摘要:我国贫困人口分布呈现山区农村聚集现象，全面了解山区农村贫困现状、有效减少山区农村贫困对象是全面建成小康社会的重要任务。本文立足河北省太行山区贫困农村，以海拔与区位特征为依据，选择河北省平山县北冶乡的6个典型村镇为研究对象，通过提问式调查方式获取数据，选取收入、资本、生活水平3个维度9个指标构建评价指标体系，采用A-F（Alkire-Foste）法分析数据，得到北冶乡多维贫困测度结果。研究结果表明：1）北冶乡单维贫困状况仍较严重，各维度贫困发生率存在显著差异，贫困主要表现为资本维度的缺失。2）北冶乡多维贫困程度较深。3维贫困（贫困户）家庭超过90%，多维贫困指数随维度k的增加而降低。3）各指标对北冶乡多维贫困的贡献存在显著差异。人均耕地面积、教育、技能培训与卫生设施4个指标贡献率均超过15%，且随维度k的增加变化不大，是太行山区精准扶贫应着重关注的方面。4）教育缺失是导致贫困发生的内在因素，相对于教育未缺失家庭，教育缺失家庭的月收入更低、收入来源更单一、家庭人口规模更大。针对以上结论，提出采用等级优化模式整理农村居民点，从而进行教育资源整合与优化、助力山区脱贫的建议。
关键词:太行山区/
A-F方法/
农村多维贫困/
贫困深度/
贫困广度/
教育水平/
精准扶贫
Abstract:China has been working to alleviate since its reformation, and has made certain success. However, the poverty-stricken populations in China distributes in rural in mountainous areas for a long time. It is difficult to get rid of poverty in these lagging areas. A comprehensive understanding of the poverty situation in mountainous areas and effective techniques to reduce it have become important tasks for building a healthy society. We chose six typical villages in Taihang Mountain, Beiye Township, Pingshan County, Hebei Province based on elevation and geographical characteristics as the objectives. A question-based survey was conducted to obtain relative data. The evaluation index system was established with three dimensions-income, capital and living standard-and 9 indexes. The A-F (Alkire-Foste) method was used to analyze the results of multidimensional poverty measurement. The results showed that:1) the single-dimensional poverty situation in Beiye Township was still serious, and the causes of poverty were significantly different in all dimensions. Poverty mainly manifested as the absence of capital dimension. 2) The degree of multi-dimensional poverty in Beiye Township was deep. More than 90 percent of poor households lived in poverty. With an increase in dimension k, the multi-dimensional poverty index decreased. 3) The contribution of each index to the multi-dimensional poverty of Beiye Township was significantly different. The indexes of per capita cultivated land area, education, skill training and health facilities all contributed more than 15% and changed little when dimension k increased. 4) The lack of education was an internal factor that led to poverty. Compared to families with education, families without education had lower monthly income, single income source, and larger family size. In view of the above conclusions, this paper put forward the suggestions of using a hierarchical optimization mode to organize rural residential areas so as to integrate and optimize educational resources and help mountainous areas eliminate poverty.
Key words:Taihang Mountain Area/
A-F method/
Rural multi-dimensional poverty/
Poverty depth/
Poverty span/
Educational level/
Precise poverty alleviation
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