples R China
[3] Beijing Forestry Univ, Sch Econ & Management, Beijing, Peoples R China
Analyzing the livelihood capital of rural households can be beneficial for informing the effect of poverty alleviation, after several years of sustained efforts of poverty alleviation at large scale in China. Based on original data from a household survey in two severe poverty areas of China (Wumeng Mountains and Western Border Mountains) and a non-poverty area (reference), this study uses a new 5-point scale to extract information, and then analyzes the effects of poverty alleviation on the poor households through regression analysis and variance analysis. The results show that the livelihood capital of rural households in the severe poverty areas has been improved but still vulnerable if compared with non-poverty area. The livelihood capitals are 39.13% and 36.04% lower than those in non-poverty area by regression model, respectively. It also can be found that, due to the combined effect of multiple factors, the control variable has a significant effect on the livelihood capital. The change of livelihood capital is more significant than that of single dimension capital in terms of poverty caused by getting illness and out of poverty caused by mastering skill. Further analysis of interactive variance demonstrates difference between the severe poverty areas, also between poverty and non-poverty areas. Focusing on increasing land benefit, enhancing county-level of industrial layout, developing better medical security, highlighting educational level, maintaining the continuity of policies represent effective methods of poverty alleviation. This study helps to better understand the optimization of poverty alleviation and improve related policies.